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

@InProceedings{10.1007/978-3-319-98521-3_7,
author="Watanabe, Yutaka
and Lee, Jinpil
and Boku, Taisuke
and Sato, Mitsuhisa",
editor="de Supinski, Bronis R.
and Valero-Lara, Pedro
and Martorell, Xavier
and Mateo Bellido, Sergi
and Labarta, Jesus",
title="Trade-Off of Offloading to FPGA in OpenMP Task-Based Programming",
booktitle="Evolving OpenMP for Evolving Architectures",
year="2018",
publisher="Springer International Publishing",
address="Cham",
pages="96--110",
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.",
isbn="978-3-319-98521-3"
}