Simulation of random network of Hodgkin and Huxley neurons with exponential synaptic conductances on an FPGA platform

Zheming Jin, Hal Finkel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Field-programmable gate arrays (FPGAs) are becoming a promising choice as a heterogeneous computing component when floating-point optimized architectures are added to the current FPGAs. The maturing high-level synthesis tools offer a streamlined design flow for researchers to develop a parallel application using a high-level language on FPGAs. In this paper, we choose a random network of Hodgkin–Huxley (HH) neurons with exponential synaptic conductance to evaluate the performance of the simulation of networks of spiking neurons on an FPGA. Focused on the conductance-based HH benchmark, we execute the benchmark on a general-purpose simulator for spiking neural networks, identify a computationally intensive kernel in the generated C++ code, convert the kernel to a portable OpenCL kernel, and describe the optimizations which can reduce the resource utilizations and improve the kernel performance. We evaluate the kernel on an Intel Arria 10 based FPGA platform, an Intel Xeon 16-core CPU, an Intel Xeon 4-core low-power processor with a CPU and a GPU integrated on the same chip, and an NVIDIA Tesla P100 discrete GPU. For the kernel execution time, the Arria 10 GX1150 FPGA is 2X and 3X faster than the two CPUs, but it is 2.5X and 4.8X slower than the two GPUs, respectively. The FPGA consumes the least power, but its performance per watt is 1.56X and 1.96X lower than the two GPUs, respectively.

Original languageEnglish
Title of host publicationACM-BCB 2019 - Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
PublisherAssociation for Computing Machinery, Inc
Pages653-657
Number of pages5
ISBN (Electronic)9781450366663
DOIs
StatePublished - Sep 4 2019
Externally publishedYes
Event10th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2019 - Niagara Falls, United States
Duration: Sep 7 2019Sep 10 2019

Publication series

NameACM-BCB 2019 - Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics

Conference

Conference10th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2019
Country/TerritoryUnited States
CityNiagara Falls
Period09/7/1909/10/19

Keywords

  • CPU
  • FPGA
  • GPU
  • OpenCL
  • Simulation
  • Spiking neural network

Fingerprint

Dive into the research topics of 'Simulation of random network of Hodgkin and Huxley neurons with exponential synaptic conductances on an FPGA platform'. Together they form a unique fingerprint.

Cite this