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Poster: implications of merging phases on scalability of multi-core architectures
Manivannan, Madhavan; Juurlink, Ben; Stenstrom, Per
Amdahl's Law estimates parallel applications with negligible serial sections to potentially scale to many cores. However, due to merging phases in data mining applications, the serial sections do not remain constant. We extend Amdahl's model to accommodate this and establish that Amdahl's Law can overestimate the scalability offered by symmetric and asymmetric architectures for such applications. Implications: 1) A better use of the chip area is for fewer and hence more capable cores rather than simply increasing the number of cores for symmetric and asymmetric architectures and 2) The performance potential of asymmetric over symmetric multi-core architectures is limited for such applications.
Published in: Proceedings of the International Conference on Supercomputing, 10.1145/1995896.1995963, Association for Computing Machinery (ACM)
