Abstract
Processing-in-Memory systems that combine processing power and system memory chips present unique algorithmic challenges in the search for optimal system efficiency. This paper presents a tool which allows algorithm designers to quickly understand the performance of their application on a parameterized, highly configurable PIM system model. This tool is not a cycle-accurate simulator, which can take days to run, but a fast and flexible performance estimation tool. Some of the results from our performance analysis of 2-D FFT and biConjugate gradient are shown, and possible ways of using the tool to improve the effectiveness of PIM applications and architectures are given.
Cite
CITATION STYLE
Baker, Z. K., & Prasanna, V. K. (2002). Performance modeling and interpretive simulation of PIM architectures and applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2400, pp. 157–161). Springer Verlag. https://doi.org/10.1007/3-540-45706-2_19
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