Improving GHC Haskell NUMA profiling

Ruairidh MacGregor, Phil Trinder, Hans Wolfgang Loidl

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As the number of cores increases Non-Uniform Memory Access (NUMA) is becoming increasingly prevalent in general purpose machines. Effectively exploiting NUMA can significantly reduce memory access latency and thus runtime by 10-20%, and profiling provides information on how to optimise. Language-level NUMA profilers are rare, and mostly profile conventional languages executing on Virtual Machines. Here we profile, and develop new NUMA profilers for, a functional language executing on a runtime system. We start by using existing OS and language level tools to systematically profile 8 benchmarks from the GHC Haskell nofib suite on a typical NUMA server (8 regions, 64 cores). We propose a new metric: NUMA access rate that allows us to compare the load placed on the memory system by different programs, and use it to contrast the benchmarks. We demonstrate significant differences in NUMA usage between computational and data-intensive benchmarks, e.g. local memory access rates of 23% and 30% respectively. We show that small changes to coordination behaviour can significantly alter NUMA usage, and for the first time quantify the effectiveness of the GHC 8.2 NUMA adaption. We identify information not available from existing profilers and extend both the numaprof profiler, and the GHC runtime system to obtain three new NUMA profiles: OS thread allocation locality, GC count (per region and generation) and GC thread locality. The new profiles not only provide a deeper understanding of program memory usage, they also suggest ways that GHC can be adapted to better exploit NUMA architectures.

Original languageEnglish
Title of host publicationProceedings of the 9th ACM SIGPLAN International Workshop on Functional High-Performance and Numerical Computing
EditorsGabriele Keller, Troels Henriksen
PublisherAssociation for Computing Machinery
Pages1-12
Number of pages12
ISBN (Electronic)9781450386142
DOIs
Publication statusPublished - 22 Aug 2021
Event9th ACM SIGPLAN International Workshop on Functional High-Performance and Numerical Computing 2021 - Virtual, Online, Korea, Republic of
Duration: 22 Aug 2021 → …

Conference

Conference9th ACM SIGPLAN International Workshop on Functional High-Performance and Numerical Computing 2021
Abbreviated titleFHPNC 2021
Country/TerritoryKorea, Republic of
CityVirtual, Online
Period22/08/21 → …

Keywords

  • GHC
  • Haskell
  • NUMA
  • Profiling

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

Fingerprint

Dive into the research topics of 'Improving GHC Haskell NUMA profiling'. Together they form a unique fingerprint.

Cite this