initial import of Michael Zucchi's port of Apples FFT example (RFE 408).

small modifications:
 - pick CLPlatform with a GPU
 - replaced tabs with spaces :)

4 files changed, 2612 insertions, 0 deletions

diff --git a/src/com/jogamp/opencl/demos/fft/BlurTest.java b/src/com/jogamp/opencl/demos/fft/BlurTest.java
new file mode 100644
index 0000000..c08da43
--- /dev/null
+++ b/src/com/jogamp/opencl/demos/fft/BlurTest.java
@@ -0,0 +1,521 @@
+package com.jogamp.opencl.demos.fft;
+
+import com.jogamp.opencl.CLBuffer;
+import com.jogamp.opencl.CLCommandQueue;
+import com.jogamp.opencl.CLContext;
+import com.jogamp.opencl.CLDevice;
+import com.jogamp.opencl.CLKernel;
+import com.jogamp.opencl.CLMemory.Mem;
+import com.jogamp.opencl.CLPlatform;
+import com.jogamp.opencl.CLProgram;
+import com.jogamp.opencl.demos.fft.CLFFTPlan.InvalidContextException;
+import java.awt.BorderLayout;
+import java.awt.Dimension;
+import java.awt.Graphics;
+import java.awt.GridBagConstraints;
+import java.awt.GridBagLayout;
+import java.awt.Insets;
+import java.awt.event.ActionEvent;
+import java.awt.event.ActionListener;
+import java.awt.image.BufferedImage;
+import java.awt.image.DataBufferByte;
+import java.awt.image.DataBufferInt;
+import java.io.File;
+import java.io.FileInputStream;
+import java.io.IOException;
+import java.nio.ByteBuffer;
+import java.nio.FloatBuffer;
+import java.nio.IntBuffer;
+import java.util.logging.Level;
+import java.util.logging.Logger;
+import javax.imageio.ImageIO;
+import javax.swing.BoxLayout;
+import javax.swing.ButtonGroup;
+import javax.swing.JButton;
+import javax.swing.JFileChooser;
+import javax.swing.JFrame;
+import javax.swing.JLabel;
+import javax.swing.JOptionPane;
+import javax.swing.JPanel;
+import javax.swing.JSlider;
+import javax.swing.JToggleButton;
+import javax.swing.SwingUtilities;
+import javax.swing.event.ChangeEvent;
+import javax.swing.event.ChangeListener;
+
+/**
+ * Perform some user-controllable blur on an image.
+ * @author notzed
+ */
+public class BlurTest implements Runnable, ChangeListener, ActionListener {
+
+    public static void main(String[] args) {
+        SwingUtilities.invokeLater(new BlurTest());
+    }
+    
+    boolean demo = false;
+    // must be power of 2 and width must be multiple of 64
+    int width = 512;
+    int height = 512;
+    BufferedImage src;
+    BufferedImage psf;
+    BufferedImage dst;
+    PaintView left;
+    ImageView right;
+    //
+    JSlider sizex;
+    JSlider sizey;
+    JSlider angle;
+    //
+    JToggleButton blurButton;
+    JToggleButton drawButton;
+
+    public void run() {
+        try {
+            initCL();
+        } catch (Exception x) {
+            System.out.println("failed to init cl");
+            x.printStackTrace();
+            System.exit(1);
+        }
+
+        JFileChooser fc = new JFileChooser();
+        BufferedImage img = null;
+
+        while (img == null) {
+            try {
+                File file = null;
+
+                if (true) {
+                    fc.setDialogTitle("Select Image File");
+                    fc.setPreferredSize(new Dimension(500, 600));
+                    if (fc.showOpenDialog(null) == JFileChooser.APPROVE_OPTION) {
+                        file = fc.getSelectedFile();
+                    } else {
+                        System.exit(0);
+                    }
+
+                } else {
+                    file = new File("/home/notzed/cat0.jpg");
+                }
+                img = ImageIO.read(file);
+                if (img == null) {
+                    JOptionPane.showMessageDialog(null, "Couldn't load file");
+                }
+            } catch (IOException x) {
+                JOptionPane.showMessageDialog(null, "Couldn't load file");
+            }
+        }
+
+        src = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
+        dst = new BufferedImage(width, height, BufferedImage.TYPE_INT_RGB);
+        psf = new BufferedImage(width, height, BufferedImage.TYPE_BYTE_GRAY);
+
+        // Ensure loaded image is in known format and size
+        Graphics g = src.createGraphics();
+        g.drawImage(img, (width - img.getWidth()) / 2, (height - img.getHeight()) / 2, null);
+        g.dispose();
+
+        JFrame win = new JFrame("Blur Demo");
+        win.setDefaultCloseOperation(win.EXIT_ON_CLOSE);
+
+        JPanel main = new JPanel();
+        main.setLayout(new BorderLayout());
+
+        JPanel controls = new JPanel();
+        controls.setLayout(new GridBagLayout());
+
+        GridBagConstraints c0 = new GridBagConstraints();
+        c0.gridx = 0;
+        c0.anchor = GridBagConstraints.BASELINE_LEADING;
+        c0.ipadx = 3;
+        c0.insets = new Insets(1, 2, 1, 2);
+
+        controls.add(new JLabel("Width"), c0);
+        controls.add(new JLabel("Height"), c0);
+
+        GridBagConstraints c2 = (GridBagConstraints) c0.clone();
+        c2.gridx = 2;
+        controls.add(new JLabel("Angle"), c2);
+
+        c0 = (GridBagConstraints) c0.clone();
+        c0.gridx = 1;
+        c0.weightx = 1;
+        c0.fill = GridBagConstraints.HORIZONTAL;
+        sizex = new JSlider(100, 5000, 1000);
+        sizey = new JSlider(100, 5000, 100);
+        controls.add(sizex, c0);
+        controls.add(sizey, c0);
+
+        c2 = (GridBagConstraints) c0.clone();
+        c2.gridx = 3;
+        angle = new JSlider(0, (int) (Math.PI * 1000));
+        controls.add(angle, c2);
+
+        sizex.addChangeListener(this);
+        sizey.addChangeListener(this);
+        angle.addChangeListener(this);
+
+        JPanel buttons = new JPanel();
+        controls.add(buttons, c2);
+        JButton b;
+        b = new JButton("Clear");
+        buttons.add(b);
+        b.addActionListener(new ActionListener() {
+
+            public void actionPerformed(ActionEvent e) {
+                doclear();
+            }
+        });
+        ButtonGroup opt = new ButtonGroup();
+        JToggleButton tb;
+        blurButton = new JToggleButton("Blur");
+        opt.add(blurButton);
+        buttons.add(blurButton);
+        blurButton.addActionListener(this);
+        drawButton = new JToggleButton("Draw");
+        opt.add(drawButton);
+        buttons.add(drawButton);
+        drawButton.addActionListener(this);
+
+        JPanel imgs = new JPanel();
+        imgs.setLayout(new BoxLayout(imgs, BoxLayout.X_AXIS));
+        left = new PaintView(this, psf);
+        right = new ImageView(dst);
+        imgs.add(left);
+        imgs.add(right);
+
+        main.add(controls, BorderLayout.NORTH);
+        main.add(imgs, BorderLayout.CENTER);
+        win.getContentPane().add(main);
+
+        win.pack();
+        win.setVisible(true);
+
+        // pre-load and transform src, since that wont change
+        loadSource(src);
+
+        blurButton.doClick();
+    }
+
+    public void stateChanged(ChangeEvent e) {
+        if (drawButton.isSelected()) {
+            recalc();
+        } else {
+            double w = sizex.getValue() / 100.0;
+            double h = sizey.getValue() / 100.0;
+            double a = angle.getValue() / 1000.0;
+
+            Graphics g = psf.createGraphics();
+
+            g.clearRect(0, 0, width, height);
+            g.dispose();
+
+            left.drawDot(w, h, a);
+        }
+    }
+
+    public void actionPerformed(ActionEvent e) {
+        stateChanged(null);
+    }
+
+    private void doclear() {
+        Graphics g = psf.createGraphics();
+
+        g.clearRect(0, 0, width, height);
+        g.dispose();
+        left.repaint();
+        recalc();
+    }
+
+    private void dorecalc() {
+        loadPSF(psf);
+
+        // convolve each plane in freq domain
+        convolve(aCBuffer, psfBuffer, aGBuffer);
+        convolve(rCBuffer, psfBuffer, rGBuffer);
+        convolve(gCBuffer, psfBuffer, gGBuffer);
+        convolve(bCBuffer, psfBuffer, bGBuffer);
+
+        // convert back to spatial domain
+        fft.executeInterleaved(q, 1, CLFFTPlan.CLFFTDirection.Inverse, aGBuffer, aBuffer, null, null);
+        fft.executeInterleaved(q, 1, CLFFTPlan.CLFFTDirection.Inverse, rGBuffer, rBuffer, null, null);
+        fft.executeInterleaved(q, 1, CLFFTPlan.CLFFTDirection.Inverse, gGBuffer, gBuffer, null, null);
+        fft.executeInterleaved(q, 1, CLFFTPlan.CLFFTDirection.Inverse, bGBuffer, bBuffer, null, null);
+
+        // while gpu is running, calculate energy of psf
+        float scale;
+
+        long total = 0;
+        DataBufferByte pd = (DataBufferByte) psf.getRaster().getDataBuffer();
+        byte[] data = pd.getData();
+        for (int i = 0; i < data.length; i++) {
+            total += data[i] & 0xff;
+        }
+        scale = 255.0f / total / width / height;
+
+        getDestination(argbBuffer, aBuffer, rBuffer, gBuffer, bBuffer, scale);
+
+        // drop back to java, slow-crappy-method
+        q.putReadBuffer(argbBuffer, true);
+        DataBufferInt db = (DataBufferInt) dst.getRaster().getDataBuffer();
+        argbBuffer.getBuffer().position(0);
+        argbBuffer.getBuffer().get(db.getData());
+        argbBuffer.getBuffer().position(0);
+        right.repaint();
+    }
+    Runnable later;
+
+    void recalc() {
+        if (later == null) {
+            later = new Runnable() {
+
+                public void run() {
+                    later = null;
+                    dorecalc();
+                }
+            };
+            SwingUtilities.invokeLater(later);
+        }
+    }
+    CLContext cl;
+    CLCommandQueue q;
+    CLProgram prog;
+    CLKernel kImg2Planes;
+    CLKernel kPlanes2Img;
+    CLKernel kGrey2Plane;
+    CLKernel kConvolve;
+    CLKernel kDeconvolve;
+    CLFFTPlan fft;
+    CLBuffer<IntBuffer> argbBuffer;
+    CLBuffer<ByteBuffer> greyBuffer;
+    CLBuffer<FloatBuffer> aBuffer;
+    CLBuffer<FloatBuffer> rBuffer;
+    CLBuffer<FloatBuffer> gBuffer;
+    CLBuffer<FloatBuffer> bBuffer;
+    CLBuffer<FloatBuffer> aCBuffer;
+    CLBuffer<FloatBuffer> rCBuffer;
+    CLBuffer<FloatBuffer> gCBuffer;
+    CLBuffer<FloatBuffer> bCBuffer;
+    CLBuffer<FloatBuffer> aGBuffer;
+    CLBuffer<FloatBuffer> rGBuffer;
+    CLBuffer<FloatBuffer> gGBuffer;
+    CLBuffer<FloatBuffer> bGBuffer;
+    CLBuffer<FloatBuffer> psfBuffer;
+    CLBuffer<FloatBuffer> tmpBuffer;
+    //
+    CLKernel fft512;
+
+    void initCL() throws InvalidContextException {
+        
+        // search a platform with a GPU
+        CLPlatform[] platforms = CLPlatform.listCLPlatforms();
+        CLDevice gpu = null;
+        for (CLPlatform platform : platforms) {
+            gpu = platform.getMaxFlopsDevice(CLDevice.Type.GPU);
+            if(gpu != null) {
+                break;
+            }
+        }
+
+        cl = CLContext.create(gpu);
+
+        q = cl.getDevices()[0].createCommandQueue();
+
+        prog = cl.createProgram(img2Planes + planes2Img + convolve + grey2Plane + deconvolve);
+        prog.build("-cl-mad-enable");
+
+        kImg2Planes = prog.createCLKernel("img2planes");
+        kPlanes2Img = prog.createCLKernel("planes2img");
+        kGrey2Plane = prog.createCLKernel("grey2plane");
+        kConvolve = prog.createCLKernel("convolve");
+        kDeconvolve = prog.createCLKernel("deconvolve");
+
+        argbBuffer = cl.createIntBuffer(width * height, Mem.READ_WRITE);
+        greyBuffer = cl.createByteBuffer(width * height, Mem.READ_WRITE);
+        aBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        rBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        gBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        bBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        psfBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        tmpBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+
+        aCBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        rCBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        gCBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        bCBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+
+        aGBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        rGBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        gGBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        bGBuffer = cl.createFloatBuffer(width * height * 2, Mem.READ_WRITE);
+        if (false) {
+            try {
+                CLProgram p = cl.createProgram(new FileInputStream("/home/notzed/cl/fft-512.cl"));
+                p.build();
+                fft512 = p.createCLKernel("fft0");
+            } catch (IOException ex) {
+                Logger.getLogger(BlurTest.class.getName()).log(Level.SEVERE, null, ex);
+            }
+        } else {
+            fft = new CLFFTPlan(cl, new int[]{width, height}, CLFFTPlan.CLFFTDataFormat.InterleavedComplexFormat);
+        }
+        //fft.dumpPlan(null);
+    }
+
+    void loadSource(BufferedImage src) {
+        DataBufferInt sb = (DataBufferInt) src.getRaster().getDataBuffer();
+
+        argbBuffer.getBuffer().position(0);
+        argbBuffer.getBuffer().put(sb.getData());
+        argbBuffer.getBuffer().position(0);
+        q.putWriteBuffer(argbBuffer, false);
+
+        kImg2Planes.setArg(0, argbBuffer);
+        kImg2Planes.setArg(1, 0);
+        kImg2Planes.setArg(2, width);
+        kImg2Planes.setArg(3, aBuffer);
+        kImg2Planes.setArg(4, rBuffer);
+        kImg2Planes.setArg(5, gBuffer);
+        kImg2Planes.setArg(6, bBuffer);
+        kImg2Planes.setArg(7, 0);
+        kImg2Planes.setArg(8, width);
+        q.put2DRangeKernel(kImg2Planes, 0, 0, width, height, 64, 1);
+        q.finish();
+
+        fft.executeInterleaved(q, 1, CLFFTPlan.CLFFTDirection.Forward, aBuffer, aCBuffer, null, null);
+        fft.executeInterleaved(q, 1, CLFFTPlan.CLFFTDirection.Forward, rBuffer, rCBuffer, null, null);
+        fft.executeInterleaved(q, 1, CLFFTPlan.CLFFTDirection.Forward, gBuffer, gCBuffer, null, null);
+        fft.executeInterleaved(q, 1, CLFFTPlan.CLFFTDirection.Forward, bBuffer, bCBuffer, null, null);
+    }
+
+    void loadPSF(BufferedImage psf) {
+        assert (psf.getType() == BufferedImage.TYPE_BYTE_GRAY);
+        DataBufferByte pb = (DataBufferByte) psf.getRaster().getDataBuffer();
+
+        greyBuffer.getBuffer().position(0);
+        greyBuffer.getBuffer().put(pb.getData());
+        greyBuffer.getBuffer().position(0);
+        q.putWriteBuffer(greyBuffer, false);
+
+        kGrey2Plane.setArg(0, greyBuffer);
+        kGrey2Plane.setArg(1, 0);
+        kGrey2Plane.setArg(2, width);
+        kGrey2Plane.setArg(3, tmpBuffer);
+        kGrey2Plane.setArg(4, 0);
+        kGrey2Plane.setArg(5, width);
+        q.put2DRangeKernel(kGrey2Plane, 0, 0, width, height, 64, 1);
+
+        if (true) {
+            fft.executeInterleaved(q, 1, CLFFTPlan.CLFFTDirection.Forward, tmpBuffer, psfBuffer, null, null);
+        } else if (true) {
+            fft512.setArg(0, tmpBuffer);
+            fft512.setArg(1, psfBuffer);
+            fft512.setArg(2, -1);
+            fft512.setArg(3, height);
+            //q.put1DRangeKernel(fft512, 0,height*64, 64);
+            q.put2DRangeKernel(fft512, 0, 0, height * 64, 1, 64, 1);
+            System.out.println("running kernel " + 64 * height + ", " + 64);
+        }
+    }
+
+    // g = f x h
+    void convolve(CLBuffer<FloatBuffer> h, CLBuffer<FloatBuffer> f, CLBuffer<FloatBuffer> g) {
+        kConvolve.setArg(0, h);
+        kConvolve.setArg(1, f);
+        kConvolve.setArg(2, g);
+        kConvolve.setArg(3, width);
+        q.put2DRangeKernel(kConvolve, 0, 0, width, height, 64, 1);
+    }
+
+    // g = h*conj(f) / (abs(f)^2 + k)
+    void deconvolve(CLBuffer<FloatBuffer> h, CLBuffer<FloatBuffer> f, CLBuffer<FloatBuffer> g, float k) {
+        kDeconvolve.setArg(0, h);
+        kDeconvolve.setArg(1, f);
+        kDeconvolve.setArg(2, g);
+        kDeconvolve.setArg(3, width);
+        kDeconvolve.setArg(4, k);
+        q.put2DRangeKernel(kDeconvolve, 0, 0, width, height, 64, 1);
+    }
+
+    void getDestination(CLBuffer<IntBuffer> dst, CLBuffer<FloatBuffer> a, CLBuffer<FloatBuffer> r, CLBuffer<FloatBuffer> g, CLBuffer<FloatBuffer> b, float scale) {
+        kPlanes2Img.setArg(0, dst);
+        kPlanes2Img.setArg(1, 0);
+        kPlanes2Img.setArg(2, width);
+        kPlanes2Img.setArg(3, a);
+        kPlanes2Img.setArg(4, r);
+        kPlanes2Img.setArg(5, g);
+        kPlanes2Img.setArg(6, b);
+        kPlanes2Img.setArg(7, 0);
+        kPlanes2Img.setArg(8, width);
+        kPlanes2Img.setArg(9, scale);
+        q.put2DRangeKernel(kPlanes2Img, 0, 0, width, height, 64, 1);
+    }
+    // Convert packed ARGB byte image to planes of complex floats
+    final String img2Planes =
+              "kernel void img2planes(global const uchar4 *argb, int soff, int sstride,"
+            + "  global float2 *a, global float2 *r, global float2 *g, global float2 *b, int doff, int dstride) {"
+            + " int gx = get_global_id(0);"
+            + " int gy = get_global_id(1);"
+            + " uchar4 v = argb[soff+sstride*gy+gx];"
+            + " float4 ff = convert_float4(v) * (float4)(1.0f/255);"
+            + " doff += (dstride * gy + gx);"
+            + " b[doff] = (float2){ ff.s0, 0 };\n"
+            + " g[doff] = (float2){ ff.s1, 0 };"
+            + " r[doff] = (float2){ ff.s2, 0 };"
+            + " a[doff] = (float2){ ff.s3, 0 };\n"
+            + "}\n\n";
+    // not the best implementation
+    // this also performs an 'fftshift'
+    final String grey2Plane =
+              "kernel void grey2plane(global const uchar *src, int soff, int sstride,"
+            + "  global float2 *dst, int doff, int dstride) {"
+            + " int gx = get_global_id(0);"
+            + " int gy = get_global_id(1);"
+            + " uchar v = src[soff+sstride*gy+gx];"
+            + " float ff = convert_float(v) * (1.0f/255);"
+            // fftshift
+            + " gx ^= get_global_size(0)>>1;"
+            + " gy ^= get_global_size(1)>>1;"
+            + " doff += (dstride * gy + gx);"
+            + " dst[doff] = (float2) { ff, 0 };"
+            + "}\n\n";
+    // This also does the 'fftscale' after the inverse fft.
+    final String planes2Img =
+              "kernel void planes2img(global uchar4 *argb, int soff, int sstride, const global float2 *a, const global float2 *r, const global float2 *g, const global float2 *b, int doff, int dstride, float scale) {"
+            + " int gx = get_global_id(0);"
+            + " int gy = get_global_id(1);"
+            + " float4 fr, fi, fa;"
+            + " float2 t;"
+            + " doff += (dstride * gy + gx);"
+            + " float2 s = (float2)scale;"
+            + " t = b[doff]*s; fr.s0 = t.s0; fi.s0 = t.s1;"
+            + " t = g[doff]*s; fr.s1 = t.s0; fi.s1 = t.s1;"
+            + " t = r[doff]*s; fr.s2 = t.s0; fi.s2 = t.s1;"
+            + " t = a[doff]*s; fr.s3 = t.s0; fi.s3 = t.s1;"
+            + " fa = sqrt(fr*fr + fi*fi) * 255;"
+            + " fa = clamp(fa, 0.0f, 255.0f);"
+            + " argb[soff +sstride*gy+gx] = convert_uchar4(fa);"
+            + "}\n\n";
+    final String convolve =
+              "kernel void convolve(global const float2 *h, global const float2 *ff, global float2 *g, int stride) {"
+            + " int gx = get_global_id(0);"
+            + " int gy = get_global_id(1);"
+            + " int off = stride * gy + gx;"
+            + " float2 a = h[off];"
+            + " float2 b = ff[off];"
+            + " g[off] = (float2) { a.s0 * b.s0 - a.s1 * b.s1, a.s0 * b.s1 + a.s1 * b.s0 };"
+            + "}\n\n";
+    final String deconvolve =
+              "kernel void deconvolve(global const float2 *h, global const float2 *ff, global float2 *g, int stride, float k) {"
+            + " int gx = get_global_id(0);"
+            + " int gy = get_global_id(1);"
+            + " int off = stride * gy + gx;"
+            + " float2 a = h[off];"
+            + " float2 b = ff[off];"
+            + " float d = b.s0 * b.s0 + b.s1 * b.s1 + k;"
+            + " b.s0 /= d;"
+            + " b.s1 /= -d;"
+            + " g[off] = (float2) { a.s0 * b.s0 - a.s1 * b.s1, a.s0 * b.s1 + a.s1 * b.s0 };"
+            + "}\n\n";
+}
diff --git a/src/com/jogamp/opencl/demos/fft/CLFFTPlan.java b/src/com/jogamp/opencl/demos/fft/CLFFTPlan.java
new file mode 100644
index 0000000..f35ce14
--- /dev/null
+++ b/src/com/jogamp/opencl/demos/fft/CLFFTPlan.java
@@ -0,0 +1,1968 @@
+
+/*
+ * sample is based on Apple's FFT example.
+ * initial port to JOCL Copyright 2010 Michael Zucchi
+ *
+ * TODO: The execute functions may allocate/use temporary memory per call hence they are
+ * neither thread safe nor multiple-queue safe.  Perhaps some per-queue allocation
+ * system would suffice.
+ * TODO: The dynamic device-dependent variables should be dynamic and device-dependent and not
+ * hardcoded.  Where possible.
+ * TODO: CPU support?
+ */
+package com.jogamp.opencl.demos.fft;
+
+import com.jogamp.opencl.CLBuffer;
+import com.jogamp.opencl.CLCommandQueue;
+import com.jogamp.opencl.CLContext;
+import com.jogamp.opencl.CLDevice;
+import com.jogamp.opencl.CLEventList;
+import com.jogamp.opencl.CLKernel;
+import com.jogamp.opencl.CLMemory;
+import com.jogamp.opencl.CLMemory.Mem;
+import com.jogamp.opencl.CLProgram;
+import java.io.OutputStream;
+import java.io.PrintStream;
+import java.nio.FloatBuffer;
+import java.util.LinkedList;
+
+/**
+ *
+ * @author notzed
+ */
+public class CLFFTPlan {
+
+    private class CLFFTDim3 {
+
+        int x;
+        int y;
+        int z;
+
+        CLFFTDim3(int x, int y, int z) {
+            this.x = x;
+            this.y = y;
+            this.z = z;
+        }
+
+        CLFFTDim3(int[] size) {
+            x = size[0];
+            y = size.length > 1 ? size[1] : 1;
+            z = size.length > 2 ? size[2] : 1;
+        }
+    }
+
+    private class WorkDimensions {
+
+        int batchSize;
+        long gWorkItems;
+        long lWorkItems;
+
+        public WorkDimensions(int batchSize, long gWorkItems, long lWorkItems) {
+            this.batchSize = batchSize;
+            this.gWorkItems = gWorkItems;
+            this.lWorkItems = lWorkItems;
+        }
+    }
+
+    private class fftPadding {
+
+        int lMemSize;
+        int offset;
+        int midPad;
+
+        public fftPadding(int lMemSize, int offset, int midPad) {
+            this.lMemSize = lMemSize;
+            this.offset = offset;
+            this.midPad = midPad;
+        }
+    }
+
+    class CLFFTKernelInfo {
+
+        CLKernel kernel;
+        String kernel_name;
+        int lmem_size;
+        int num_workgroups;
+        int num_xforms_per_workgroup;
+        int num_workitems_per_workgroup;
+        CLFFTKernelDir dir;
+        boolean in_place_possible;
+    };
+
+    public enum CLFFTDirection {
+
+        Forward {
+
+            int value() {
+                return -1;
+            }
+        },
+        Inverse {
+
+            int value() {
+                return 1;
+            }
+        };
+
+        abstract int value();
+    };
+
+    enum CLFFTKernelDir {
+        X,
+        Y,
+        Z
+    };
+
+    public enum CLFFTDataFormat {
+        SplitComplexFormat,
+        InterleavedComplexFormat,
+    }
+
+    // context in which fft resources are created and kernels are executed
+    CLContext context;
+    // size of signal
+    CLFFTDim3 size;
+    // dimension of transform ... must be either 1, 2 or 3
+    int dim;
+    // data format ... must be either interleaved or plannar
+    CLFFTDataFormat format;
+    // string containing kernel source. Generated at runtime based on
+    // size, dim, format and other parameters
+    StringBuilder kernel_string;
+    // CL program containing source and kernel this particular
+    // size, dim, data format
+    CLProgram program;
+    // linked list of kernels which needs to be executed for this fft
+    LinkedList<CLFFTKernelInfo> kernel_list;
+    // twist kernel for virtualizing fft of very large sizes that do not
+    // fit in GPU global memory
+    CLKernel twist_kernel;
+    // flag indicating if temporary intermediate buffer is needed or not.
+    // this depends on fft kernels being executed and if transform is
+    // in-place or out-of-place. e.g. Local memory fft (say 1D 1024 ...
+    // one that does not require global transpose do not need temporary buffer)
+    // 2D 1024x1024 out-of-place fft however do require intermediate buffer.
+    // If temp buffer is needed, its allocation is lazy i.e. its not allocated
+    // until its needed
+    boolean temp_buffer_needed;
+    // Batch size is runtime parameter and size of temporary buffer (if needed)
+    // depends on batch size. Allocation of temporary buffer is lazy i.e. its
+    // only created when needed. Once its created at first call of clFFT_Executexxx
+    // it is not allocated next time if next time clFFT_Executexxx is called with
+    // batch size different than the first call. last_batch_size caches the last
+    // batch size with which this plan is used so that we dont keep allocating/deallocating
+    // temp buffer if same batch size is used again and again.
+    int last_batch_size;
+    // temporary buffer for interleaved plan
+    CLMemory tempmemobj;
+    // temporary buffer for planner plan. Only one of tempmemobj or
+    // (tempmemobj_real, tempmemobj_imag) pair is valid (allocated) depending
+    // data format of plan (plannar or interleaved)
+    CLMemory tempmemobj_real, tempmemobj_imag;
+    // Maximum size of signal for which local memory transposed based
+    // fft is sufficient i.e. no global mem transpose (communication)
+    // is needed
+    int max_localmem_fft_size;
+    // Maximum work items per work group allowed. This, along with max_radix below controls
+    // maximum local memory being used by fft kernels of this plan. Set to 256 by default
+    int max_work_item_per_workgroup;
+    // Maximum base radix for local memory fft ... this controls the maximum register
+    // space used by work items. Currently defaults to 16
+    int max_radix;
+    // Device depended parameter that tells how many work-items need to be read consecutive
+    // values to make sure global memory access by work-items of a work-group result in
+    // coalesced memory access to utilize full bandwidth e.g. on NVidia tesla, this is 16
+    int min_mem_coalesce_width;
+    // Number of local memory banks. This is used to geneate kernel with local memory
+    // transposes with appropriate padding to avoid bank conflicts to local memory
+    // e.g. on NVidia it is 16.
+    int num_local_mem_banks;
+
+    public class InvalidContextException extends Exception {
+    }
+
+    /**
+     * Create a new FFT plan.
+     *
+     * Use the matching executeInterleaved() or executePlanar() depending on the dataFormat specified.
+     * @param context
+     * @param sizes Array of sizes for each dimension.  The length of array defines how many dimensions there are.
+     * @param dataFormat Data format, InterleavedComplex (array of complex) or SplitComplex (separate planar arrays).
+     * @throws zephyr.cl.CLFFTPlan.InvalidContextException
+     */
+    public CLFFTPlan(CLContext context, int[] sizes, CLFFTDataFormat dataFormat) throws InvalidContextException {
+        int i;
+        int err;
+        boolean isPow2 = true;
+        String kString;
+        int num_devices;
+        boolean gpu_found = false;
+        CLDevice[] devices;
+        int ret_size;
+
+        if (sizes.length < 1 || sizes.length > 3) {
+            throw new IllegalArgumentException("Dimensions must be between 1 and 3");
+        }
+
+        this.size = new CLFFTDim3(sizes);
+
+        isPow2 |= (this.size.x != 0) && (((this.size.x - 1) & this.size.x) == 0);
+        isPow2 |= (this.size.y != 0) && (((this.size.y - 1) & this.size.y) == 0);
+        isPow2 |= (this.size.z != 0) && (((this.size.z - 1) & this.size.z) == 0);
+
+        if (!isPow2) {
+            throw new IllegalArgumentException("Sizes must be power of two");
+        }
+
+        //if( (dim == FFT_1D && (size.y != 1 || size.z != 1)) || (dim == FFT_2D && size.z != 1) )
+        //	ERR_MACRO(CL_INVALID_VALUE);
+
+        this.context = context;
+        //clRetainContext(context);
+        //this.size = size;
+        this.dim = sizes.length;
+        this.format = dataFormat;
+        //this.kernel_list = 0;
+        //this.twist_kernel = 0;
+        //this.program = 0;
+        this.temp_buffer_needed = false;
+        this.last_batch_size = 0;
+        //this.tempmemobj = 0;
+        //this.tempmemobj_real = 0;
+        //this.tempmemobj_imag = 0;
+        this.max_localmem_fft_size = 2048;
+        this.max_work_item_per_workgroup = 256;
+        this.max_radix = 16;
+        this.min_mem_coalesce_width = 16;
+        this.num_local_mem_banks = 16;
+
+        boolean done = false;
+
+        // this seems pretty shit, can't it tell this before building it?
+        while (!done) {
+            kernel_list = new LinkedList<CLFFTKernelInfo>();
+
+            this.kernel_string = new StringBuilder();
+            getBlockConfigAndKernelString();
+
+            this.program = context.createProgram(kernel_string.toString());
+
+            devices = context.getDevices();
+            for (i = 0; i < devices.length; i++) {
+                CLDevice dev = devices[i];
+
+                if (dev.getType() == CLDevice.Type.GPU) {
+                    gpu_found = true;
+                    program.build("-cl-mad-enable", dev);
+                }
+            }
+
+            if (!gpu_found) {
+                throw new InvalidContextException();
+            }
+
+            createKernelList();
+
+            // we created program and kernels based on "some max work group size (default 256)" ... this work group size
+            // may be larger than what kernel may execute with ... if thats the case we need to regenerate the kernel source
+            // setting this as limit i.e max group size and rebuild.
+            if (getPatchingRequired(devices)) {
+                release();
+                this.max_work_item_per_workgroup = (int) getMaxKernelWorkGroupSize(devices);
+            } else {
+                done = true;
+            }
+        }
+    }
+
+    /**
+     * Release system resources.
+     */
+    public void release() {
+        for (CLFFTKernelInfo kInfo : kernel_list) {
+            kInfo.kernel.release();
+        }
+        program.release();
+    }
+
+    void allocateTemporaryBufferInterleaved(int batchSize) {
+        if (temp_buffer_needed && last_batch_size != batchSize) {
+            last_batch_size = batchSize;
+            int tmpLength = size.x * size.y * size.z * batchSize * 2 * 4; // sizeof(float)
+
+            if (tempmemobj != null) {
+                tempmemobj.release();
+            }
+
+            tempmemobj = context.createFloatBuffer(tmpLength, Mem.READ_WRITE);
+        }
+    }
+
+    /**
+     * Calculate FFT on interleaved complex data.
+     * @param queue
+     * @param batchSize How many instances to calculate.  Use 1 for a single FFT.
+     * @param dir Direction of calculation, Forward or Inverse.
+     * @param data_in Input buffer.
+     * @param data_out Output buffer.  May be the same as data_in for in-place transform.
+     * @param condition Condition to wait for.  NOT YET IMPLEMENTED.
+     * @param event Event to wait for completion.  NOT YET IMPLEMENTED.
+     */
+    public void executeInterleaved(CLCommandQueue queue, int batchSize, CLFFTDirection dir,
+            CLBuffer<FloatBuffer> data_in, CLBuffer<FloatBuffer> data_out,
+            CLEventList condition, CLEventList event) {
+        int s;
+        if (format != format.InterleavedComplexFormat) {
+            throw new IllegalArgumentException();
+        }
+
+        WorkDimensions wd;
+        boolean inPlaceDone = false;
+
+        boolean isInPlace = data_in == data_out;
+
+        allocateTemporaryBufferInterleaved(batchSize);
+
+        CLMemory[] memObj = new CLMemory[3];
+        memObj[0] = data_in;
+        memObj[1] = data_out;
+        memObj[2] = tempmemobj;
+        int numKernels = kernel_list.size();
+
+        boolean numKernelsOdd = (numKernels & 1) != 0;
+        int currRead = 0;
+        int currWrite = 1;
+
+        // at least one external dram shuffle (transpose) required
+        if (temp_buffer_needed) {
+            // in-place transform
+            if (isInPlace) {
+                inPlaceDone = false;
+                currRead = 1;
+                currWrite = 2;
+            } else {
+                currWrite = (numKernels & 1) == 1 ? 1 : 2;
+            }
+
+            for (CLFFTKernelInfo kernelInfo : kernel_list) {
+                if (isInPlace && numKernelsOdd && !inPlaceDone && kernelInfo.in_place_possible) {
+                    currWrite = currRead;
+                    inPlaceDone = true;
+                }
+
+                s = batchSize;
+                wd = getKernelWorkDimensions(kernelInfo, s);
+                kernelInfo.kernel.setArg(0, memObj[currRead]);
+                kernelInfo.kernel.setArg(1, memObj[currWrite]);
+                kernelInfo.kernel.setArg(2, dir.value());
+                kernelInfo.kernel.setArg(3, wd.batchSize);
+                queue.put2DRangeKernel(kernelInfo.kernel, 0, 0, wd.gWorkItems, 1, wd.lWorkItems, 1);
+                //queue.put1DRangeKernel(kernelInfo.kernel, 0, wd.gWorkItems, wd.lWorkItems);
+
+                //System.out.printf("execute %s size %d,%d batch %d, dir %d, currread %d currwrite %d\size", kernelInfo.kernel_name, wd.gWorkItems, wd.lWorkItems, wd.batchSize, dir.value(), currRead, currWrite);
+
+                currRead = (currWrite == 1) ? 1 : 2;
+                currWrite = (currWrite == 1) ? 2 : 1;
+            }
+        } else {
+            // no dram shuffle (transpose required) transform
+            // all kernels can execute in-place.
+            for (CLFFTKernelInfo kernelInfo : kernel_list) {
+                {
+                    s = batchSize;
+                    wd = getKernelWorkDimensions(kernelInfo, s);
+
+                    kernelInfo.kernel.setArg(0, memObj[currRead]);
+                    kernelInfo.kernel.setArg(1, memObj[currWrite]);
+                    kernelInfo.kernel.setArg(2, dir.value());
+                    kernelInfo.kernel.setArg(3, wd.batchSize);
+                    queue.put2DRangeKernel(kernelInfo.kernel, 0, 0, wd.gWorkItems, 1, wd.lWorkItems, 1);
+
+                    //System.out.printf("execute %s size %d,%d batch %d, currread %d currwrite %d\size", kernelInfo.kernel_name, wd.gWorkItems, wd.lWorkItems, wd.batchSize, currRead, currWrite);
+
+                    currRead = 1;
+                    currWrite = 1;
+                }
+            }
+        }
+    }
+
+    void allocateTemporaryBufferPlanar(int batchSize) {
+        if (temp_buffer_needed && last_batch_size != batchSize) {
+            last_batch_size = batchSize;
+            int tmpLength = size.x * size.y * size.z * batchSize * 4; //sizeof(cl_float);
+
+            if (tempmemobj_real != null) {
+                tempmemobj_real.release();
+            }
+
+            if (tempmemobj_imag != null) {
+                tempmemobj_imag.release();
+            }
+
+            tempmemobj_real = context.createFloatBuffer(tmpLength, Mem.READ_WRITE);
+            tempmemobj_imag = context.createFloatBuffer(tmpLength, Mem.READ_WRITE);
+        }
+    }
+
+    /**
+     * Calculate FFT of planar data.
+     * @param queue
+     * @param batchSize
+     * @param dir
+     * @param data_in_real
+     * @param data_in_imag
+     * @param data_out_real
+     * @param data_out_imag
+     * @param contition
+     * @param event
+     */
+    public void executePlanar(CLCommandQueue queue, int batchSize, CLFFTDirection dir,
+            CLBuffer<FloatBuffer> data_in_real, CLBuffer<FloatBuffer> data_in_imag, CLBuffer<FloatBuffer> data_out_real, CLBuffer<FloatBuffer> data_out_imag,
+            CLEventList contition, CLEventList event) {
+        int s;
+
+        if (format != format.SplitComplexFormat) {
+            throw new IllegalArgumentException();
+        }
+
+        int err;
+        WorkDimensions wd;
+        boolean inPlaceDone = false;
+
+        boolean isInPlace = ((data_in_real == data_out_real) && (data_in_imag == data_out_imag));
+
+        allocateTemporaryBufferPlanar(batchSize);
+
+        CLMemory[] memObj_real = new CLMemory[3];
+        CLMemory[] memObj_imag = new CLMemory[3];
+        memObj_real[0] = data_in_real;
+        memObj_real[1] = data_out_real;
+        memObj_real[2] = tempmemobj_real;
+        memObj_imag[0] = data_in_imag;
+        memObj_imag[1] = data_out_imag;
+        memObj_imag[2] = tempmemobj_imag;
+
+        int numKernels = kernel_list.size();
+
+        boolean numKernelsOdd = (numKernels & 1) == 1;
+        int currRead = 0;
+        int currWrite = 1;
+
+        // at least one external dram shuffle (transpose) required
+        if (temp_buffer_needed) {
+            // in-place transform
+            if (isInPlace) {
+                inPlaceDone = false;
+                currRead = 1;
+                currWrite = 2;
+            } else {
+                currWrite = (numKernels & 1) == 1 ? 1 : 2;
+            }
+
+            for (CLFFTKernelInfo kernelInfo : kernel_list) {
+                if (isInPlace && numKernelsOdd && !inPlaceDone && kernelInfo.in_place_possible) {
+                    currWrite = currRead;
+                    inPlaceDone = true;
+                }
+
+                s = batchSize;
+                wd = getKernelWorkDimensions(kernelInfo, s);
+
+                kernelInfo.kernel.setArg(0, memObj_real[currRead]);
+                kernelInfo.kernel.setArg(1, memObj_imag[currRead]);
+                kernelInfo.kernel.setArg(2, memObj_real[currWrite]);
+                kernelInfo.kernel.setArg(3, memObj_imag[currWrite]);
+                kernelInfo.kernel.setArg(4, dir.value());
+                kernelInfo.kernel.setArg(5, wd.batchSize);
+
+                queue.put1DRangeKernel(kernelInfo.kernel, 0, wd.gWorkItems, wd.lWorkItems);
+
+
+                currRead = (currWrite == 1) ? 1 : 2;
+                currWrite = (currWrite == 1) ? 2 : 1;
+
+            }
+        } // no dram shuffle (transpose required) transform
+        else {
+
+            for (CLFFTKernelInfo kernelInfo : kernel_list) {
+                s = batchSize;
+                wd = getKernelWorkDimensions(kernelInfo, s);
+
+                kernelInfo.kernel.setArg(0, memObj_real[currRead]);
+                kernelInfo.kernel.setArg(1, memObj_imag[currRead]);
+                kernelInfo.kernel.setArg(2, memObj_real[currWrite]);
+                kernelInfo.kernel.setArg(3, memObj_imag[currWrite]);
+                kernelInfo.kernel.setArg(4, dir.value());
+                kernelInfo.kernel.setArg(5, wd.batchSize);
+
+                queue.put1DRangeKernel(kernelInfo.kernel, 0, wd.gWorkItems, wd.lWorkItems);
+                currRead = 1;
+                currWrite = 1;
+            }
+        }
+    }
+
+    /**
+     * Dump the planner result to the output stream.
+     * @param os if null, System.out is used.
+     */
+    public void dumpPlan(OutputStream os) {
+        PrintStream out = os == null ? System.out : new PrintStream(os);
+
+        for (CLFFTKernelInfo kInfo : kernel_list) {
+            int s = 1;
+            WorkDimensions wd = getKernelWorkDimensions(kInfo, s);
+            out.printf("Run kernel %s with global dim = {%d*BatchSize}, local dim={%d}\n", kInfo.kernel_name, wd.gWorkItems, wd.lWorkItems);
+        }
+        out.printf("%s\n", kernel_string.toString());
+    }
+
+    WorkDimensions getKernelWorkDimensions(CLFFTKernelInfo kernelInfo, int batchSize) {
+        int lWorkItems = kernelInfo.num_workitems_per_workgroup;
+        int numWorkGroups = kernelInfo.num_workgroups;
+        int numXFormsPerWG = kernelInfo.num_xforms_per_workgroup;
+
+        switch (kernelInfo.dir) {
+            case X:
+                batchSize *= (size.y * size.z);
+                numWorkGroups = ((batchSize % numXFormsPerWG) != 0) ? (batchSize / numXFormsPerWG + 1) : (batchSize / numXFormsPerWG);
+                numWorkGroups *= kernelInfo.num_workgroups;
+                break;
+            case Y:
+                batchSize *= size.z;
+                numWorkGroups *= batchSize;
+                break;
+            case Z:
+                numWorkGroups *= batchSize;
+                break;
+        }
+
+        return new WorkDimensions(batchSize, numWorkGroups * lWorkItems, lWorkItems);
+    }
+
+    /*
+     *
+     * Kernel building/customisation code follows
+     *
+     */
+    private void getBlockConfigAndKernelString() {
+        this.temp_buffer_needed = false;
+        this.kernel_string.append(baseKernels);
+
+        if (this.format == CLFFTDataFormat.SplitComplexFormat) {
+            this.kernel_string.append(twistKernelPlannar);
+        } else {
+            this.kernel_string.append(twistKernelInterleaved);
+        }
+
+        switch (this.dim) {
+            case 1:
+                FFT1D(CLFFTKernelDir.X);
+                break;
+
+            case 2:
+                FFT1D(CLFFTKernelDir.X);
+                FFT1D(CLFFTKernelDir.Y);
+                break;
+
+            case 3:
+                FFT1D(CLFFTKernelDir.X);
+                FFT1D(CLFFTKernelDir.Y);
+                FFT1D(CLFFTKernelDir.Z);
+                break;
+
+            default:
+                return;
+        }
+
+        this.temp_buffer_needed = false;
+        for (CLFFTKernelInfo kInfo : this.kernel_list) {
+            this.temp_buffer_needed |= !kInfo.in_place_possible;
+        }
+    }
+
+    private void createKernelList() {
+        CLFFTKernelInfo kern;
+        for (CLFFTKernelInfo kinfo : this.kernel_list) {
+            kinfo.kernel = program.createCLKernel(kinfo.kernel_name);
+        }
+
+        if (format == format.SplitComplexFormat) {
+            twist_kernel = program.createCLKernel("clFFT_1DTwistSplit");
+        } else {
+            twist_kernel = program.createCLKernel("clFFT_1DTwistInterleaved");
+        }
+    }
+
+    private boolean getPatchingRequired(CLDevice[] devices) {
+        int i;
+        for (i = 0; i < devices.length; i++) {
+            for (CLFFTKernelInfo kInfo : kernel_list) {
+                if (kInfo.kernel.getWorkGroupSize(devices[i]) < kInfo.num_workitems_per_workgroup) {
+                    return true;
+                }
+            }
+        }
+        return false;
+    }
+
+    long getMaxKernelWorkGroupSize(CLDevice[] devices) {
+        long max_wg_size = Integer.MAX_VALUE;
+        int i;
+
+        for (i = 0; i < devices.length; i++) {
+            for (CLFFTKernelInfo kInfo : kernel_list) {
+                long wg_size = kInfo.kernel.getWorkGroupSize(devices[i]);
+
+                if (max_wg_size > wg_size) {
+                    max_wg_size = wg_size;
+                }
+            }
+        }
+
+        return max_wg_size;
+    }
+
+    int log2(int x) {
+        return 32 - Integer.numberOfLeadingZeros(x - 1);
+    }
+
+// For any size, this function decomposes size into factors for loacal memory tranpose
+// based fft. Factors (radices) are sorted such that the first one (radixArray[0])
+// is the largest. This base radix determines the number of registers used by each
+// work item and product of remaining radices determine the size of work group needed.
+// To make things concrete with and example, suppose size = 1024. It is decomposed into
+// 1024 = 16 x 16 x 4. Hence kernel uses float2 a[16], for local in-register fft and
+// needs 16 x 4 = 64 work items per work group. So kernel first performance 64 length
+// 16 ffts (64 work items working in parallel) following by transpose using local
+// memory followed by again 64 length 16 ffts followed by transpose using local memory
+// followed by 256 length 4 ffts. For the last step since with size of work group is
+// 64 and each work item can array for 16 values, 64 work items can compute 256 length
+// 4 ffts by each work item computing 4 length 4 ffts.
+// Similarly for size = 2048 = 8 x 8 x 8 x 4, each work group has 8 x 8 x 4 = 256 work
+// iterms which each computes 256 (in-parallel) length 8 ffts in-register, followed
+// by transpose using local memory, followed by 256 length 8 in-register ffts, followed
+// by transpose using local memory, followed by 256 length 8 in-register ffts, followed
+// by transpose using local memory, followed by 512 length 4 in-register ffts. Again,
+// for the last step, each work item computes two length 4 in-register ffts and thus
+// 256 work items are needed to compute all 512 ffts.
+// For size = 32 = 8 x 4, 4 work items first compute 4 in-register
+// lenth 8 ffts, followed by transpose using local memory followed by 8 in-register
+// length 4 ffts, where each work item computes two length 4 ffts thus 4 work items
+// can compute 8 length 4 ffts. However if work group size of say 64 is choosen,
+// each work group can compute 64/ 4 = 16 size 32 ffts (batched transform).
+// Users can play with these parameters to figure what gives best performance on
+// their particular device i.e. some device have less register space thus using
+// smaller base radix can avoid spilling ... some has small local memory thus
+// using smaller work group size may be required etc
+    int getRadixArray(int n, int[] radixArray, int maxRadix) {
+        if (maxRadix > 1) {
+            maxRadix = Math.min(n, maxRadix);
+            int cnt = 0;
+            while (n > maxRadix) {
+                radixArray[cnt++] = maxRadix;
+                n /= maxRadix;
+            }
+            radixArray[cnt++] = n;
+            return cnt;
+        }
+
+        switch (n) {
+            case 2:
+                radixArray[0] = 2;
+                return 1;
+
+            case 4:
+                radixArray[0] = 4;
+                return 1;
+
+            case 8:
+                radixArray[0] = 8;
+                return 1;
+
+            case 16:
+                radixArray[0] = 8;
+                radixArray[1] = 2;
+                return 2;
+
+            case 32:
+                radixArray[0] = 8;
+                radixArray[1] = 4;
+                return 2;
+
+            case 64:
+                radixArray[0] = 8;
+                radixArray[1] = 8;
+                return 2;
+
+            case 128:
+                radixArray[0] = 8;
+                radixArray[1] = 4;
+                radixArray[2] = 4;
+                return 3;
+
+            case 256:
+                radixArray[0] = 4;
+                radixArray[1] = 4;
+                radixArray[2] = 4;
+                radixArray[3] = 4;
+                return 4;
+
+            case 512:
+                radixArray[0] = 8;
+                radixArray[1] = 8;
+                radixArray[2] = 8;
+                return 3;
+
+            case 1024:
+                radixArray[0] = 16;
+                radixArray[1] = 16;
+                radixArray[2] = 4;
+                return 3;
+            case 2048:
+                radixArray[0] = 8;
+                radixArray[1] = 8;
+                radixArray[2] = 8;
+                radixArray[3] = 4;
+                return 4;
+            default:
+                return 0;
+        }
+    }
+
+    void insertHeader(StringBuilder kernelString, String kernelName, CLFFTDataFormat dataFormat) {
+        if (dataFormat == CLFFTPlan.CLFFTDataFormat.SplitComplexFormat) {
+            kernelString.append("__kernel void ").append(kernelName).append("(__global float *in_real, __global float *in_imag, __global float *out_real, __global float *out_imag, int dir, int S)\n");
+        } else {
+            kernelString.append("__kernel void ").append(kernelName).append("(__global float2 *in, __global float2 *out, int dir, int S)\n");
+        }
+    }
+
+    void insertVariables(StringBuilder kStream, int maxRadix) {
+        kStream.append("    int i, j, r, indexIn, indexOut, index, tid, bNum, xNum, k, l;\n");
+        kStream.append("    int s, ii, jj, offset;\n");
+        kStream.append("    float2 w;\n");
+        kStream.append("    float ang, angf, ang1;\n");
+        kStream.append("    __local float *lMemStore, *lMemLoad;\n");
+        kStream.append("    float2 a[").append(maxRadix).append("];\n");
+        kStream.append("    int lId = get_local_id( 0 );\n");
+        kStream.append("    int groupId = get_group_id( 0 );\n");
+    }
+
+    void formattedLoad(StringBuilder kernelString, int aIndex, int gIndex, CLFFTDataFormat dataFormat) {
+        if (dataFormat == dataFormat.InterleavedComplexFormat) {
+            kernelString.append("        a[").append(aIndex).append("] = in[").append(gIndex).append("];\n");
+        } else {
+            kernelString.append("        a[").append(aIndex).append("].x = in_real[").append(gIndex).append("];\n");
+            kernelString.append("        a[").append(aIndex).append("].y = in_imag[").append(gIndex).append("];\n");
+        }
+    }
+
+    void formattedStore(StringBuilder kernelString, int aIndex, int gIndex, CLFFTDataFormat dataFormat) {
+        if (dataFormat == dataFormat.InterleavedComplexFormat) {
+            kernelString.append("        out[").append(gIndex).append("] = a[").append(aIndex).append("];\n");
+        } else {
+            kernelString.append("        out_real[").append(gIndex).append("] = a[").append(aIndex).append("].x;\n");
+            kernelString.append("        out_imag[").append(gIndex).append("] = a[").append(aIndex).append("].y;\n");
+        }
+    }
+
+    int insertGlobalLoadsAndTranspose(StringBuilder kernelString, int N, int numWorkItemsPerXForm, int numXFormsPerWG, int R0, int mem_coalesce_width, CLFFTDataFormat dataFormat) {
+        int log2NumWorkItemsPerXForm = (int) log2(numWorkItemsPerXForm);
+        int groupSize = numWorkItemsPerXForm * numXFormsPerWG;
+        int i, j;
+        int lMemSize = 0;
+
+        if (numXFormsPerWG > 1) {
+            kernelString.append("        s = S & ").append(numXFormsPerWG - 1).append(";\n");
+        }
+
+        if (numWorkItemsPerXForm >= mem_coalesce_width) {
+            if (numXFormsPerWG > 1) {
+                kernelString.append("    ii = lId & ").append(numWorkItemsPerXForm - 1).append(";\n");
+                kernelString.append("    jj = lId >> ").append(log2NumWorkItemsPerXForm).append(";\n");
+                kernelString.append("    if( !s || (groupId < get_num_groups(0)-1) || (jj < s) ) {\n");
+                kernelString.append("        offset = mad24( mad24(groupId, ").append(numXFormsPerWG).append(", jj), ").append(N).append(", ii );\n");
+                if (dataFormat == dataFormat.InterleavedComplexFormat) {
+                    kernelString.append("        in += offset;\n");
+                    kernelString.append("        out += offset;\n");
+                } else {
+                    kernelString.append("        in_real += offset;\n");
+                    kernelString.append("        in_imag += offset;\n");
+                    kernelString.append("        out_real += offset;\n");
+                    kernelString.append("        out_imag += offset;\n");
+                }
+                for (i = 0; i < R0; i++) {
+                    formattedLoad(kernelString, i, i * numWorkItemsPerXForm, dataFormat);
+                }
+                kernelString.append("    }\n");
+            } else {
+                kernelString.append("    ii = lId;\n");
+                kernelString.append("    jj = 0;\n");
+                kernelString.append("    offset =  mad24(groupId, ").append(N).append(", ii);\n");
+                if (dataFormat == dataFormat.InterleavedComplexFormat) {
+                    kernelString.append("        in += offset;\n");
+                    kernelString.append("        out += offset;\n");
+                } else {
+                    kernelString.append("        in_real += offset;\n");
+                    kernelString.append("        in_imag += offset;\n");
+                    kernelString.append("        out_real += offset;\n");
+                    kernelString.append("        out_imag += offset;\n");
+                }
+                for (i = 0; i < R0; i++) {
+                    formattedLoad(kernelString, i, i * numWorkItemsPerXForm, dataFormat);
+                }
+            }
+        } else if (N >= mem_coalesce_width) {
+            int numInnerIter = N / mem_coalesce_width;
+            int numOuterIter = numXFormsPerWG / (groupSize / mem_coalesce_width);
+
+            kernelString.append("    ii = lId & ").append(mem_coalesce_width - 1).append(";\n");
+            kernelString.append("    jj = lId >> ").append((int) log2(mem_coalesce_width)).append(";\n");
+            kernelString.append("    lMemStore = sMem + mad24( jj, ").append(N + numWorkItemsPerXForm).append(", ii );\n");
+            kernelString.append("    offset = mad24( groupId, ").append(numXFormsPerWG).append(", jj);\n");
+            kernelString.append("    offset = mad24( offset, ").append(N).append(", ii );\n");
+            if (dataFormat == dataFormat.InterleavedComplexFormat) {
+                kernelString.append("        in += offset;\n");
+                kernelString.append("        out += offset;\n");
+            } else {
+                kernelString.append("        in_real += offset;\n");
+                kernelString.append("        in_imag += offset;\n");
+                kernelString.append("        out_real += offset;\n");
+                kernelString.append("        out_imag += offset;\n");
+            }
+
+            kernelString.append("if((groupId == get_num_groups(0)-1) && s) {\n");
+            for (i = 0; i < numOuterIter; i++) {
+                kernelString.append("    if( jj < s ) {\n");
+                for (j = 0; j < numInnerIter; j++) {
+                    formattedLoad(kernelString, i * numInnerIter + j, j * mem_coalesce_width + i * (groupSize / mem_coalesce_width) * N, dataFormat);
+                }
+                kernelString.append("    }\n");
+                if (i != numOuterIter - 1) {
+                    kernelString.append("    jj += ").append(groupSize / mem_coalesce_width).append(";\n");
+                }
+            }
+            kernelString.append("}\n ");
+            kernelString.append("else {\n");
+            for (i = 0; i < numOuterIter; i++) {
+                for (j = 0; j < numInnerIter; j++) {
+                    formattedLoad(kernelString, i * numInnerIter + j, j * mem_coalesce_width + i * (groupSize / mem_coalesce_width) * N, dataFormat);
+                }
+            }
+            kernelString.append("}\n");
+
+            kernelString.append("    ii = lId & ").append(numWorkItemsPerXForm - 1).append(";\n");
+            kernelString.append("    jj = lId >> ").append(log2NumWorkItemsPerXForm).append(";\n");
+            kernelString.append("    lMemLoad  = sMem + mad24( jj, ").append(N + numWorkItemsPerXForm).append(", ii);\n");
+
+            for (i = 0; i < numOuterIter; i++) {
+                for (j = 0; j < numInnerIter; j++) {
+                    kernelString.append("    lMemStore[").append(j * mem_coalesce_width + i * (groupSize / mem_coalesce_width) * (N + numWorkItemsPerXForm)).append("] = a[").append(i * numInnerIter + j).append("].x;\n");
+                }
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < R0; i++) {
+                kernelString.append("    a[").append(i).append("].x = lMemLoad[").append(i * numWorkItemsPerXForm).append("];\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < numOuterIter; i++) {
+                for (j = 0; j < numInnerIter; j++) {
+                    kernelString.append("    lMemStore[").append(j * mem_coalesce_width + i * (groupSize / mem_coalesce_width) * (N + numWorkItemsPerXForm)).append("] = a[").append(i * numInnerIter + j).append("].y;\n");
+                }
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < R0; i++) {
+                kernelString.append("    a[").append(i).append("].y = lMemLoad[").append(i * numWorkItemsPerXForm).append("];\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            lMemSize = (N + numWorkItemsPerXForm) * numXFormsPerWG;
+        } else {
+            kernelString.append("    offset = mad24( groupId,  ").append(N * numXFormsPerWG).append(", lId );\n");
+            if (dataFormat == dataFormat.InterleavedComplexFormat) {
+                kernelString.append("        in += offset;\n");
+                kernelString.append("        out += offset;\n");
+            } else {
+                kernelString.append("        in_real += offset;\n");
+                kernelString.append("        in_imag += offset;\n");
+                kernelString.append("        out_real += offset;\n");
+                kernelString.append("        out_imag += offset;\n");
+            }
+
+            kernelString.append("    ii = lId & ").append(N - 1).append(";\n");
+            kernelString.append("    jj = lId >> ").append((int) log2(N)).append(";\n");
+            kernelString.append("    lMemStore = sMem + mad24( jj, ").append(N + numWorkItemsPerXForm).append(", ii );\n");
+
+            kernelString.append("if((groupId == get_num_groups(0)-1) && s) {\n");
+            for (i = 0; i < R0; i++) {
+                kernelString.append("    if(jj < s )\n");
+                formattedLoad(kernelString, i, i * groupSize, dataFormat);
+                if (i != R0 - 1) {
+                    kernelString.append("    jj += ").append(groupSize / N).append(";\n");
+                }
+            }
+            kernelString.append("}\n");
+            kernelString.append("else {\n");
+            for (i = 0; i < R0; i++) {
+                formattedLoad(kernelString, i, i * groupSize, dataFormat);
+            }
+            kernelString.append("}\n");
+
+            if (numWorkItemsPerXForm > 1) {
+                kernelString.append("    ii = lId & ").append(numWorkItemsPerXForm - 1).append(";\n");
+                kernelString.append("    jj = lId >> ").append(log2NumWorkItemsPerXForm).append(";\n");
+                kernelString.append("    lMemLoad = sMem + mad24( jj, ").append(N + numWorkItemsPerXForm).append(", ii );\n");
+            } else {
+                kernelString.append("    ii = 0;\n");
+                kernelString.append("    jj = lId;\n");
+                kernelString.append("    lMemLoad = sMem + mul24( jj, ").append(N + numWorkItemsPerXForm).append(");\n");
+            }
+
+
+            for (i = 0; i < R0; i++) {
+                kernelString.append("    lMemStore[").append(i * (groupSize / N) * (N + numWorkItemsPerXForm)).append("] = a[").append(i).append("].x;\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < R0; i++) {
+                kernelString.append("    a[").append(i).append("].x = lMemLoad[").append(i * numWorkItemsPerXForm).append("];\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < R0; i++) {
+                kernelString.append("    lMemStore[").append(i * (groupSize / N) * (N + numWorkItemsPerXForm)).append("] = a[").append(i).append("].y;\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < R0; i++) {
+                kernelString.append("    a[").append(i).append("].y = lMemLoad[").append(i * numWorkItemsPerXForm).append("];\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            lMemSize = (N + numWorkItemsPerXForm) * numXFormsPerWG;
+        }
+
+        return lMemSize;
+    }
+
+    int insertGlobalStoresAndTranspose(StringBuilder kernelString, int N, int maxRadix, int Nr, int numWorkItemsPerXForm, int numXFormsPerWG, int mem_coalesce_width, CLFFTDataFormat dataFormat) {
+        int groupSize = numWorkItemsPerXForm * numXFormsPerWG;
+        int i, j, k, ind;
+        int lMemSize = 0;
+        int numIter = maxRadix / Nr;
+        String indent = "";
+
+        if (numWorkItemsPerXForm >= mem_coalesce_width) {
+            if (numXFormsPerWG > 1) {
+                kernelString.append("    if( !s || (groupId < get_num_groups(0)-1) || (jj < s) ) {\n");
+                indent = ("    ");
+            }
+            for (i = 0; i < maxRadix; i++) {
+                j = i % numIter;
+                k = i / numIter;
+                ind = j * Nr + k;
+                formattedStore(kernelString, ind, i * numWorkItemsPerXForm, dataFormat);
+            }
+            if (numXFormsPerWG > 1) {
+                kernelString.append("    }\n");
+            }
+        } else if (N >= mem_coalesce_width) {
+            int numInnerIter = N / mem_coalesce_width;
+            int numOuterIter = numXFormsPerWG / (groupSize / mem_coalesce_width);
+
+            kernelString.append("    lMemLoad  = sMem + mad24( jj, ").append(N + numWorkItemsPerXForm).append(", ii );\n");
+            kernelString.append("    ii = lId & ").append(mem_coalesce_width - 1).append(";\n");
+            kernelString.append("    jj = lId >> ").append((int) log2(mem_coalesce_width)).append(";\n");
+            kernelString.append("    lMemStore = sMem + mad24( jj,").append(N + numWorkItemsPerXForm).append(", ii );\n");
+
+            for (i = 0; i < maxRadix; i++) {
+                j = i % numIter;
+                k = i / numIter;
+                ind = j * Nr + k;
+                kernelString.append("    lMemLoad[").append(i * numWorkItemsPerXForm).append("] = a[").append(ind).append("].x;\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < numOuterIter; i++) {
+                for (j = 0; j < numInnerIter; j++) {
+                    kernelString.append("    a[").append(i * numInnerIter + j).append("].x = lMemStore[").append(j * mem_coalesce_width + i * (groupSize / mem_coalesce_width) * (N + numWorkItemsPerXForm)).append("];\n");
+                }
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < maxRadix; i++) {
+                j = i % numIter;
+                k = i / numIter;
+                ind = j * Nr + k;
+                kernelString.append("    lMemLoad[").append(i * numWorkItemsPerXForm).append("] = a[").append(ind).append("].y;\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < numOuterIter; i++) {
+                for (j = 0; j < numInnerIter; j++) {
+                    kernelString.append("    a[").append(i * numInnerIter + j).append("].y = lMemStore[").append(j * mem_coalesce_width + i * (groupSize / mem_coalesce_width) * (N + numWorkItemsPerXForm)).append("];\n");
+                }
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            kernelString.append("if((groupId == get_num_groups(0)-1) && s) {\n");
+            for (i = 0; i < numOuterIter; i++) {
+                kernelString.append("    if( jj < s ) {\n");
+                for (j = 0; j < numInnerIter; j++) {
+                    formattedStore(kernelString, i * numInnerIter + j, j * mem_coalesce_width + i * (groupSize / mem_coalesce_width) * N, dataFormat);
+                }
+                kernelString.append("    }\n");
+                if (i != numOuterIter - 1) {
+                    kernelString.append("    jj += ").append(groupSize / mem_coalesce_width).append(";\n");
+                }
+            }
+            kernelString.append("}\n");
+            kernelString.append("else {\n");
+            for (i = 0; i < numOuterIter; i++) {
+                for (j = 0; j < numInnerIter; j++) {
+                    formattedStore(kernelString, i * numInnerIter + j, j * mem_coalesce_width + i * (groupSize / mem_coalesce_width) * N, dataFormat);
+                }
+            }
+            kernelString.append("}\n");
+
+            lMemSize = (N + numWorkItemsPerXForm) * numXFormsPerWG;
+        } else {
+            kernelString.append("    lMemLoad  = sMem + mad24( jj,").append(N + numWorkItemsPerXForm).append(", ii );\n");
+
+            kernelString.append("    ii = lId & ").append(N - 1).append(";\n");
+            kernelString.append("    jj = lId >> ").append((int) log2(N)).append(";\n");
+            kernelString.append("    lMemStore = sMem + mad24( jj,").append(N + numWorkItemsPerXForm).append(", ii );\n");
+
+            for (i = 0; i < maxRadix; i++) {
+                j = i % numIter;
+                k = i / numIter;
+                ind = j * Nr + k;
+                kernelString.append("    lMemLoad[").append(i * numWorkItemsPerXForm).append("] = a[").append(ind).append("].x;\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < maxRadix; i++) {
+                kernelString.append("    a[").append(i).append("].x = lMemStore[").append(i * (groupSize / N) * (N + numWorkItemsPerXForm)).append("];\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < maxRadix; i++) {
+                j = i % numIter;
+                k = i / numIter;
+                ind = j * Nr + k;
+                kernelString.append("    lMemLoad[").append(i * numWorkItemsPerXForm).append("] = a[").append(ind).append("].y;\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            for (i = 0; i < maxRadix; i++) {
+                kernelString.append("    a[").append(i).append("].y = lMemStore[").append(i * (groupSize / N) * (N + numWorkItemsPerXForm)).append("];\n");
+            }
+            kernelString.append("    barrier( CLK_LOCAL_MEM_FENCE );\n");
+
+            kernelString.append("if((groupId == get_num_groups(0)-1) && s) {\n");
+            for (i = 0; i < maxRadix; i++) {
+                kernelString.append("    if(jj < s ) {\n");
+                formattedStore(kernelString, i, i * groupSize, dataFormat);
+                kernelString.append("    }\n");
+                if (i != maxRadix - 1) {
+                    kernelString.append("    jj +=").append(groupSize / N).append(";\n");
+                }
+            }
+            kernelString.append("}\n");
+            kernelString.append("else {\n");
+            for (i = 0; i < maxRadix; i++) {
+                formattedStore(kernelString, i, i * groupSize, dataFormat);
+            }
+            kernelString.append("}\n");
+
+            lMemSize = (N + numWorkItemsPerXForm) * numXFormsPerWG;
+        }
+
+        return lMemSize;
+    }
+
+    void insertfftKernel(StringBuilder kernelString, int Nr, int numIter) {
+        int i;
+        for (i = 0; i < numIter; i++) {
+            kernelString.append("    fftKernel").append(Nr).append("(a+").append(i * Nr).append(", dir);\n");
+        }
+    }
+
+    void insertTwiddleKernel(StringBuilder kernelString, int Nr, int numIter, int Nprev, int len, int numWorkItemsPerXForm) {
+        int z, k;
+        int logNPrev = log2(Nprev);
+
+        for (z = 0; z < numIter; z++) {
+            if (z == 0) {
+                if (Nprev > 1) {
+                    kernelString.append("    angf = (float) (ii >> ").append(logNPrev).append(");\n");
+                } else {
+                    kernelString.append("    angf = (float) ii;\n");
+                }
+            } else {
+                if (Nprev > 1) {
+                    kernelString.append("    angf = (float) ((").append(z * numWorkItemsPerXForm).append(" + ii) >>").append(logNPrev).append(");\n");
+                } else {
+                    kernelString.append("    angf = (float) (").append(z * numWorkItemsPerXForm).append(" + ii);\n");
+                }
+            }
+
+            for (k = 1; k < Nr; k++) {
+                int ind = z * Nr + k;
+                //float fac =  (float) (2.0 * M_PI * (double) k / (double) len);
+                kernelString.append("    ang = dir * ( 2.0f * M_PI * ").append(k).append(".0f / ").append(len).append(".0f )").append(" * angf;\n");
+                kernelString.append("    w = (float2)(native_cos(ang), native_sin(ang));\n");
+                kernelString.append("    a[").append(ind).append("] = complexMul(a[").append(ind).append("], w);\n");
+            }
+        }
+    }
+
+    fftPadding getPadding(int numWorkItemsPerXForm, int Nprev, int numWorkItemsReq, int numXFormsPerWG, int Nr, int numBanks) {
+        int offset, midPad;
+
+        if ((numWorkItemsPerXForm <= Nprev) || (Nprev >= numBanks)) {
+            offset = 0;
+        } else {
+            int numRowsReq = ((numWorkItemsPerXForm < numBanks) ? numWorkItemsPerXForm : numBanks) / Nprev;
+            int numColsReq = 1;
+            if (numRowsReq > Nr) {
+                numColsReq = numRowsReq / Nr;
+            }
+            numColsReq = Nprev * numColsReq;
+            offset = numColsReq;
+        }
+
+        if (numWorkItemsPerXForm >= numBanks || numXFormsPerWG == 1) {
+            midPad = 0;
+        } else {
+            int bankNum = ((numWorkItemsReq + offset) * Nr) & (numBanks - 1);
+            if (bankNum >= numWorkItemsPerXForm) {
+                midPad = 0;
+            } else {
+                midPad = numWorkItemsPerXForm - bankNum;
+            }
+        }
+
+        int lMemSize = (numWorkItemsReq + offset) * Nr * numXFormsPerWG + midPad * (numXFormsPerWG - 1);
+        return new fftPadding(lMemSize, offset, midPad);
+    }
+
+    void insertLocalStores(StringBuilder kernelString, int numIter, int Nr, int numWorkItemsPerXForm, int numWorkItemsReq, int offset, String comp) {
+        int z, k;
+
+        for (z = 0; z < numIter; z++) {
+            for (k = 0; k < Nr; k++) {
+                int index = k * (numWorkItemsReq + offset) + z * numWorkItemsPerXForm;
+                kernelString.append("    lMemStore[").append(index).append("] = a[").append(z * Nr + k).append("].").append(comp).append(";\n");
+            }
+        }
+        kernelString.append("    barrier(CLK_LOCAL_MEM_FENCE);\n");
+    }
+
+    void insertLocalLoads(StringBuilder kernelString, int n, int Nr, int Nrn, int Nprev, int Ncurr, int numWorkItemsPerXForm, int numWorkItemsReq, int offset, String comp) {
+        int numWorkItemsReqN = n / Nrn;
+        int interBlockHNum = Math.max(Nprev / numWorkItemsPerXForm, 1);
+        int interBlockHStride = numWorkItemsPerXForm;
+        int vertWidth = Math.max(numWorkItemsPerXForm / Nprev, 1);
+        vertWidth = Math.min(vertWidth, Nr);
+        int vertNum = Nr / vertWidth;
+        int vertStride = (n / Nr + offset) * vertWidth;
+        int iter = Math.max(numWorkItemsReqN / numWorkItemsPerXForm, 1);
+        int intraBlockHStride = (numWorkItemsPerXForm / (Nprev * Nr)) > 1 ? (numWorkItemsPerXForm / (Nprev * Nr)) : 1;
+        intraBlockHStride *= Nprev;
+
+        int stride = numWorkItemsReq / Nrn;
+        int i;
+        for (i = 0; i < iter; i++) {
+            int ii = i / (interBlockHNum * vertNum);
+            int zz = i % (interBlockHNum * vertNum);
+            int jj = zz % interBlockHNum;
+            int kk = zz / interBlockHNum;
+            int z;
+            for (z = 0; z < Nrn; z++) {
+                int st = kk * vertStride + jj * interBlockHStride + ii * intraBlockHStride + z * stride;
+                kernelString.append("    a[").append(i * Nrn + z).append("].").append(comp).append(" = lMemLoad[").append(st).append("];\n");
+            }
+        }
+        kernelString.append("    barrier(CLK_LOCAL_MEM_FENCE);\n");
+    }
+
+    void insertLocalLoadIndexArithmatic(StringBuilder kernelString, int Nprev, int Nr, int numWorkItemsReq, int numWorkItemsPerXForm, int numXFormsPerWG, int offset, int midPad) {
+        int Ncurr = Nprev * Nr;
+        int logNcurr = log2(Ncurr);
+        int logNprev = log2(Nprev);
+        int incr = (numWorkItemsReq + offset) * Nr + midPad;
+
+        if (Ncurr < numWorkItemsPerXForm) {
+            if (Nprev == 1) {
+                kernelString.append("    j = ii & ").append(Ncurr - 1).append(";\n");
+            } else {
+                kernelString.append("    j = (ii & ").append(Ncurr - 1).append(") >> ").append(logNprev).append(";\n");
+            }
+
+            if (Nprev == 1) {
+                kernelString.append("    i = ii >> ").append(logNcurr).append(";\n");
+            } else {
+                kernelString.append("    i = mad24(ii >> ").append(logNcurr).append(", ").append(Nprev).append(", ii & ").append(Nprev - 1).append(");\n");
+            }
+        } else {
+            if (Nprev == 1) {
+                kernelString.append("    j = ii;\n");
+            } else {
+                kernelString.append("    j = ii >> ").append(logNprev).append(";\n");
+            }
+            if (Nprev == 1) {
+                kernelString.append("    i = 0;\n");
+            } else {
+                kernelString.append("    i = ii & ").append(Nprev - 1).append(";\n");
+            }
+        }
+
+        if (numXFormsPerWG > 1) {
+            kernelString.append("    i = mad24(jj, ").append(incr).append(", i);\n");
+        }
+
+        kernelString.append("    lMemLoad = sMem + mad24(j, ").append(numWorkItemsReq + offset).append(", i);\n");
+    }
+
+    void insertLocalStoreIndexArithmatic(StringBuilder kernelString, int numWorkItemsReq, int numXFormsPerWG, int Nr, int offset, int midPad) {
+        if (numXFormsPerWG == 1) {
+            kernelString.append("    lMemStore = sMem + ii;\n");
+        } else {
+            kernelString.append("    lMemStore = sMem + mad24(jj, ").append((numWorkItemsReq + offset) * Nr + midPad).append(", ii);\n");
+        }
+    }
+
+    void createLocalMemfftKernelString() {
+        int[] radixArray = new int[10];
+        int numRadix;
+
+        int n = this.size.x;
+
+        assert (n <= this.max_work_item_per_workgroup * this.max_radix);
+
+        numRadix = getRadixArray(n, radixArray, 0);
+        assert (numRadix > 0);
+
+        if (n / radixArray[0] > this.max_work_item_per_workgroup) {
+            numRadix = getRadixArray(n, radixArray, this.max_radix);
+        }
+
+        assert (radixArray[0] <= this.max_radix);
+        assert (n / radixArray[0] <= this.max_work_item_per_workgroup);
+
+        int tmpLen = 1;
+        int i;
+        for (i = 0; i < numRadix; i++) {
+            assert ((radixArray[i] != 0) && !(((radixArray[i] - 1) != 0) & (radixArray[i] != 0)));
+            tmpLen *= radixArray[i];
+        }
+        assert (tmpLen == n);
+
+        //int offset, midPad;
+        StringBuilder localString = new StringBuilder();
+        String kernelName;
+
+        CLFFTDataFormat dataFormat = this.format;
+        StringBuilder kernelString = this.kernel_string;
+
+        int kCount = kernel_list.size();
+
+        kernelName = "fft" + (kCount);
+
+        CLFFTKernelInfo kInfo = new CLFFTKernelInfo();
+        kernel_list.add(kInfo);
+        //kInfo.kernel = null;
+        //kInfo.lmem_size = 0;
+        //kInfo.num_workgroups = 0;
+        //kInfo.num_workitems_per_workgroup = 0;
+        kInfo.dir = CLFFTKernelDir.X;
+        kInfo.in_place_possible = true;
+        //kInfo.next = null;
+        kInfo.kernel_name = kernelName;
+
+        int numWorkItemsPerXForm = n / radixArray[0];
+        int numWorkItemsPerWG = numWorkItemsPerXForm <= 64 ? 64 : numWorkItemsPerXForm;
+        assert (numWorkItemsPerWG <= this.max_work_item_per_workgroup);
+        int numXFormsPerWG = numWorkItemsPerWG / numWorkItemsPerXForm;
+        kInfo.num_workgroups = 1;
+        kInfo.num_xforms_per_workgroup = numXFormsPerWG;
+        kInfo.num_workitems_per_workgroup = numWorkItemsPerWG;
+
+        int[] N = radixArray;
+        int maxRadix = N[0];
+        int lMemSize = 0;
+
+        insertVariables(localString, maxRadix);
+
+        lMemSize = insertGlobalLoadsAndTranspose(localString, n, numWorkItemsPerXForm, numXFormsPerWG, maxRadix, this.min_mem_coalesce_width, dataFormat);
+        kInfo.lmem_size = (lMemSize > kInfo.lmem_size) ? lMemSize : kInfo.lmem_size;
+
+        String xcomp = "x";
+        String ycomp = "y";
+
+        int Nprev = 1;
+        int len = n;
+        int r;
+        for (r = 0; r < numRadix; r++) {
+            int numIter = N[0] / N[r];
+            int numWorkItemsReq = n / N[r];
+            int Ncurr = Nprev * N[r];
+            insertfftKernel(localString, N[r], numIter);
+
+            if (r < (numRadix - 1)) {
+                fftPadding pad;
+
+                insertTwiddleKernel(localString, N[r], numIter, Nprev, len, numWorkItemsPerXForm);
+                pad = getPadding(numWorkItemsPerXForm, Nprev, numWorkItemsReq, numXFormsPerWG, N[r], this.num_local_mem_banks);
+                kInfo.lmem_size = (pad.lMemSize > kInfo.lmem_size) ? pad.lMemSize : kInfo.lmem_size;
+                insertLocalStoreIndexArithmatic(localString, numWorkItemsReq, numXFormsPerWG, N[r], pad.offset, pad.midPad);
+                insertLocalLoadIndexArithmatic(localString, Nprev, N[r], numWorkItemsReq, numWorkItemsPerXForm, numXFormsPerWG, pad.offset, pad.midPad);
+                insertLocalStores(localString, numIter, N[r], numWorkItemsPerXForm, numWorkItemsReq, pad.offset, xcomp);
+                insertLocalLoads(localString, n, N[r], N[r + 1], Nprev, Ncurr, numWorkItemsPerXForm, numWorkItemsReq, pad.offset, xcomp);
+                insertLocalStores(localString, numIter, N[r], numWorkItemsPerXForm, numWorkItemsReq, pad.offset, ycomp);
+                insertLocalLoads(localString, n, N[r], N[r + 1], Nprev, Ncurr, numWorkItemsPerXForm, numWorkItemsReq, pad.offset, ycomp);
+                Nprev = Ncurr;
+                len = len / N[r];
+            }
+        }
+
+        lMemSize = insertGlobalStoresAndTranspose(localString, n, maxRadix, N[numRadix - 1], numWorkItemsPerXForm, numXFormsPerWG, this.min_mem_coalesce_width, dataFormat);
+        kInfo.lmem_size = (lMemSize > kInfo.lmem_size) ? lMemSize : kInfo.lmem_size;
+
+        insertHeader(kernelString, kernelName, dataFormat);
+        kernelString.append("{\n");
+        if (kInfo.lmem_size > 0) {
+            kernelString.append("    __local float sMem[").append(kInfo.lmem_size).append("];\n");
+        }
+        kernelString.append(localString);
+        kernelString.append("}\n");
+    }
+
+// For size larger than what can be computed using local memory fft, global transposes
+// multiple kernel launces is needed. For these sizes, size can be decomposed using
+// much larger base radices i.e. say size = 262144 = 128 x 64 x 32. Thus three kernel
+// launches will be needed, first computing 64 x 32, length 128 ffts, second computing
+// 128 x 32 length 64 ffts, and finally a kernel computing 128 x 64 length 32 ffts.
+// Each of these base radices can futher be divided into factors so that each of these
+// base ffts can be computed within one kernel launch using in-register ffts and local
+// memory transposes i.e for the first kernel above which computes 64 x 32 ffts on length
+// 128, 128 can be decomposed into 128 = 16 x 8 i.e. 8 work items can compute 8 length
+// 16 ffts followed by transpose using local memory followed by each of these eight
+// work items computing 2 length 8 ffts thus computing 16 length 8 ffts in total. This
+// means only 8 work items are needed for computing one length 128 fft. If we choose
+// work group size of say 64, we can compute 64/8 = 8 length 128 ffts within one
+// work group. Since we need to compute 64 x 32 length 128 ffts in first kernel, this
+// means we need to launch 64 x 32 / 8 = 256 work groups with 64 work items in each
+// work group where each work group is computing 8 length 128 ffts where each length
+// 128 fft is computed by 8 work items. Same logic can be applied to other two kernels
+// in this example. Users can play with difference base radices and difference
+// decompositions of base radices to generates different kernels and see which gives
+// best performance. Following function is just fixed to use 128 as base radix
+    int getGlobalRadixInfo(int n, int[] radix, int[] R1, int[] R2) {
+        int baseRadix = Math.min(n, 128);
+
+        int numR = 0;
+        int N = n;
+        while (N > baseRadix) {
+            N /= baseRadix;
+            numR++;
+        }
+
+        for (int i = 0; i < numR; i++) {
+            radix[i] = baseRadix;
+        }
+
+        radix[numR] = N;
+        numR++;
+
+        for (int i = 0; i < numR; i++) {
+            int B = radix[i];
+            if (B <= 8) {
+                R1[i] = B;
+                R2[i] = 1;
+                continue;
+            }
+
+            int r1 = 2;
+            int r2 = B / r1;
+            while (r2 > r1) {
+                r1 *= 2;
+                r2 = B / r1;
+            }
+            R1[i] = r1;
+            R2[i] = r2;
+        }
+        return numR;
+    }
+
+    void createGlobalFFTKernelString(int n, int BS, CLFFTKernelDir dir, int vertBS) {
+        int i, j, k, t;
+        int[] radixArr = new int[10];
+        int[] R1Arr = new int[10];
+        int[] R2Arr = new int[10];
+        int radix, R1, R2;
+        int numRadices;
+
+        int maxThreadsPerBlock = this.max_work_item_per_workgroup;
+        int maxArrayLen = this.max_radix;
+        int batchSize = this.min_mem_coalesce_width;
+        CLFFTDataFormat dataFormat = this.format;
+        boolean vertical = (dir == dir.X) ? false : true;
+
+        numRadices = getGlobalRadixInfo(n, radixArr, R1Arr, R2Arr);
+
+        int numPasses = numRadices;
+
+        StringBuilder localString = new StringBuilder();
+        String kernelName;
+        StringBuilder kernelString = this.kernel_string;
+
+        int kCount = kernel_list.size();
+        //cl_fft_kernel_info **kInfo = &this.kernel_list;
+        //int kCount = 0;
+
+        //while(*kInfo)
+        //{
+        //	kInfo = &kInfo.next;
+        //	kCount++;
+        //}
+
+        int N = n;
+        int m = (int) log2(n);
+        int Rinit = vertical ? BS : 1;
+        batchSize = vertical ? Math.min(BS, batchSize) : batchSize;
+        int passNum;
+
+        for (passNum = 0; passNum < numPasses; passNum++) {
+
+            localString.setLength(0);
+            //kernelName.clear();
+
+            radix = radixArr[passNum];
+            R1 = R1Arr[passNum];
+            R2 = R2Arr[passNum];
+
+            int strideI = Rinit;
+            for (i = 0; i < numPasses; i++) {
+                if (i != passNum) {
+                    strideI *= radixArr[i];
+                }
+            }
+
+            int strideO = Rinit;
+            for (i = 0; i < passNum; i++) {
+                strideO *= radixArr[i];
+            }
+
+            int threadsPerXForm = R2;
+            batchSize = R2 == 1 ? this.max_work_item_per_workgroup : batchSize;
+            batchSize = Math.min(batchSize, strideI);
+            int threadsPerBlock = batchSize * threadsPerXForm;
+            threadsPerBlock = Math.min(threadsPerBlock, maxThreadsPerBlock);
+            batchSize = threadsPerBlock / threadsPerXForm;
+            assert (R2 <= R1);
+            assert (R1 * R2 == radix);
+            assert (R1 <= maxArrayLen);
+            assert (threadsPerBlock <= maxThreadsPerBlock);
+
+            int numIter = R1 / R2;
+            int gInInc = threadsPerBlock / batchSize;
+
+
+            int lgStrideO = log2(strideO);
+            int numBlocksPerXForm = strideI / batchSize;
+            int numBlocks = numBlocksPerXForm;
+            if (!vertical) {
+                numBlocks *= BS;
+            } else {
+                numBlocks *= vertBS;
+            }
+
+            kernelName = "fft" + (kCount);
+            CLFFTKernelInfo kInfo = new CLFFTKernelInfo();
+            if (R2 == 1) {
+                kInfo.lmem_size = 0;
+            } else {
+                if (strideO == 1) {
+                    kInfo.lmem_size = (radix + 1) * batchSize;
+                } else {
+                    kInfo.lmem_size = threadsPerBlock * R1;
+                }
+            }
+            kInfo.num_workgroups = numBlocks;
+            kInfo.num_xforms_per_workgroup = 1;
+            kInfo.num_workitems_per_workgroup = threadsPerBlock;
+            kInfo.dir = dir;
+            kInfo.in_place_possible = ((passNum == (numPasses - 1)) && ((numPasses & 1) != 0));
+            //kInfo.next = NULL;
+            kInfo.kernel_name = kernelName;
+
+            insertVariables(localString, R1);
+
+            if (vertical) {
+                localString.append("xNum = groupId >> ").append((int) log2(numBlocksPerXForm)).append(";\n");
+                localString.append("groupId = groupId & ").append(numBlocksPerXForm - 1).append(";\n");
+                localString.append("indexIn = mad24(groupId, ").append(batchSize).append(", xNum << ").append((int) log2(n * BS)).append(");\n");
+                localString.append("tid = mul24(groupId, ").append(batchSize).append(");\n");
+                localString.append("i = tid >> ").append(lgStrideO).append(";\n");
+                localString.append("j = tid & ").append(strideO - 1).append(";\n");
+                int stride = radix * Rinit;
+                for (i = 0; i < passNum; i++) {
+                    stride *= radixArr[i];
+                }
+                localString.append("indexOut = mad24(i, ").append(stride).append(", j + ").append("(xNum << ").append((int) log2(n * BS)).append("));\n");
+                localString.append("bNum = groupId;\n");
+            } else {
+                int lgNumBlocksPerXForm = log2(numBlocksPerXForm);
+                localString.append("bNum = groupId & ").append(numBlocksPerXForm - 1).append(";\n");
+                localString.append("xNum = groupId >> ").append(lgNumBlocksPerXForm).append(";\n");
+                localString.append("indexIn = mul24(bNum, ").append(batchSize).append(");\n");
+                localString.append("tid = indexIn;\n");
+                localString.append("i = tid >> ").append(lgStrideO).append(";\n");
+                localString.append("j = tid & ").append(strideO - 1).append(";\n");
+                int stride = radix * Rinit;
+                for (i = 0; i < passNum; i++) {
+                    stride *= radixArr[i];
+                }
+                localString.append("indexOut = mad24(i, ").append(stride).append(", j);\n");
+                localString.append("indexIn += (xNum << ").append(m).append(");\n");
+                localString.append("indexOut += (xNum << ").append(m).append(");\n");
+            }
+
+            // Load Data
+            int lgBatchSize = log2(batchSize);
+            localString.append("tid = lId;\n");
+            localString.append("i = tid & ").append(batchSize - 1).append(";\n");
+            localString.append("j = tid >> ").append(lgBatchSize).append(";\n");
+            localString.append("indexIn += mad24(j, ").append(strideI).append(", i);\n");
+
+            if (dataFormat == dataFormat.SplitComplexFormat) {
+                localString.append("in_real += indexIn;\n");
+                localString.append("in_imag += indexIn;\n");
+                for (j = 0; j < R1; j++) {
+                    localString.append("a[").append(j).append("].x = in_real[").append(j * gInInc * strideI).append("];\n");
+                }
+                for (j = 0; j < R1; j++) {
+                    localString.append("a[").append(j).append("].y = in_imag[").append(j * gInInc * strideI).append("];\n");
+                }
+            } else {
+                localString.append("in += indexIn;\n");
+                for (j = 0; j < R1; j++) {
+                    localString.append("a[").append(j).append("] = in[").append(j * gInInc * strideI).append("];\n");
+                }
+            }
+
+            localString.append("fftKernel").append(R1).append("(a, dir);\n");
+
+            if (R2 > 1) {
+                // twiddle
+                for (k = 1; k < R1; k++) {
+                    localString.append("ang = dir*(2.0f*M_PI*").append(k).append("/").append(radix).append(")*j;\n");
+                    localString.append("w = (float2)(native_cos(ang), native_sin(ang));\n");
+                    localString.append("a[").append(k).append("] = complexMul(a[").append(k).append("], w);\n");
+                }
+
+                // shuffle
+                numIter = R1 / R2;
+                localString.append("indexIn = mad24(j, ").append(threadsPerBlock * numIter).append(", i);\n");
+                localString.append("lMemStore = sMem + tid;\n");
+                localString.append("lMemLoad = sMem + indexIn;\n");
+                for (k = 0; k < R1; k++) {
+                    localString.append("lMemStore[").append(k * threadsPerBlock).append("] = a[").append(k).append("].x;\n");
+                }
+                localString.append("barrier(CLK_LOCAL_MEM_FENCE);\n");
+                for (k = 0; k < numIter; k++) {
+                    for (t = 0; t < R2; t++) {
+                        localString.append("a[").append(k * R2 + t).append("].x = lMemLoad[").append(t * batchSize + k * threadsPerBlock).append("];\n");
+                    }
+                }
+                localString.append("barrier(CLK_LOCAL_MEM_FENCE);\n");
+                for (k = 0; k < R1; k++) {
+                    localString.append("lMemStore[").append(k * threadsPerBlock).append("] = a[").append(k).append("].y;\n");
+                }
+                localString.append("barrier(CLK_LOCAL_MEM_FENCE);\n");
+                for (k = 0; k < numIter; k++) {
+                    for (t = 0; t < R2; t++) {
+                        localString.append("a[").append(k * R2 + t).append("].y = lMemLoad[").append(t * batchSize + k * threadsPerBlock).append("];\n");
+                    }
+                }
+                localString.append("barrier(CLK_LOCAL_MEM_FENCE);\n");
+
+                for (j = 0; j < numIter; j++) {
+                    localString.append("fftKernel").append(R2).append("(a + ").append(j * R2).append(", dir);\n");
+                }
+            }
+
+            // twiddle
+            if (passNum < (numPasses - 1)) {
+                localString.append("l = ((bNum << ").append(lgBatchSize).append(") + i) >> ").append(lgStrideO).append(";\n");
+                localString.append("k = j << ").append((int) log2(R1 / R2)).append(";\n");
+                localString.append("ang1 = dir*(2.0f*M_PI/").append(N).append(")*l;\n");
+                for (t = 0; t < R1; t++) {
+                    localString.append("ang = ang1*(k + ").append((t % R2) * R1 + (t / R2)).append(");\n");
+                    localString.append("w = (float2)(native_cos(ang), native_sin(ang));\n");
+                    localString.append("a[").append(t).append("] = complexMul(a[").append(t).append("], w);\n");
+                }
+            }
+
+            // Store Data
+            if (strideO == 1) {
+
+                localString.append("lMemStore = sMem + mad24(i, ").append(radix + 1).append(", j << ").append((int) log2(R1 / R2)).append(");\n");
+                localString.append("lMemLoad = sMem + mad24(tid >> ").append((int) log2(radix)).append(", ").append(radix + 1).append(", tid & ").append(radix - 1).append(");\n");
+
+                for (i = 0; i < R1 / R2; i++) {
+                    for (j = 0; j < R2; j++) {
+                        localString.append("lMemStore[ ").append(i + j * R1).append("] = a[").append(i * R2 + j).append("].x;\n");
+                    }
+                }
+                localString.append("barrier(CLK_LOCAL_MEM_FENCE);\n");
+                if (threadsPerBlock >= radix) {
+                    for (i = 0; i < R1; i++) {
+                        localString.append("a[").append(i).append("].x = lMemLoad[").append(i * (radix + 1) * (threadsPerBlock / radix)).append("];\n");
+                    }
+                } else {
+                    int innerIter = radix / threadsPerBlock;
+                    int outerIter = R1 / innerIter;
+                    for (i = 0; i < outerIter; i++) {
+                        for (j = 0; j < innerIter; j++) {
+                            localString.append("a[").append(i * innerIter + j).append("].x = lMemLoad[").append(j * threadsPerBlock + i * (radix + 1)).append("];\n");
+                        }
+                    }
+                }
+                localString.append("barrier(CLK_LOCAL_MEM_FENCE);\n");
+
+                for (i = 0; i < R1 / R2; i++) {
+                    for (j = 0; j < R2; j++) {
+                        localString.append("lMemStore[ ").append(i + j * R1).append("] = a[").append(i * R2 + j).append("].y;\n");
+                    }
+                }
+                localString.append("barrier(CLK_LOCAL_MEM_FENCE);\n");
+                if (threadsPerBlock >= radix) {
+                    for (i = 0; i < R1; i++) {
+                        localString.append("a[").append(i).append("].y = lMemLoad[").append(i * (radix + 1) * (threadsPerBlock / radix)).append("];\n");
+                    }
+                } else {
+                    int innerIter = radix / threadsPerBlock;
+                    int outerIter = R1 / innerIter;
+                    for (i = 0; i < outerIter; i++) {
+                        for (j = 0; j < innerIter; j++) {
+                            localString.append("a[").append(i * innerIter + j).append("].y = lMemLoad[").append(j * threadsPerBlock + i * (radix + 1)).append("];\n");
+                        }
+                    }
+                }
+                localString.append("barrier(CLK_LOCAL_MEM_FENCE);\n");
+
+                localString.append("indexOut += tid;\n");
+                if (dataFormat == dataFormat.SplitComplexFormat) {
+                    localString.append("out_real += indexOut;\n");
+                    localString.append("out_imag += indexOut;\n");
+                    for (k = 0; k < R1; k++) {
+                        localString.append("out_real[").append(k * threadsPerBlock).append("] = a[").append(k).append("].x;\n");
+                    }
+                    for (k = 0; k < R1; k++) {
+                        localString.append("out_imag[").append(k * threadsPerBlock).append("] = a[").append(k).append("].y;\n");
+                    }
+                } else {
+                    localString.append("out += indexOut;\n");
+                    for (k = 0; k < R1; k++) {
+                        localString.append("out[").append(k * threadsPerBlock).append("] = a[").append(k).append("];\n");
+                    }
+                }
+
+            } else {
+                localString.append("indexOut += mad24(j, ").append(numIter * strideO).append(", i);\n");
+                if (dataFormat == dataFormat.SplitComplexFormat) {
+                    localString.append("out_real += indexOut;\n");
+                    localString.append("out_imag += indexOut;\n");
+                    for (k = 0; k < R1; k++) {
+                        localString.append("out_real[").append(((k % R2) * R1 + (k / R2)) * strideO).append("] = a[").append(k).append("].x;\n");
+                    }
+                    for (k = 0; k < R1; k++) {
+                        localString.append("out_imag[").append(((k % R2) * R1 + (k / R2)) * strideO).append("] = a[").append(k).append("].y;\n");
+                    }
+                } else {
+                    localString.append("out += indexOut;\n");
+                    for (k = 0; k < R1; k++) {
+                        localString.append("out[").append(((k % R2) * R1 + (k / R2)) * strideO).append("] = a[").append(k).append("];\n");
+                    }
+                }
+            }
+
+            insertHeader(kernelString, kernelName, dataFormat);
+            kernelString.append("{\n");
+            if (kInfo.lmem_size > 0) {
+                kernelString.append("    __local float sMem[").append(kInfo.lmem_size).append("];\n");
+            }
+            kernelString.append(localString);
+            kernelString.append("}\n");
+
+            N /= radix;
+            kernel_list.add(kInfo);
+            kCount++;
+        }
+    }
+
+    void FFT1D(CLFFTKernelDir dir) {
+        int[] radixArray = new int[10];
+
+        switch (dir) {
+            case X:
+                if (this.size.x > this.max_localmem_fft_size) {
+                    createGlobalFFTKernelString(this.size.x, 1, dir, 1);
+                } else if (this.size.x > 1) {
+                    getRadixArray(this.size.x, radixArray, 0);
+                    if (this.size.x / radixArray[0] <= this.max_work_item_per_workgroup) {
+                        createLocalMemfftKernelString();
+                    } else {
+                        getRadixArray(this.size.x, radixArray, this.max_radix);
+                        if (this.size.x / radixArray[0] <= this.max_work_item_per_workgroup) {
+                            createLocalMemfftKernelString();
+                        } else {
+                            createGlobalFFTKernelString(this.size.x, 1, dir, 1);
+                        }
+                    }
+                }
+                break;
+
+            case Y:
+                if (this.size.y > 1) {
+                    createGlobalFFTKernelString(this.size.y, this.size.x, dir, 1);
+                }
+                break;
+
+            case Z:
+                if (this.size.z > 1) {
+                    createGlobalFFTKernelString(this.size.z, this.size.x * this.size.y, dir, 1);
+                }
+            default:
+                return;
+        }
+    }
+
+    /*
+     *
+     * Pre-defined kernel parts
+     *
+     */
+    static String baseKernels =
+            "#ifndef M_PI\n"
+            + "#define M_PI 0x1.921fb54442d18p+1\n"
+            + "#endif\n"
+            + "#define complexMul(a,b) ((float2)(mad(-(a).y, (b).y, (a).x * (b).x), mad((a).y, (b).x, (a).x * (b).y)))\n"
+            + "#define conj(a) ((float2)((a).x, -(a).y))\n"
+            + "#define conjTransp(a) ((float2)(-(a).y, (a).x))\n"
+            + "\n"
+            + "#define fftKernel2(a,dir) \\\n"
+            + "{ \\\n"
+            + "    float2 c = (a)[0];    \\\n"
+            + "    (a)[0] = c + (a)[1];  \\\n"
+            + "    (a)[1] = c - (a)[1];  \\\n"
+            + "}\n"
+            + "\n"
+            + "#define fftKernel2S(d1,d2,dir) \\\n"
+            + "{ \\\n"
+            + "    float2 c = (d1);   \\\n"
+            + "    (d1) = c + (d2);   \\\n"
+            + "    (d2) = c - (d2);   \\\n"
+            + "}\n"
+            + "\n"
+            + "#define fftKernel4(a,dir) \\\n"
+            + "{ \\\n"
+            + "    fftKernel2S((a)[0], (a)[2], dir); \\\n"
+            + "    fftKernel2S((a)[1], (a)[3], dir); \\\n"
+            + "    fftKernel2S((a)[0], (a)[1], dir); \\\n"
+            + "    (a)[3] = (float2)(dir)*(conjTransp((a)[3])); \\\n"
+            + "    fftKernel2S((a)[2], (a)[3], dir); \\\n"
+            + "    float2 c = (a)[1]; \\\n"
+            + "    (a)[1] = (a)[2]; \\\n"
+            + "    (a)[2] = c; \\\n"
+            + "}\n"
+            + "\n"
+            + "#define fftKernel4s(a0,a1,a2,a3,dir) \\\n"
+            + "{ \\\n"
+            + "    fftKernel2S((a0), (a2), dir); \\\n"
+            + "    fftKernel2S((a1), (a3), dir); \\\n"
+            + "    fftKernel2S((a0), (a1), dir); \\\n"
+            + "    (a3) = (float2)(dir)*(conjTransp((a3))); \\\n"
+            + "    fftKernel2S((a2), (a3), dir); \\\n"
+            + "    float2 c = (a1); \\\n"
+            + "    (a1) = (a2); \\\n"
+            + "    (a2) = c; \\\n"
+            + "}\n"
+            + "\n"
+            + "#define bitreverse8(a) \\\n"
+            + "{ \\\n"
+            + "    float2 c; \\\n"
+            + "    c = (a)[1]; \\\n"
+            + "    (a)[1] = (a)[4]; \\\n"
+            + "    (a)[4] = c; \\\n"
+            + "    c = (a)[3]; \\\n"
+            + "    (a)[3] = (a)[6]; \\\n"
+            + "    (a)[6] = c; \\\n"
+            + "}\n"
+            + "\n"
+            + "#define fftKernel8(a,dir) \\\n"
+            + "{ \\\n"
+            + "	const float2 w1  = (float2)(0x1.6a09e6p-1f,  dir*0x1.6a09e6p-1f);  \\\n"
+            + "	const float2 w3  = (float2)(-0x1.6a09e6p-1f, dir*0x1.6a09e6p-1f);  \\\n"
+            + "	float2 c; \\\n"
+            + "	fftKernel2S((a)[0], (a)[4], dir); \\\n"
+            + "	fftKernel2S((a)[1], (a)[5], dir); \\\n"
+            + "	fftKernel2S((a)[2], (a)[6], dir); \\\n"
+            + "	fftKernel2S((a)[3], (a)[7], dir); \\\n"
+            + "	(a)[5] = complexMul(w1, (a)[5]); \\\n"
+            + "	(a)[6] = (float2)(dir)*(conjTransp((a)[6])); \\\n"
+            + "	(a)[7] = complexMul(w3, (a)[7]); \\\n"
+            + "	fftKernel2S((a)[0], (a)[2], dir); \\\n"
+            + "	fftKernel2S((a)[1], (a)[3], dir); \\\n"
+            + "	fftKernel2S((a)[4], (a)[6], dir); \\\n"
+            + "	fftKernel2S((a)[5], (a)[7], dir); \\\n"
+            + "	(a)[3] = (float2)(dir)*(conjTransp((a)[3])); \\\n"
+            + "	(a)[7] = (float2)(dir)*(conjTransp((a)[7])); \\\n"
+            + "	fftKernel2S((a)[0], (a)[1], dir); \\\n"
+            + "	fftKernel2S((a)[2], (a)[3], dir); \\\n"
+            + "	fftKernel2S((a)[4], (a)[5], dir); \\\n"
+            + "	fftKernel2S((a)[6], (a)[7], dir); \\\n"
+            + "	bitreverse8((a)); \\\n"
+            + "}\n"
+            + "\n"
+            + "#define bitreverse4x4(a) \\\n"
+            + "{ \\\n"
+            + "	float2 c; \\\n"
+            + "	c = (a)[1];  (a)[1]  = (a)[4];  (a)[4]  = c; \\\n"
+            + "	c = (a)[2];  (a)[2]  = (a)[8];  (a)[8]  = c; \\\n"
+            + "	c = (a)[3];  (a)[3]  = (a)[12]; (a)[12] = c; \\\n"
+            + "	c = (a)[6];  (a)[6]  = (a)[9];  (a)[9]  = c; \\\n"
+            + "	c = (a)[7];  (a)[7]  = (a)[13]; (a)[13] = c; \\\n"
+            + "	c = (a)[11]; (a)[11] = (a)[14]; (a)[14] = c; \\\n"
+            + "}\n"
+            + "\n"
+            + "#define fftKernel16(a,dir) \\\n"
+            + "{ \\\n"
+            + "    const float w0 = 0x1.d906bcp-1f; \\\n"
+            + "    const float w1 = 0x1.87de2ap-2f; \\\n"
+            + "    const float w2 = 0x1.6a09e6p-1f; \\\n"
+            + "    fftKernel4s((a)[0], (a)[4], (a)[8],  (a)[12], dir); \\\n"
+            + "    fftKernel4s((a)[1], (a)[5], (a)[9],  (a)[13], dir); \\\n"
+            + "    fftKernel4s((a)[2], (a)[6], (a)[10], (a)[14], dir); \\\n"
+            + "    fftKernel4s((a)[3], (a)[7], (a)[11], (a)[15], dir); \\\n"
+            + "    (a)[5]  = complexMul((a)[5], (float2)(w0, dir*w1)); \\\n"
+            + "    (a)[6]  = complexMul((a)[6], (float2)(w2, dir*w2)); \\\n"
+            + "    (a)[7]  = complexMul((a)[7], (float2)(w1, dir*w0)); \\\n"
+            + "    (a)[9]  = complexMul((a)[9], (float2)(w2, dir*w2)); \\\n"
+            + "    (a)[10] = (float2)(dir)*(conjTransp((a)[10])); \\\n"
+            + "    (a)[11] = complexMul((a)[11], (float2)(-w2, dir*w2)); \\\n"
+            + "    (a)[13] = complexMul((a)[13], (float2)(w1, dir*w0)); \\\n"
+            + "    (a)[14] = complexMul((a)[14], (float2)(-w2, dir*w2)); \\\n"
+            + "    (a)[15] = complexMul((a)[15], (float2)(-w0, dir*-w1)); \\\n"
+            + "    fftKernel4((a), dir); \\\n"
+            + "    fftKernel4((a) + 4, dir); \\\n"
+            + "    fftKernel4((a) + 8, dir); \\\n"
+            + "    fftKernel4((a) + 12, dir); \\\n"
+            + "    bitreverse4x4((a)); \\\n"
+            + "}\n"
+            + "\n"
+            + "#define bitreverse32(a) \\\n"
+            + "{ \\\n"
+            + "    float2 c1, c2; \\\n"
+            + "    c1 = (a)[2];   (a)[2] = (a)[1];   c2 = (a)[4];   (a)[4] = c1;   c1 = (a)[8];   (a)[8] = c2;    c2 = (a)[16];  (a)[16] = c1;   (a)[1] = c2; \\\n"
+            + "    c1 = (a)[6];   (a)[6] = (a)[3];   c2 = (a)[12];  (a)[12] = c1;  c1 = (a)[24];  (a)[24] = c2;   c2 = (a)[17];  (a)[17] = c1;   (a)[3] = c2; \\\n"
+            + "    c1 = (a)[10];  (a)[10] = (a)[5];  c2 = (a)[20];  (a)[20] = c1;  c1 = (a)[9];   (a)[9] = c2;    c2 = (a)[18];  (a)[18] = c1;   (a)[5] = c2; \\\n"
+            + "    c1 = (a)[14];  (a)[14] = (a)[7];  c2 = (a)[28];  (a)[28] = c1;  c1 = (a)[25];  (a)[25] = c2;   c2 = (a)[19];  (a)[19] = c1;   (a)[7] = c2; \\\n"
+            + "    c1 = (a)[22];  (a)[22] = (a)[11]; c2 = (a)[13];  (a)[13] = c1;  c1 = (a)[26];  (a)[26] = c2;   c2 = (a)[21];  (a)[21] = c1;   (a)[11] = c2; \\\n"
+            + "    c1 = (a)[30];  (a)[30] = (a)[15]; c2 = (a)[29];  (a)[29] = c1;  c1 = (a)[27];  (a)[27] = c2;   c2 = (a)[23];  (a)[23] = c1;   (a)[15] = c2; \\\n"
+            + "}\n"
+            + "\n"
+            + "#define fftKernel32(a,dir) \\\n"
+            + "{ \\\n"
+            + "    fftKernel2S((a)[0],  (a)[16], dir); \\\n"
+            + "    fftKernel2S((a)[1],  (a)[17], dir); \\\n"
+            + "    fftKernel2S((a)[2],  (a)[18], dir); \\\n"
+            + "    fftKernel2S((a)[3],  (a)[19], dir); \\\n"
+            + "    fftKernel2S((a)[4],  (a)[20], dir); \\\n"
+            + "    fftKernel2S((a)[5],  (a)[21], dir); \\\n"
+            + "    fftKernel2S((a)[6],  (a)[22], dir); \\\n"
+            + "    fftKernel2S((a)[7],  (a)[23], dir); \\\n"
+            + "    fftKernel2S((a)[8],  (a)[24], dir); \\\n"
+            + "    fftKernel2S((a)[9],  (a)[25], dir); \\\n"
+            + "    fftKernel2S((a)[10], (a)[26], dir); \\\n"
+            + "    fftKernel2S((a)[11], (a)[27], dir); \\\n"
+            + "    fftKernel2S((a)[12], (a)[28], dir); \\\n"
+            + "    fftKernel2S((a)[13], (a)[29], dir); \\\n"
+            + "    fftKernel2S((a)[14], (a)[30], dir); \\\n"
+            + "    fftKernel2S((a)[15], (a)[31], dir); \\\n"
+            + "    (a)[17] = complexMul((a)[17], (float2)(0x1.f6297cp-1f, dir*0x1.8f8b84p-3f)); \\\n"
+            + "    (a)[18] = complexMul((a)[18], (float2)(0x1.d906bcp-1f, dir*0x1.87de2ap-2f)); \\\n"
+            + "    (a)[19] = complexMul((a)[19], (float2)(0x1.a9b662p-1f, dir*0x1.1c73b4p-1f)); \\\n"
+            + "    (a)[20] = complexMul((a)[20], (float2)(0x1.6a09e6p-1f, dir*0x1.6a09e6p-1f)); \\\n"
+            + "    (a)[21] = complexMul((a)[21], (float2)(0x1.1c73b4p-1f, dir*0x1.a9b662p-1f)); \\\n"
+            + "    (a)[22] = complexMul((a)[22], (float2)(0x1.87de2ap-2f, dir*0x1.d906bcp-1f)); \\\n"
+            + "    (a)[23] = complexMul((a)[23], (float2)(0x1.8f8b84p-3f, dir*0x1.f6297cp-1f)); \\\n"
+            + "    (a)[24] = complexMul((a)[24], (float2)(0x0p+0f, dir*0x1p+0f)); \\\n"
+            + "    (a)[25] = complexMul((a)[25], (float2)(-0x1.8f8b84p-3f, dir*0x1.f6297cp-1f)); \\\n"
+            + "    (a)[26] = complexMul((a)[26], (float2)(-0x1.87de2ap-2f, dir*0x1.d906bcp-1f)); \\\n"
+            + "    (a)[27] = complexMul((a)[27], (float2)(-0x1.1c73b4p-1f, dir*0x1.a9b662p-1f)); \\\n"
+            + "    (a)[28] = complexMul((a)[28], (float2)(-0x1.6a09e6p-1f, dir*0x1.6a09e6p-1f)); \\\n"
+            + "    (a)[29] = complexMul((a)[29], (float2)(-0x1.a9b662p-1f, dir*0x1.1c73b4p-1f)); \\\n"
+            + "    (a)[30] = complexMul((a)[30], (float2)(-0x1.d906bcp-1f, dir*0x1.87de2ap-2f)); \\\n"
+            + "    (a)[31] = complexMul((a)[31], (float2)(-0x1.f6297cp-1f, dir*0x1.8f8b84p-3f)); \\\n"
+            + "    fftKernel16((a), dir); \\\n"
+            + "    fftKernel16((a) + 16, dir); \\\n"
+            + "    bitreverse32((a)); \\\n"
+            + "}\n\n";
+    static String twistKernelInterleaved =
+            "__kernel void \\\n"
+            + "clFFT_1DTwistInterleaved(__global float2 *in, unsigned int startRow, unsigned int numCols, unsigned int N, unsigned int numRowsToProcess, int dir) \\\n"
+            + "{ \\\n"
+            + "   float2 a, w; \\\n"
+            + "   float ang; \\\n"
+            + "   unsigned int j; \\\n"
+            + "	unsigned int i = get_global_id(0); \\\n"
+            + "	unsigned int startIndex = i; \\\n"
+            + "	 \\\n"
+            + "	if(i < numCols) \\\n"
+            + "	{ \\\n"
+            + "	    for(j = 0; j < numRowsToProcess; j++) \\\n"
+            + "	    { \\\n"
+            + "	        a = in[startIndex]; \\\n"
+            + "	        ang = 2.0f * M_PI * dir * i * (startRow + j) / N; \\\n"
+            + "	        w = (float2)(native_cos(ang), native_sin(ang)); \\\n"
+            + "	        a = complexMul(a, w); \\\n"
+            + "	        in[startIndex] = a; \\\n"
+            + "	        startIndex += numCols; \\\n"
+            + "	    } \\\n"
+            + "	}	 \\\n"
+            + "} \\\n";
+    static String twistKernelPlannar =
+            "__kernel void \\\n"
+            + "clFFT_1DTwistSplit(__global float *in_real, __global float *in_imag , unsigned int startRow, unsigned int numCols, unsigned int N, unsigned int numRowsToProcess, int dir) \\\n"
+            + "{ \\\n"
+            + "    float2 a, w; \\\n"
+            + "    float ang; \\\n"
+            + "    unsigned int j; \\\n"
+            + "	unsigned int i = get_global_id(0); \\\n"
+            + "	unsigned int startIndex = i; \\\n"
+            + "	 \\\n"
+            + "	if(i < numCols) \\\n"
+            + "	{ \\\n"
+            + "	    for(j = 0; j < numRowsToProcess; j++) \\\n"
+            + "	    { \\\n"
+            + "	        a = (float2)(in_real[startIndex], in_imag[startIndex]); \\\n"
+            + "	        ang = 2.0f * M_PI * dir * i * (startRow + j) / N; \\\n"
+            + "	        w = (float2)(native_cos(ang), native_sin(ang)); \\\n"
+            + "	        a = complexMul(a, w); \\\n"
+            + "	        in_real[startIndex] = a.x; \\\n"
+            + "	        in_imag[startIndex] = a.y; \\\n"
+            + "	        startIndex += numCols; \\\n"
+            + "	    } \\\n"
+            + "	}	 \\\n"
+            + "} \\\n";
+}
diff --git a/src/com/jogamp/opencl/demos/fft/ImageView.java b/src/com/jogamp/opencl/demos/fft/ImageView.java
new file mode 100644
index 0000000..c5d07a1
--- /dev/null
+++ b/src/com/jogamp/opencl/demos/fft/ImageView.java
@@ -0,0 +1,25 @@
+package com.jogamp.opencl.demos.fft;
+
+import java.awt.Dimension;
+import java.awt.Graphics;
+import java.awt.image.BufferedImage;
+import javax.swing.JComponent;
+
+/**
+ * Just draws an image.
+ * @author notzed
+ */
+class ImageView extends JComponent {
+
+    BufferedImage img;
+
+    public ImageView(BufferedImage img) {
+        this.img = img;
+        this.setPreferredSize(new Dimension(img.getWidth(), img.getHeight()));
+    }
+
+    @Override
+    protected void paintComponent(Graphics g) {
+        g.drawImage(img, 0, 0, null);
+    }
+}
diff --git a/src/com/jogamp/opencl/demos/fft/PaintView.java b/src/com/jogamp/opencl/demos/fft/PaintView.java
new file mode 100644
index 0000000..9dea3c8
--- /dev/null
+++ b/src/com/jogamp/opencl/demos/fft/PaintView.java
@@ -0,0 +1,98 @@
+package com.jogamp.opencl.demos.fft;
+
+import java.awt.Color;
+import java.awt.Graphics2D;
+import java.awt.Paint;
+import java.awt.RadialGradientPaint;
+import java.awt.Rectangle;
+import java.awt.Shape;
+import java.awt.event.MouseEvent;
+import java.awt.event.MouseListener;
+import java.awt.event.MouseMotionListener;
+import java.awt.geom.Point2D;
+import java.awt.image.BufferedImage;
+
+/**
+ * Draws an image and lets you draw white dots in it with the mouse.  Or big white dots with code.
+ * @author notzed
+ */
+class PaintView extends ImageView implements MouseListener, MouseMotionListener {
+
+	Graphics2D imgg;
+	Paint paint;
+	Shape brush;
+	BlurTest win;
+
+	public PaintView(BlurTest win, BufferedImage img) {
+		super(img);
+
+		this.win = win;
+
+		paint = new RadialGradientPaint(new Point2D.Float(0, 0), 3,
+				new float[]{0.0f, 1.0f}, new Color[]{new Color(255, 255, 255, 255), new Color(255, 255, 255, 0)});
+		brush = new java.awt.geom.Ellipse2D.Float(-5, -5, 11, 11);
+
+		imgg = img.createGraphics();
+
+		this.addMouseListener(this);
+	}
+
+	void drawPaint(double x, double y) {
+		Graphics2D gg = (Graphics2D) imgg.create();
+
+		gg.translate(x, y);
+		gg.setPaint(paint);
+		gg.fill(brush);
+
+		gg.dispose();
+
+		repaint(new Rectangle((int) (x - 6), (int) (y - 6), 12, 12));
+		// close your eyes if you're under-age ...
+		win.recalc();
+	}
+
+	public void drawDot(double width, double height, double angle) {
+		Graphics2D gg = (Graphics2D) imgg.create();
+
+		gg.setPaint(paint);
+		gg.translate(img.getWidth() / 2, img.getHeight() / 2);
+		gg.rotate(angle);
+		gg.scale(width, height);
+		gg.fill(brush);
+
+		gg.dispose();
+
+		repaint();
+		win.recalc();
+	}
+
+	public void mouseClicked(MouseEvent e) {
+	}
+
+	public void mousePressed(MouseEvent e) {
+		if (e.getButton() == e.BUTTON1) {
+			addMouseMotionListener(this);
+			drawPaint(e.getX(), e.getY());
+		}
+	}
+
+	public void mouseReleased(MouseEvent e) {
+		if (e.getButton() == e.BUTTON1) {
+			removeMouseMotionListener(this);
+			//drawPaint(e.getX(), e.getY());
+		}
+	}
+
+	public void mouseEntered(MouseEvent e) {
+	}
+
+	public void mouseExited(MouseEvent e) {
+	}
+
+	public void mouseDragged(MouseEvent e) {
+		drawPaint(e.getX(), e.getY());
+	}
+
+	public void mouseMoved(MouseEvent e) {
+	}
+}