Publication | Closed Access
Wait of a Decade: Did SPEC CPU 2017 Broaden the Performance Horizon?
88
Citations
34
References
2018
Year
Unknown Venue
Cluster ComputingEngineeringComputer ArchitectureSoftware EngineeringProcessor ArchitectureData ScienceSpec Cpu2017 BenchmarksParallel ComputingManycore ProcessorPerformance PredictionXeon PhiComputer EngineeringComputer ScienceCpu2017 BenchmarksPerformance Analysis ToolBenchmarking ToolPerformance HorizonProgram AnalysisSoftware TestingParallel Performance EvaluationMany-core ArchitectureParallel ProgrammingSpec Cpu2017Technology
The recently released SPEC CPU2017 benchmark suite has already started receiving a lot of attention from both industry and academic communities. However, due to the significantly high size and complexity of the benchmarks, simulating all the CPU2017 benchmarks for design trade-off evaluation is likely to become extremely difficult. Simulating a randomly selected subset, or a random input set, may result in misleading conclusions. This paper analyzes the SPEC CPU2017 benchmarks using performance counter based experimentation from seven commercial systems, and uses statistical techniques such as principal component analysis and clustering to identify similarities among benchmarks. Such analysis can reveal benchmark redundancies and identify subsets for researchers who cannot use all benchmarks in pre-silicon design trade-off evaluations. Many of the SPEC CPU2006 benchmarks have been replaced with larger and complex workloads in the SPEC CPU2017 suite. However, compared to CPU2006, it is unknown whether SPEC CPU2017 benchmarks have different performance demands or whether they stress machines differently. Additionally, to evaluate the balance of CPU2017 benchmarks, we analyze the performance characteristics of CPU2017 workloads and compare them with emerging database, graph analytics and electronic design automation (EDA) workloads. This paper provides the first detailed analysis of SPEC CPU2017 benchmark suite for the architecture community.
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