[code-reflection] RFR: [feature][HAT] 2D and 3D ranges for the NDRange API [v3]

[Juan Fumero]

> This patch introduces the concept of 2D and 3D ranges. 
> 
> This allows developers to do the following:
> - Accessing 1D, 2D and 3D thread indexing within the kernels. The `KernelContext` API has been extended to do this.
> - Dispatching 1D, 2D and 3D kernels via the `ComputeContext`.
> 
> **IMPORTANT**: This patch has been tested for the OpenCL backend, the CUDA backend generates correct code, but for some reason I can't dispatch it due to CUDA incompatibilities (seems to be orthogonal to this PR). I will investigate this in a separate issue. 
> 
> An example of use is provided in the `matmul/Main.java` class.
> 
> Example of 1D kernel in HAT:
> 
> 
> @CodeReflection
>     public static void matrixMultiplyKernel1D(@RO KernelContext kc, @RO F32Array matrixA, @RO F32Array matrixB, @RW F32Array matrixC, int size) {
>         if (kc.x < kc.maxX) {
>             for (int j = 0; j < size; j++) {
>                 float acc = 0;
>                 for (int k = 0; k < size; k++) {
>                     acc += (matrixA.array(kc.x * size + k) * matrixB.array(k * size + j));
>                 }
>                 matrixC.array(kc.x * size + j, acc);
>             }
>         }
>     }
> 
> 
> Example of a 2D kernel:
> 
> 
> @CodeReflection
>     public static void matrixMultiplyKernel2D(@RO KernelContext kc, @RO F32Array matrixA, @RO F32Array matrixB, @RW F32Array matrixC, int size) {
>         if (kc.x < kc.maxX) {
>             if (kc.y < kc.maxY) {
>                 float acc = 0;
>                 for (int k = 0; k < size; k++) {
>                     acc += (matrixA.array(kc.x * size + k) * matrixB.array(k * size + kc.y));
>                 }
>                 matrixC.array(kc.x * size + kc.y, acc);
>             }
>         }
>     }
> 
> 
> How to dispatch?
> 
> The dispatcher now has more parameters to setup the max thread size for each dimension. In the case of a 2D:
> 
> 
> computeContext.dispatchKernel(maxX, maxY,
>     kernelContext -> matrixMultiplyKernel2D(kernelContext, matrixA, matrixB, matrixC, size)
> );
> 
> 
> ### How to test this patch?
> 
> I extended the test-case for the matrix multiplication. 
> 
> Run with 1D:
> 
> 
> HAT=SHOW_CODE java @hat/run ffi-opencl matmul 1D
> 
> 
> Run with 2D
> 
> 
> HAT=SHOW_CODE java @hat/run ffi-opencl matmul 2D

Juan Fumero has updated the pull request with a new target base due to a merge or a rebase. The incremental webrev excludes the unrelated changes brought in by the merge/rebase. The pull request contains three additional commits since the last revision:

 - Merge branch 'code-reflection' into dev/ndrange
 - [hat] launch exception if more than 3D configuration is set
 - [feature] 2D and 3D ranges for the NDRange API
   
   This patch introduces the concept of 2D and 3D ranges.
   This allows developers to:
   - Access 1D, 2D and 3D thread indexing within the kernels.
     The KernelContext API has been extended.
   - Dispatch 1D, 2D and 3D kernels via the ComputeContext.
   
   An example of use is provided in the matmul/Main.java class.

-------------

Changes:
  - all: https://git.openjdk.org/babylon/pull/496/files
  - new: https://git.openjdk.org/babylon/pull/496/files/0bb26536..f69b190b

Webrevs:
 - full: https://webrevs.openjdk.org/?repo=babylon&pr=496&range=02
 - incr: https://webrevs.openjdk.org/?repo=babylon&pr=496&range=01-02

  Stats: 386 lines in 9 files changed: 298 ins; 78 del; 10 mod
  Patch: https://git.openjdk.org/babylon/pull/496.diff
  Fetch: git fetch https://git.openjdk.org/babylon.git pull/496/head:pull/496

PR: https://git.openjdk.org/babylon/pull/496