Fully Parallel Implementation of Digital Memcomputing on FPGA

We present a fully parallel digital memcomputing solver implemented on a field-programmable gate array (FPGA) board. For this purpose, we have designed an FPGA code that solves the ordinary differential equations associated with digital memcomputing in parallel. A feature of the code is the use of only integer-type variables and integer constants to enhance optimization. Consequently, each integration step in our solver is executed in 96 ns. This method was utilized for difficult instances of the Boolean satisfiability (SAT) problem close to a phase transition, involving up to about 150 variables. Our results demonstrate that the parallel implementation reduces the scaling exponent by about 1 compared to a sequential C++ code on a standard computer. Additionally, compared to C++ code, we observed a time-to-solution advantage of about three orders of magnitude. Given the limitations of FPGA resources, the current implementation of digital memcomputing will be especially useful for solving compact but challenging problems.

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Publication Details

Published
2024-08-11
DOI
https://doi.org/10.1109/mwscas60917.2024.10658882
Citations
2
Primary Topic
Interconnection Networks and Systems
Type
article
Field-Weighted Citation Impact
0.70

Funders

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article

Fully Parallel Implementation of Digital Memcomputing on FPGA

Yuriy V. Pershin, Dyk Chung Nguyen
2 citations
Interconnection Networks and Systems
0.70
article

Fully Parallel Implementation of Digital Memcomputing on FPGA

Yuriy V. Pershin, Dyk Chung Nguyen
article en
2 citations

Abstract

We present a fully parallel digital memcomputing solver implemented on a field-programmable gate array (FPGA) board. For this purpose, we have designed an FPGA code that solves the ordinary differential equations associated with digital memcomputing in parallel. A feature of the code is the use of only integer-type variables and integer constants to enhance optimization. Consequently, each integration step in our solver is executed in 96 ns. This method was utilized for difficult instances of the Boolean satisfiability (SAT) problem close to a phase transition, involving up to about 150 variables. Our results demonstrate that the parallel implementation reduces the scaling exponent by about 1 compared to a sequential C++ code on a standard computer. Additionally, compared to C++ code, we observed a time-to-solution advantage of about three orders of magnitude. Given the limitations of FPGA resources, the current implementation of digital memcomputing will be especially useful for solving compact but challenging problems.

University of South Carolina (US)
National Science Foundation
Openalex Percentile: Top 28%
Interconnection Networks and Systems
0.70
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