Memory centric characterization and analysis of SPec CPU 2017 suite

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Abstract

In this paper, we provide a comprehensive, memory-centric characterization of the SPEC CPU2017 benchmark suite, using a number of mechanisms including dynamic binary instrumentation, measurements on native hardware using hardware performance counters and operating system based tools. We present a number of results including working set sizes, memory capacity consumption and memory bandwidth utilization of various workloads. Our experiments reveal that, on the x86_64 ISA, SPEC CPU2017 workloads execute a significant number of memory related instructions, with approximately 50% of all dynamic instructions requiring memory accesses. We also show that there is a large variation in the memory footprint and bandwidth utilization profiles of the entire suite, with some benchmarks using as much as 16 GB of main memory and up to 2.3 GB/s of memory bandwidth. We perform instruction distribution analysis of the benchmark suite and find that the average instruction count for SPEC CPU2017 workloads is an order of magnitude higher than SPEC CPU2006 ones. In addition, we also find that FP benchmarks of the suite have higher compute requirements: on average, FP workloads execute three times the number of compute operations as compared to INT workloads.

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Singh, S., & Awasthi, M. (2019). Memory centric characterization and analysis of SPec CPU 2017 suite. In ICPE 2019 - Proceedings of the 2019 ACM/SPEC International Conference on Performance Engineering (pp. 285–292). Association for Computing Machinery, Inc. https://doi.org/10.1145/3297663.3310311

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