Trade-Off of Offloading to FPGA in OpenMP Task-Based Programming

Abstract

In High-Performance Computing (HPC), Field Programmable Gate Array (FPGA) is attracting increased attention as an accelerator because its performance has been dramatically improved in recent years. On the other hand, task-based programming recently supported in OpenMP 4.0 enables to expose much parallelism by executing several tasks of the program in the form of a task graph. To accelerate the task-based parallel program by FPGA, it is useful for some dominant tasks frequently executed in parallel to be offloaded to FPGA as an asynchronous FPGA task. We present a performance optimization based on the trade-off between the kernel size and the number of asynchronously executed kernels in parallel in OpenMP task-based programming with FPGA tasks to make use of FPGA hardware resources efficiently. Since a “program” for FPGA is directly converted into the hardware, the hardware resource limitation raises a new issue in optimization on which and how to offload a task to FPGA. Taking task-based block Cholesky factorization as a motivating example, we present the trade-off on how to offload dominant “GEMM” task frequently executed in parallel in the execution of the task-graph. We found that under the limitation of the hardware resource, multiple small kernels are better than a single big high-performance kernel because of higher throughput and higher kernel frequency.