Abstract
The study presents a comparison of computing systems based on IBM POWER8, IBM POWER9, and Intel Xeon Platinum 8160 processors running parallel applications. Memory subsystem bandwidth was studied, parallel programming technologies were compared, and the operating modes and capabilities of simultaneous multithreading technology were analyzed. Performance analysis for the studied computing systems running parallel applications based on the OpenMP and MPI technologies was carried out by using the NAS Parallel Benchmarks. An assessment of the results obtained during experimental calculations led to the conclusion that IBM POWER8 and Intel Xeon Platinum 8160 systems have almost the same maximum memory bandwidth, but require a different number of threads for efficient utilization. The IBM POWER9 system has the highest maximum bandwidth, which can be attributed to the large number of memory channels per socket. Based on the results of numerical experiments, recommendations are given on how the hardware of a similar grade can be utilized to solve various scientific problems, including recommendations on optimal processor architecture choice for leveraging the operation of high-performance hybrid computing platforms.
Highlights
The advent of specialized algorithms and software data-processing systems using the capabilities of graphic coprocessors (GPUs) has led to an increase in the demand for hybrid high-performance computing systems
This paper presents the second part of the results of this study, which contains benchmark data for modern IBM POWER series processors, including a comparison with Intel Xeon Platinum
The results shown in the figure show that, despite an almost double difference in operating frequency, IBM POWER8 and Intel Xeon Platinum 8160 processor cores demonstrate a similar performance in ST mode
Summary
The advent of specialized algorithms and software data-processing systems using the capabilities of graphic coprocessors (GPUs) has led to an increase in the demand for hybrid high-performance computing systems. We can single out the tasks of image processing [1], which have found completely new capabilities for data analysis and interpretation. Most of the above studies evaluate only the GPU in detail [2], paying very little attention to central processors. This issue is extremely important, since in supercomputer centers that provide access to their computing resources for scientists, it is necessary to use the capabilities of modern computing systems built on the basis of the GPU as efficiently as possible [3]. With the seemingly limited choice of CPU manufacturers, each of them (Intel (Santa Clara, CA, USA), IBM (Armonk, NY, USA), etc.) is Electronics 2020, 9, 1035; doi:10.3390/electronics9061035 www.mdpi.com/journal/electronics
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