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Open Access Publications from the University of California

Apex-Map: A Synthetic Scalable Benchmark Probe to Explore Data Access Performance on Highly Parallel Systems


With the increasing gap between processor, memory, and interconnect speed, the performances of scientific applications on high performance computing systems have become dominated by the ability to move global data. However, many benchmarks in the field of high performance computing focus on measuring the achieved CPU speed in MFlop/s. In this paper, we introduced a novel benchmark, Apex-Map, which focuses on global data movement and measures how fast global data can be fed into computational units. Apex-Map is a parameterized synthetic performance probe and integrates concepts for tempo-ral and spatial locality into its design. By measuring the Apex-Map performance for a whole range of temporal and spatial localities performance surfaces can be generated which can be used to study the characteristics of the computational platforms and which are useful for performance comparison. Results on a vector platform and two superscalar platforms clearly reflect the design differences be-tween these two types of systems.

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