Spatter: A Tool for Evaluating Gather / Scatter Performance
Patrick Lavin, Jeffrey Young, Jason Riedy, Richard Vuduc, Aaron Vose,, Dan Ernst

TL;DR
Spatter is a new benchmark tool designed to evaluate memory system performance for complex gather and scatter access patterns common in modern HPC applications, providing insights into CPU and GPU efficiencies.
Contribution
This paper introduces Spatter, an open-source, configurable benchmark for assessing gather/scatter memory operations across different hardware and access patterns, filling gaps left by traditional benchmarks.
Findings
GPUs outperform CPUs for gather/scatter operations
Spatter better models cache-dependent mini-app performance
Evaluates prefetching and vectorization effects
Abstract
This paper describes a new benchmark tool, Spatter, for assessing memory system architectures in the context of a specific category of indexed accesses known as gather and scatter. These types of operations are increasingly used to express sparse and irregular data access patterns, and they have widespread utility in many modern HPC applications including scientific simulations, data mining and analysis computations, and graph processing. However, many traditional benchmarking tools like STREAM, STRIDE, and GUPS focus on characterizing only uniform stride or fully random accesses despite evidence that modern applications use varied sets of more complex access patterns. Spatter is an open-source benchmark that provides a tunable and configurable framework to benchmark a variety of indexed access patterns, including variations of gather/scatter that are seen in HPC mini-apps evaluated…
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Taxonomy
TopicsParallel Computing and Optimization Techniques · Advanced Data Storage Technologies · Cloud Computing and Resource Management
