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  1. Proceedings of the 3rd International Workshop on Multicore Software Engineering (IWMSE '10)
  2. Predicting multi-core performance: a case study using Solaris containers
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Automatic parallelization of programming languages: past, present and future
Writing concurrent desktop applications in an actor-based programming model
Towards efficient video compression using scalable vector graphics on the Cell/B.E.
IMUnit: improved multithreaded unit testing
JCudaMP: OpenMP/Java on CUDA
Enabling multi-core based monitoring and fault tolerance in C++/Java
You are not alone: breaking transaction isolation
Predicting multi-core performance: a case study using Solaris containers
Concurrency design patterns, software quality attributes and their tactics
Challenges in operating-systems reengineering for many cores
The correlation between parallel patterns and multi-core benchmarks
Dynamic reconfiguration in NoC-based MPSoCs in the avionics domain

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Predicting multi-core performance: a case study using Solaris containers

Content Provider ACM Digital Library
Author Siami Namin, Akbar Tomar, Pulkit Sridharan, Mohan
Abstract Multi-core technology is an emerging hardware trend that provides significant capabilities for computationally expensive applications. However, it also demands a paradigm shift in the software industry, Software developers need to think about the best distribution of software components across the available CPUs, and trade-off the computational efficiency against the cost of re-structuring the standard sequential execution of software. The relationship between the measured performance and the corresponding parameters such as the number of threads and CPUs remains an interesting open problem, especially since it is a challenge to conduct controlled experiments. This paper reports a case study on the use of Solaris containers to control the assignment of threads to the available CPUs in a set of applications. We model the performance as a function of the number of threads, the number of CPUs and the type of program. We use two different modeling strategies: linear regression and Neural Networks, which are applied to the well-established Java Grande benchmark. We observe that there is a nonlinear relationship between these parameters and the associated performance. In addition, neural network models are observed to be consistently better at estimating the performance over a range of parameter values. The results reported in this paper can therefore be used to suitably re-structure software programs to fully utilize the available resources.
Starting Page 18
Ending Page 25
Page Count 8
File Format PDF
ISBN 9781605589640
DOI 10.1145/1808954.1808960
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2010-05-01
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Multi-core performance Neural networks Regression Solaris containers
Content Type Text
Resource Type Article
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