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Characterizing the performance benefit of hybrid memory system for HPC applications
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2018 (English)In: Parallel Computing, ISSN 0167-8191, E-ISSN 1872-7336, Vol. 76, p. 57-69Article in journal (Refereed) Published
Abstract [en]

Heterogenous memory systems that consist of multiple memory technologies are becoming common in high-performance computing environments. Modern processors and accelerators, such as the Intel Knights Landing (KNL) CPU and NVIDIA Volta GPU, feature small-size high-bandwidth memory near the compute cores and large-size normal-bandwidth memory that is connected off-chip. Theoretically, HBM can provide about four times higher bandwidth than conventional DRAM. However, many factors impact the actual performance improvement that an application can achieve on such system. In this paper, we focus on the Intel KNL system and identify the most important factors on the application performance, including the application memory access pattern, the problem size, the threading level and the actual memory configuration. We use a set of representative applications from both scientific and data-analytics domains. Our results show that applications with regular memory access benefit from MCDRAM, achieving up to three times performance when compared to the performance obtained using only DRAM. On the contrary, applications with irregular memory access pattern are latency-bound and may suffer from performance degradation when using only MCDRAM. Also, we provide memory-centric analysis of four applications, identify their major data objects, correlate their characteristics to the performance improvement on the testbed.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 76, p. 57-69
Keywords [en]
Heterogenous memory system, Intel Knights Landing (KNL) processor, MCDRAM, Memory-centric profiling
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-229249DOI: 10.1016/j.parco.2018.04.007ISI: 000446404600005Scopus ID: 2-s2.0-85047113223OAI: oai:DiVA.org:kth-229249DiVA, id: diva2:1212137
Funder
EU, European Research Council
Note

QC 20180601

Available from: 2018-06-01 Created: 2018-06-01 Last updated: 2018-10-23Bibliographically approved

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Laure, ErwinMarkidis, Stefano

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CiteExportLink to record
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