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This paper presents the Graph Analytics Repository for DesigningNext-generation Accelerators (GARDENIA), a benchmark suite for studyingirregular algorithms on massively parallel accelerators. Existing genericbenchmarks for accelerators have mainly focused on high performance computing(HPC) applications with limited control and data irregularity, while availablegraph analytics benchmarks do not apply state-of-the-art algorithms and/oroptimization techniques. GARDENIA includes emerging irregular applications inbig-data and machine learning domains which mimic massively multithreadedcommercial programs running on modern large-scale datacenters. Ourcharacterization shows that GARDENIA exhibits irregular microarchitecturalbehavior which is quite different from structured workloads andstraightforward-implemented graph benchmarks.

GARDENIA: A Domain-specific Benchmark Suite for Next-generation Accelerators