2012Unpublished venueRequires access

A SIMD Parallelization Method for an Application for LSI Logic Simulation

Natsuki Kai, Ryoji Nishinohara, Hiroshi Koide

Open publisher page 3 citations

Abstract

This paper proposes and evaluates a SIMD parallelization method for an application for LSI logic simulation. The proposal method converts a net list into a parallel and distributed program code so as to make the code SIMD parallelized. As experiments to evaluate our proposal method, tasks in SIMD arithmetic logical units on Cell/B.E., and we measure that elapsed time. In the results of experiments, over 80% tasks are SIMD parallelized and the program with a shuffle instruction and a SIMD instruction reduces computation time by over 90%.

About this research paper

What this paper is about

This paper proposes and evaluates a SIMD parallelization method for an application for LSI logic simulation. The proposal method converts a net list into a parallel and distributed program code so as to make the code SIMD parallelized. As experiments to evaluate our proposal method, tasks in SIMD arithmetic logical units on Cell/B.E., and we measure that elapsed time. In the results of experiments, over 80% tasks are SIMD parallelized and the program with a shuffle instruction and a SIMD instruction reduces computation time by over 90%.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper proposes and evaluates a SIMD parallelization method for an application for LSI logic simulation. The proposal method converts a net list into a parallel and distributed program code so as to make the code SIMD parallelized. As experiments to evaluate our proposal method, tasks in SIMD arithmetic logical units on Cell/B.E., and we measure that elapsed time. In the results of experiments, over 80% tasks are SIMD parallelized and the program with a shuffle instruction and a SIMD instruction reduces computation time by over 90%.

Key concepts: SIMD, Parallel computing, Computer science, Code (set theory), Computation, Programming language, Set (abstract data type)

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