Exploring the random network of hodgkin and huxley neurons with exponential synaptic conductances on opencl FPGA platform

Zheming Jin; Hal Finkel

doi:10.1109/FCCM.2019.00057

Exploring the random network of hodgkin and huxley neurons with exponential synaptic conductances on opencl FPGA platform

Zheming Jin
, Hal Finkel

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

We choose a random network of Hodgkin-Huxley (HH) neurons with exponential synaptic conductance as a study of accelerating the simulation of networks of spiking neurons on an FPGA. Focused on the conductance-based HH (COBAHH) 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 kernel 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, and an NVIDIA Tesla P100 GPU. FPGAs are promising for the simulation of spiking neuron network.

Original language	English
Title of host publication	Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	316
Number of pages	1
ISBN (Electronic)	9781728111315
DOIs	https://doi.org/10.1109/FCCM.2019.00057
State	Published - Apr 2019
Externally published	Yes
Event	27th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019 - San Diego, United States Duration: Apr 28 2019 → May 1 2019

Publication series

Name	Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019

Conference

Conference	27th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019
Country/Territory	United States
City	San Diego
Period	04/28/19 → 05/1/19

Funding

The research was supported by the U.S. Department of Energy, Office of Science, under contract DE-AC02-06CH11357 and made use of the Argonne Leadership Computing Facility, a DOE Office of Science User Facility XXX-X-XXXX-XXXX-X/XX/$XX.00 ©20XX IEEE

Keywords

FPGA
OpenCL
Spiking neuron network
simulation

Access to Document

10.1109/FCCM.2019.00057

Cite this

Jin, Z., & Finkel, H. (2019). Exploring the random network of hodgkin and huxley neurons with exponential synaptic conductances on opencl FPGA platform. In Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019 (pp. 316). Article 8735516 (Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FCCM.2019.00057

Jin, Zheming ; Finkel, Hal. / Exploring the random network of hodgkin and huxley neurons with exponential synaptic conductances on opencl FPGA platform. Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 316 (Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019).

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title = "Exploring the random network of hodgkin and huxley neurons with exponential synaptic conductances on opencl FPGA platform",

abstract = "We choose a random network of Hodgkin-Huxley (HH) neurons with exponential synaptic conductance as a study of accelerating the simulation of networks of spiking neurons on an FPGA. Focused on the conductance-based HH (COBAHH) 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 kernel 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, and an NVIDIA Tesla P100 GPU. FPGAs are promising for the simulation of spiking neuron network.",

keywords = "FPGA, OpenCL, Spiking neuron network, simulation",

author = "Zheming Jin and Hal Finkel",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 27th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019 ; Conference date: 28-04-2019 Through 01-05-2019",

year = "2019",

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doi = "10.1109/FCCM.2019.00057",

language = "English",

series = "Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Jin, Z & Finkel, H 2019, Exploring the random network of hodgkin and huxley neurons with exponential synaptic conductances on opencl FPGA platform. in Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019., 8735516, Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019, Institute of Electrical and Electronics Engineers Inc., pp. 316, 27th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019, San Diego, United States, 04/28/19. https://doi.org/10.1109/FCCM.2019.00057

Exploring the random network of hodgkin and huxley neurons with exponential synaptic conductances on opencl FPGA platform. / Jin, Zheming; Finkel, Hal.
Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 316 8735516 (Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - We choose a random network of Hodgkin-Huxley (HH) neurons with exponential synaptic conductance as a study of accelerating the simulation of networks of spiking neurons on an FPGA. Focused on the conductance-based HH (COBAHH) 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 kernel 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, and an NVIDIA Tesla P100 GPU. FPGAs are promising for the simulation of spiking neuron network.

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Jin Z, Finkel H. Exploring the random network of hodgkin and huxley neurons with exponential synaptic conductances on opencl FPGA platform. In Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 316. 8735516. (Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019). doi: 10.1109/FCCM.2019.00057

Exploring the random network of hodgkin and huxley neurons with exponential synaptic conductances on opencl FPGA platform

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