Performance Analysis of Adaptive Resource Allocation Scheme for OpenCL-based FPGA Virtualization System

被引:1
|
作者
Le, Duc-Canh [1 ]
Oh, Eun-Young [2 ,3 ]
Cho, Gyu-Sang [1 ]
Lee, Kyung-Chae [1 ]
Kim, Sung-Hyun [1 ]
Youn, Chan-Hyun [1 ]
机构
[1] Korea Adv Inst Sci & Technol, Sch Elect Engn, Daejeon, South Korea
[2] Korea Telecom, Cloud Platform Dept, Seoul, South Korea
[3] Korea Adv Inst Sci & Technol, Daejeon, South Korea
来源
2019 10TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE (ICTC): ICT CONVERGENCE LEADING THE AUTONOMOUS FUTURE | 2019年
关键词
FPGA virtualization; FPGA sharing; FPGA as a Service (FaaS); Reconfigurable Computing;
D O I
10.1109/ictc46691.2019.8939758
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A recent advance in the performance of FPGA devices is creating an industry trend toward an energy efficient, high-performance computing paradigm. In response to this trend, major cloud providers have begun to offer FPGA-as-a-Service (FaaS). Unfortunately, most of the current FPGA services and researches are inefficient in resource utilization, that they assign an FPGA per process which cannot be shared among users. In this paper, we propose a partial reconfiguration (PR) based virtualized FPGA (vFPGA) system with OpenCL compatibility. Moreover, we propose a run-time management system and dynamic resource allocation scheme to efficiently allocate resources in the system. With our system, FPGA resources can be fully utilized and shared by multiple users. Experimental results show that our proposed vFPGA system can accomodate multiple users with high resource utilization and low service latency. We suggest that our system is suitable for the current trend of cloud computing towards the mobile edge computing (MEC) cloud.
引用
收藏
页码:392 / 397
页数:6
相关论文
共 50 条
  • [1] Toward In-System Monitoring of OpenCL-Based Designs on FPGA
    Bensalem, Hachem
    Blaquiere, Yves
    Savaria, Yvon
    2019 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2019,
  • [2] Research on Parallel Architecture of OpenCL-Based FPGA
    Zhang, Yi
    Cai, Ye
    Luo, Qiuming
    SMART COMPUTING AND COMMUNICATION, SMARTCOM 2017, 2018, 10699 : 27 - 38
  • [3] Improving the Performance of OpenCL-based FPGA Accelerator for Convolutional Neural Network
    Zhang, Jialiang
    Li, Jing
    FPGA'17: PROCEEDINGS OF THE 2017 ACM/SIGDA INTERNATIONAL SYMPOSIUM ON FIELD-PROGRAMMABLE GATE ARRAYS, 2017, : 25 - 34
  • [4] Improving the Performance of Whale Optimization Algorithm through OpenCL-Based FPGA Accelerator
    Jiang, Qiangqiang
    Guo, Yuanjun
    Yang, Zhile
    Wang, Zheng
    Yang, Dongsheng
    Zhou, Xianyu
    COMPLEXITY, 2020, 2020
  • [5] In-FPGA Instrumentation Framework for OpenCL-Based Designs
    Bensalem, Hachem
    Blaquiere, Yves
    Savaria, Yvon
    IEEE ACCESS, 2020, 8 (08): : 212979 - 212994
  • [6] Evaluation of an OpenCL-Based FPGA Platform for Particle Filter
    Tatsumi, Shunsuke
    Hariyama, Masanori
    Ikoma, Norikazu
    JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 2016, 20 (05) : 743 - 754
  • [7] OpenCL-based design of an FPGA accelerator for quantum annealing simulation
    Hasitha Muthumala Waidyasooriya
    Masanori Hariyama
    Masamichi J. Miyama
    Masayuki Ohzeki
    The Journal of Supercomputing, 2019, 75 : 5019 - 5039
  • [8] OpenCL-based design of an FPGA accelerator for quantum annealing simulation
    Waidyasooriya, Hasitha Muthumala
    Hariyama, Masanori
    Miyama, Masamichi J.
    Ohzeki, Masayuki
    JOURNAL OF SUPERCOMPUTING, 2019, 75 (08): : 5019 - 5039
  • [9] An OpenCL-Based FPGA Accelerator for Compressed YOLOv2
    Yang, Anrong
    Li, Yuanhui
    Shu, Hongqiao
    Deng, Jianlin
    Ma, Chuanzhao
    Li, Zheng
    Wang, Qigang
    2019 INTERNATIONAL CONFERENCE ON FIELD-PROGRAMMABLE TECHNOLOGY (ICFPT 2019), 2019, : 235 - 238
  • [10] A Scalable OpenCL-Based FPGA Accelerator For YOLOv2
    Xu, Ke
    Wang, Xiaoyun
    Wang, Dong
    2019 27TH IEEE ANNUAL INTERNATIONAL SYMPOSIUM ON FIELD-PROGRAMMABLE CUSTOM COMPUTING MACHINES (FCCM), 2019, : 317 - 317