Array Block and Cyclic Partitioning (OpenCL Kernel)

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

KEY CONCEPTS: Kernel Optimization, Array Partitioning, Block Partition, Cyclic Partition

KEYWORDS: xcl_array_partition, cyclic, block

This example demonstrates how to use array block and cyclic partitioning to improve the performance of the kernel. Matrix multiplication is performed in this example which would require repeated access to rows of former matrix and columns of latter. Array can be partitioned across different dimensions to reduce the latency of these transfers.

xcl_array_partition attribute is used to partition an array into multiple smaller arrays 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 untill 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 own read/write ports.

int A[MAX_DIM * MAX_DIM] __attribute__((xcl_array_partition(cyclic, MAX_DIM, 1)));
int B[MAX_DIM * MAX_DIM] __attribute__((xcl_array_partition(block, MAX_DIM, 1)));

EXCLUDED PLATFORMS:

  • Embedded ZC702

  • All NoDMA Platforms, i.e u50 nodma etc

  • Samsung U.2 SmartSSD

  • Versal DFX platform

  • Alveo U200

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_partition_cyclicblock <matmul XCLBIN>