Analyzing Performance and Power of Multicore Architecture Using Multithreaded Iterative Solver

Ingyu Lee

doi:10.3844/jcssp.2010.406.412

Abstract

Problem statement: Scientific modeling and simulations have been popularly used with experiments and theoretical analysis in science and engineering communities. Approach: Consequently, computational demands are growing exponentially to afford large scale modeling and simulations. Results: As a result, multicore computing architectures had been proposed and several products are already available. However, we do not have a proper study on the performance, power and thermal issues of real science and engineering problems bec ause software, which takes advantage of multicore architecture, is not available. Conclusion/Recommendations: In this study, we explored the performance and power characteristics of scientific algorithms on multicore architectures using a multithreaded version of sparse iterative linear so lver, named mtCG, with real scientific application problems.

Highlights

Computational modeling and simulations have been popularly used in science and engineering community to describe and understand complex phenomena instead of expensive or dangerous experiments such as drug design, global climate simulation, radiation simulation, crash testing aerodynamics and combustion (Heath, 2002)
We do not have a proper study on performance, power and thermal issues on multicore processors since the lack of scientific applications which benefits from multicore architectures
Several researches to characterize the performance of multicore architecture have been done with multiprogramming or loop level parallel benchmark programs (Jaleel et al, 2006; Li et al, 2005; Manjikian, 2001)

Summary

Introduction

Computational modeling and simulations have been popularly used in science and engineering community to describe and understand complex phenomena instead of expensive or dangerous experiments such as drug design, global climate simulation, radiation simulation, crash testing aerodynamics and combustion (Heath, 2002) These modeling and simulations are usually represented as Partial Differential Equations (PDEs) which require meshes and sparse matrices. High performance computing community increases the number of transistors in a given area to improve performance The latter meets physical limitation and generates new problems such as power consumption and thermal issues. Several researches have been done with SPEC to measure the performance of multicore architecture (Li et al, 2005; Manjikian, 2001) These benchmark programs only support a single thread. Even with OpenMP version of SPEC supports loop level parallelism which is different with general multithreaded programs which have task level parallelism

Methods

Results

Conclusion