initial import of jocl-demos project.

added first demo: HelloJOCL.

2 files changed, 109 insertions, 0 deletions

diff --git a/src/com/mbien/opencl/demos/hellojocl/HelloJOCL.java b/src/com/mbien/opencl/demos/hellojocl/HelloJOCL.java
new file mode 100644
index 0000000..31cbdef
--- /dev/null
+++ b/src/com/mbien/opencl/demos/hellojocl/HelloJOCL.java
@@ -0,0 +1,97 @@
+package com.mbien.opencl.demos.hellojocl;
+
+import com.mbien.opencl.CL;
+import com.mbien.opencl.CLBuffer;
+import com.mbien.opencl.CLCommandQueue;
+import com.mbien.opencl.CLContext;
+import com.mbien.opencl.CLKernel;
+import com.mbien.opencl.CLProgram;
+import java.io.IOException;
+import java.nio.ByteBuffer;
+import java.util.Random;
+
+import static java.lang.System.*;
+import static com.sun.gluegen.runtime.BufferFactory.*;
+
+/**
+ * Hello Java OpenCL example. Adds all elements of buffer A to buffer B
+ * and stores the result in buffer C.<br/>
+ * Sample was inspired by the Nvidia VectorAdd example written in C/C++
+ * which is bundled in the Nvidia OpenCL SDK.
+ * @author Michael Bien
+ */
+public class HelloJOCL {
+
+    public static void main(String[] args) throws IOException {
+        
+        int elementCount = 11444777;                                // Length of float arrays to process
+        int localWorkSize = 256;                                    // set and log Global and Local work size dimensions
+        int globalWorkSize = roundUp(localWorkSize, elementCount);  // rounded up to the nearest multiple of the localWorkSize
+
+        // set up
+        CLContext context = CLContext.create();
+
+        CLProgram program = context.createProgram(HelloJOCL.class.getResourceAsStream("VectorAdd.cl")).build();
+
+        CLBuffer clBufferA = context.createBuffer(CL.CL_MEM_READ_ONLY,  globalWorkSize*SIZEOF_INT);
+        CLBuffer clBufferB = context.createBuffer(CL.CL_MEM_READ_ONLY,  globalWorkSize*SIZEOF_INT);
+        CLBuffer clBufferC = context.createBuffer(CL.CL_MEM_WRITE_ONLY, globalWorkSize*SIZEOF_INT);
+
+        out.println("used device memory: "
+            + (clBufferA.buffer.capacity()+clBufferB.buffer.capacity()+clBufferC.buffer.capacity())/1000000 +"MB");
+
+        // fill read buffers with random numbers (just to have test data; seed is fixed -> results will not change between).
+        fillBuffer(clBufferA.buffer, 12345);
+        fillBuffer(clBufferB.buffer, 67890);
+
+        // get a reference to the kernel functon with the name 'VectorAdd' and map the buffers to its input parameters.
+        CLKernel kernel = program.getCLKernels().get("VectorAdd");
+        kernel.setArg(0, SIZEOF_LONG, clBufferA)
+              .setArg(1, SIZEOF_LONG, clBufferB)
+              .setArg(2, SIZEOF_LONG, clBufferC)
+              .setArg(3, SIZEOF_INT, elementCount);
+
+        // create command queue on first device.
+        CLCommandQueue queue = context.getCLDevices()[0].createCommandQueue();
+
+        // asynchronous write of data to GPU device, blocking read later to get the computed results back.
+        long time = nanoTime();
+        queue.putWriteBuffer(clBufferA, false)
+             .putWriteBuffer(clBufferB, false)
+             .putNDRangeKernel(kernel, 1, null, new long[]{ globalWorkSize }, new long[]{ localWorkSize })
+             .putReadBuffer(clBufferC, true);
+        time = nanoTime() - time;
+
+        // cleanup all resources associated with this context.
+        context.release();
+
+        // print first few elements of the resulting buffer to the console.
+        out.println("a+b=c results snapshot: ");
+        for(int i = 0; i < 10; i++)
+            out.print(clBufferC.buffer.getInt() + ", ");
+        out.println("...; " + clBufferC.buffer.remaining()/SIZEOF_INT + " more");
+        
+        System.out.println("computation took: "+(time/1000000)+"ms");
+
+    }
+
+    public static final void fillBuffer(ByteBuffer buffer, int seed) {
+
+        Random rnd = new Random(seed);
+
+        while(buffer.remaining() != 0)
+            buffer.putInt(rnd.nextInt());
+
+        buffer.rewind();
+    }
+
+    public static final int roundUp(int groupSize, int globalSize) {
+        int r = globalSize % groupSize;
+        if (r == 0) {
+            return globalSize;
+        } else {
+            return globalSize + groupSize - r;
+        }
+    }
+
+}
diff --git a/src/com/mbien/opencl/demos/hellojocl/VectorAdd.cl b/src/com/mbien/opencl/demos/hellojocl/VectorAdd.cl
new file mode 100644
index 0000000..b53fc41
--- /dev/null
+++ b/src/com/mbien/opencl/demos/hellojocl/VectorAdd.cl
@@ -0,0 +1,12 @@
+
+    // OpenCL Kernel Function for element by element vector addition
+    __kernel void VectorAdd(__global const int* a, __global const int* b, __global int* c, int iNumElements) {
+        // get index into global data array
+        int iGID = get_global_id(0);
+        // bound check (equivalent to the limit on a 'for' loop for standard/serial C code
+        if (iGID >= iNumElements)  {
+            return;
+        }
+        // add the vector elements
+        c[iGID] = a[iGID] + b[iGID];
+    }