Nonvolatile memory NVDIMMs, available as Intel Optane, are less expensive than DRAM and bring large byte-addressable storage within reach to many applications. Evaluations on graph analytics have shown promising performance only when DRAM is used as a hardware cache (Memory mode). An open question is whether graph applications can exploit Optane and DRAM directly (AppDirect mode) and achieving better-than-DRAM average bandwidth and run times. We evaluate Optane as a volatile pool on two large-scale graph applications with very different computational patterns, Grappolo and Ripples. We show that AppDirect mode can deliver better-than-DRAM performance, by allocating data structures to Optane and DRAM according to their access characteristics, resulting in higher average memory bandwidth and lower average latency. Memory mode provides DRAM-competitive performance with capacity equal to persistent memory. We demonstrate occasional 4x improvement using the latest AppDirect option and frequently observe competitive performance between Optane AppDirect Memory modes and DRAM.
Published: December 18, 2021
Citation
Ghosh S., N.R. Tallent, M. Minutoli, M. Halappanavar, R. Peri, and A. Kalyanaraman. 2021.Single-node Partitioned-Memory for Huge Graph Analytics: Cost and Performance Trade-offs. In Proceedings of the International Conference for High Performance Computing, Network, Storage and Analysis (SC 2021), November 14-19, 2021, Virtual, Online, Art. No. 55. New York, New York:Association for Computing Machinery.PNNL-SA-161359.doi:10.1145/3458817.3476156