What is Aparapi?

Aparapi allows Java developers to take advantage of the compute power of GPU and APU devices by executing data parallel code fragments on the GPU rather than being confined to the local CPU. It does this by converting Java bytecode to OpenCL at runtime and executing on the GPU, if for any reason Aparapi can't execute on the GPU it will execute in a Java thread pool.

We like to think that for the appropriate workload this extends Java's 'Write Once Run Anywhere' to include GPU devices.

With Aparapi we can take a sequential loop such as this (which adds each element from inA and inB arrays and puts the result in result).

final float inA[] = .... // get a float array of data from somewhere
final float inB[] = .... // get a float array of data from somewhere (inA.length==inB.length)
final float result = new float[inA.length];

for (int i=0; i<array.length; i++){
    result[i]=intA[i]+inB[i];
}

And refactor the sequential loop to the following form:

Kernel kernel = new Kernel(){
   @Override public void run(){
      int i= getGlobalId();
      result[i]=intA[i]+inB[i];
   }
};
Range range = Range.create(result.length); 
kernel.execute(range);

In the above code we extend com.amd.aparapi.Kernel base class and override the Kernel.run() method to express our data parallel algorithm. We initiate the execution of the Kernel(over a specific range 0..results.length) using Kernel.execute(range).

If you would like to download and try Aparapi follow the 'Downloads' link above and read the UsersGuide, alternatively if you would like to contribute or access the code you can check out the code from the SVN repository above and jump right in by reading the DevelopersGuide pages.

Useful links

Wiki Pages

User’s Guide UsersGuide
Developer’s Guide DevelopersGuide, for developers who want to build Aparapi or contribute to the project
Frequently Asked Questions FrequentlyAskedQuestions