Performance study of sustained petascale direct numerical simulation on Cray XC40 systems. (17th March 2020)

• Record Type: Journal Article
• Authors: Hadri, Bilel; Parsani, Matteo; Hutchinson, Maxwell; Heinecke, Alexander; Dalcin, Lisandro; Keyes, David
• Other Names: Gil‐Costa Veronica guestEditor.; Senger Hermes guestEditor.; Robinson Timothy W. guestEditor.; Thota Abhinav guestEditor.
• Is Part Of: Concurrency and computation. Volume 32:Number 20(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-03-17
• Subjects: Cray XC40 -- energy efficiency -- Haswell -- KNL -- Nek5000 -- performance analysis -- regression; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.5725
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: We present in this paper a comprehensive performance study of highly efficient extreme scale direct numerical simulations of secondary flows, using an optimized version of Nek5000. Our investigations are conducted on various Cray XC40 systems, using a very high‐order spectral element method. Single‐node efficiency is achieved by auto‐generated assembly implementations of small matrix multiplies and key vector‐vector operations, streaming lossless I/O compression, aggressive loop merging, and selective single precision evaluations. Comparative studies across different Cray XC40 systems at scale, Trinity (LANL), Cori (NERSC), and ShaheenII (KAUST) show that a Cray programming environment, network configuration, parallel file system, and burst buffer all have a major impact on the performance. All three systems possess a similar hardware with similar CPU nodes and parallel file system, but they have different theoretical peak network bandwidths, different OSs, and different versions of the programming environment. Our study reveals how these slight configuration differences can be critical in terms of performance of the application. We also find that with 9216 nodes (294 912 cores) on Trinity XC40 the applications sustain petascale performance, as well as 50% of peak memory bandwidth over the entire solver (500 TB/s in aggregate). On 3072 Xeon Phi nodes of Cori, we reach 378 TFLOP/s with an aggregated bandwidth of 310 TB/s, corresponding to time‐to‐solution 2.11× faster than obtained with the same number of (dual‐socket) Xeon nodes.