Year: 2025
Type: article
Abstract: Over the past decades, Field-Programmable Gate Arrays (FPGAs) have become a choice for heterogeneous computing due to their flexibility, energy efficiency, and processing speed. OpenCL is used in FPGA heterogeneous computing for its high-level abstraction and cross-platform compatibility. Previous works have introduced optimization techniques in OpenCL for FPGAs to leverage FPGA-specific advantages. However, the multi-kernel pipeline technique, which can raise throughput and resource utilization, has not performed well. This article presents a CPU+FPGA heterogeneous platform with a novel execution model to optimize multi-kernel pipeline. Firstly, we extend OpenCL by introducing new APIs and additional functions to represent the execution model. Secondly, a hardware-software co-scheduling scheme is employed to manage execution. Thirdly, we design a holistic development flow and toolkit to facilitate the deployment of algorithms on the platform or the integration of RTL IP cores to the OpenCL environment. We validate the platform using a Range Doppler algorithm. The proposed development flow and integrated toolchain enhance the efficiency of integrating traditional RTL IP cores into the OpenCL environment. Experimental results demonstrate that, with a comparable processing speed (averaging 95%) to traditional RTL implementations, the platform successfully establishes the multi-kernel pipelines. Leveraging the multi-kernel pipeline, the platform achieves a significant improvement in multi-frame processing speed compared to traditional OpenCL.
DOI: 10.1145/3744922
Authors: Yuefei Wang, Wendong Mao, Lang Feng, Jin Sha, Zhongfeng Wang
Institutions: Nanjing University, Sun Yat-sen University
Language: English
Subfield: Hardware and Architecture
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Award: G7225354281
OpenAlex ID: W4411456907