In-FPGA Instrumentation Framework for OpenCL-Based Designs

被引:2
|
作者
Bensalem, Hachem [1 ]
Blaquiere, Yves [1 ]
Savaria, Yvon [2 ]
机构
[1] Ecole Technol Super, Dept Elect Engn, Montreal, PQ H3C 1K3, Canada
[2] Polytech Montreal, Dept Elect Engn, Montreal, PQ H3T 1J4, Canada
来源
IEEE ACCESS | 2020年 / 8卷 / 08期
基金
加拿大自然科学与工程研究理事会;
关键词
Field programmable gate arrays; Instruments; Tools; Kernel; Debugging; Hardware; Benchmark testing; OpenCL; FPGA; instrumentation; high-performance reconfigurable computing; HLS; timing performance;
D O I
10.1109/ACCESS.2020.3040081
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The productivity achieved when developing applications on high-performance reconfigurable heterogeneous computing (HPRHC) systems is increased by using the Open Computing Language (OpenCL). However, the hardware produced by OpenCL compilers in field-programmable gate arrays (FPGAs) can result in severe performance bottlenecks that are challenging to solve. The problem is compounded by the fact that the generated netlist details are disorganized, making them mostly unreadable and only partially visible to designers. This paper proposes an in-FPGA instrumentation method and a new framework for extracting the FPGA-cycle-accurate timing performances of OpenCL-based designs. The results clearly show that the chosen execution model for OpenCL-based designs strongly affects the timing performance when it is not properly implemented. Our framework is implemented on an HPRHC platform that contains a CPU and two Arria10 FPGAs, and it is evaluated with a wide variety of benchmarks with different complexities. After testing on the reported benchmarks, the average logic overhead for one inserted instrument is 0.2 % of the total amount of adaptive look-up tables (ALUTs) and 0.1 % of the total registers in an FPGA. This resource utilization is between 1.5 and six times lower than those reported in the best previously published works. The scalability of the framework is also evaluated by inserting up to 50 instruments. The experimental results show that the average logic utilization per instrument is 0.19 % of the ALUTs and 0.17 % of the registers in the FPGA when 50 instruments are inserted.
引用
收藏
页码:212979 / 212994
页数:16
相关论文
共 50 条
  • [31] A Study of Data Partitioning on OpenCL-based FPGAs
    Wang, Zeke
    He, Bingsheng
    Zhang, Wei
    2015 25TH INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE LOGIC AND APPLICATIONS, 2015,
  • [32] An Automatic Conversion Tool for Caffe Neural Network Configuration oriented to OpenCL-based FPGA Platforms
    Wang, Li
    Zhao, Yaqian
    Li, Xuelei
    PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019), 2019, : 195 - 198
  • [33] Relational Query Processing on OpenCL-based FPGAs
    Wang, Zeke
    Paul, Johns
    Ntu, Hui Yan Cheah
    He, Bingsheng
    Zhang, Wei
    2016 26TH INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE LOGIC AND APPLICATIONS (FPL), 2016,
  • [34] Unified OpenCL Integration Methodology for FPGA Designs
    Leppanen, Topi
    Mousouliotis, Panagiotis
    Keramidas, Georgios
    Multanen, Joonas
    Jaaskeleainen, Pekka
    2021 IEEE NORDIC CIRCUITS AND SYSTEMS CONFERENCE (NORCAS), 2021,
  • [35] An OpenCL-based software framework for a heterogeneous multicore architecture on Zynq-7000 SoC
    Miyazaki T.
    Takai S.
    Taniguchi I.
    Tomiyama H.
    IPSJ Transactions on System LSI Design Methodology, 2019, 12 : 46 - 49
  • [36] A Portable OpenCL-based Approach for SVMs in GPU
    Cagnini, Henry E. L.
    Winck, Ana T.
    Barros, Rodrigo C.
    2015 BRAZILIAN CONFERENCE ON INTELLIGENT SYSTEMS (BRACIS 2015), 2015, : 198 - 203
  • [37] OpenCL-Based Performance Enhancement of Model Transformations
    Fekete, Tamas
    Mezei, Gergely
    IWOCL'18: PROCEEDINGS OF THE INTERNATIONAL WORKSHOP ON OPENCL, 2018, : 89 - 90
  • [38] Introduction of an OpenCL-Based Model Transformation Engine
    Fekete, Tamas
    Mezei, Gergely
    SOFTWARE TECHNOLOGIES: APPLICATIONS AND FOUNDATIONS, STAF 2017, 2018, 10748 : 14 - 19
  • [39] Using OpenCL to Rapidly Prototype FPGA Designs
    Wang, Kui
    Nurmi, Jari
    2016 2ND IEEE NORDIC CIRCUITS AND SYSTEMS CONFERENCE (NORCAS), 2016,
  • [40] Optimization Techniques for OpenCL-based Linear Algebra Routines
    Kozacik, Stephen
    Fox, Paul
    Humphrey, John
    Kuller, Aryeh
    Kelmelis, Eric
    Prather, Dennis W.
    MODELING AND SIMULATION FOR DEFENSE SYSTEMS AND APPLICATIONS IX, 2014, 9095