Array Partitioning (OpenCL Kernel)

This example shows how to use array partitioning to improve performance of a kernel

KEY CONCEPTS: Kernel Optimization, Array Partition

KEYWORDS: xcl_array_partition, complete

This example demonstrates how array partition in OpenCL kernels can improve the performance of an application. Operations like matrix multiplication require multiple accesses to data in memory for a single iteration. Two kernels are executed, matmul_partition with the array partitions and matmul without the array partitions and performance is compared.

xcl_array_partition is used to partition an array into multiple smaller arrays or memories with more number of ports for read and write operations. This results in improved throughput of the design.

Arrays can be partitioned in three ways, cyclic where elements are put into smaller arrays one by one in the interleaved manner until the whole array is partitioned, block where elements are put into smaller arrays from continuous blocks of original array and complete where array is decomposed into individual elements each having its own read/write ports.

int B[MAX_SIZE][MAX_SIZE] __attribute__((xcl_array_partition(complete, 2)));

int C[MAX_SIZE][MAX_SIZE] __attribute__((xcl_array_partition(complete, 2)));

int temp_sum[MAX_SIZE]    __attribute__((xcl_array_partition(complete, 1)));

EXCLUDED PLATFORMS:

• All NoDMA Platforms, i.e u50 nodma etc

DESIGN FILES

Application code is located in the src directory. Accelerator binary files will be compiled to the xclbin directory. The xclbin directory is required by the Makefile and its contents will be filled during compilation. A listing of all the files in this example is shown below

src/host.cpp
src/matmul.cl

Access these files in the github repo by clicking here.

COMMAND LINE ARGUMENTS

Once the environment has been configured, the application can be executed by

./cl_array_partition <matmul XCLBIN>