* To execute this kernel, first create a new instance of it and then call <code>execute(int globalSize)</code>.
* To execute this kernel, first create a new instance of it and then call <code>execute(Range _range)</code>.
* <p>
* <blockquote><pre>
* int[] values = new int[1024];
* // fill values array
* Range range = Range.create(values.length); // create a range 0..1024
* SquareKernel kernel = new SquareKernel(values);
* kernel.execute(values.length);
* kernel.execute(range);
* </pre></blockquote>
* <p>
* When <code>execute()</code> returns, all the executions of Kernel.run() have completed and the results are available in the <code>squares</code> array.
* When <code>execute(Range)</code> returns, all the executions of <code>Kernel.run()</code> have completed and the results are available in the <code>squares</code> array.
"Kernel.globalBarrier() has been deprecated. It was based an incorrect understanding of OpenCL functionality.");
}
...
...
@@ -1441,23 +1570,38 @@ public abstract class Kernel implements Cloneable{
}
/**
* Start execution of <code>globalSize</code> kernels.
* Start execution of <code>_range</code> kernels.
* <p>
* When <code>kernel.execute(globalSize)</code> is invoked, Aparapi will schedule the execution of <code>globalSize</code> kernels. If the execution mode is GPU then
* the kernels will execute as OpenCL code on the GPU device. Otherwise, if the mode is JTP, the kernels will execute as a pool of Java threads on the CPU.
* <p>
* @param _globalSize The number of Kernels that we would like to initiate.
* @param range The number of Kernels that we would like to initiate.
* @returnThe Kernel instance (this) so we can chain calls to put(arr).execute(range).get(arr)
*
*/
publicsynchronizedKernelexecute(Range_range){
return(execute(_range,1));
}
/**
* Start execution of <code>_range</code> kernels.
* <p>
* When <code>kernel.execute(_range)</code> is invoked, Aparapi will schedule the execution of <code>_range</code> kernels. If the execution mode is GPU then
* the kernels will execute as OpenCL code on the GPU device. Otherwise, if the mode is JTP, the kernels will execute as a pool of Java threads on the CPU.
* <p>
* Since adding the new <code>Range class</code> this method offers backward compatibility and merely defers to <code> return (execute(Range.create(_range), 1));</code>.
* @param _range The number of Kernels that we would like to initiate.
* @returnThe Kernel instance (this) so we can chain calls to put(arr).execute(range).get(arr)
*
*/
publicsynchronizedKernelexecute(int_globalSize){
return(execute(_globalSize,1));
publicsynchronizedKernelexecute(int_range){
return(execute(Range.create(_range),1));
}
/**
* Start execution of <code>_passes</code> iterations of <code>globalSize</code> kernels.
* Start execution of <code>_passes</code> iterations of <code>_range</code> kernels.
* <p>
* When <code>kernel.execute(globalSize, passes)</code> is invoked, Aparapi will schedule the execution of <code>globalSize</code> kernels. If the execution mode is GPU then
* When <code>kernel.execute(_range, _passes)</code> is invoked, Aparapi will schedule the execution of <code>_reange</code> kernels. If the execution mode is GPU then
* the kernels will execute as OpenCL code on the GPU device. Otherwise, if the mode is JTP, the kernels will execute as a pool of Java threads on the CPU.
* <p>
* @param _globalSize The number of Kernels that we would like to initiate.
...
...
@@ -1465,8 +1609,23 @@ public abstract class Kernel implements Cloneable{
* @return The Kernel instance (this) so we can chain calls to put(arr).execute(range).get(arr)
* Start execution of <code>_passes</code> iterations over the <code>_range</code> of kernels.
* <p>
* When <code>kernel.execute(_range)</code> is invoked, Aparapi will schedule the execution of <code>_range</code> kernels. If the execution mode is GPU then
* the kernels will execute as OpenCL code on the GPU device. Otherwise, if the mode is JTP, the kernels will execute as a pool of Java threads on the CPU.
* <p>
* Since adding the new <code>Range class</code> this method offers backward compatibility and merely defers to <code> return (execute(Range.create(_range), 1));</code>.
* @param _range The number of Kernels that we would like to initiate.
* @returnThe Kernel instance (this) so we can chain calls to put(arr).execute(range).get(arr)
