Forskning ved Københavns Universitet - Københavns Universitet


Comparing and Optimising Parallel Haskell Implementations for Multicore Machines

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  • Jost Berthold
  • Simon Marlow
  • Kevin Hammond
  • A.D. Al Zain
In this paper, we investigate the differences and tradeoffs imposed by two parallel Haskell dialects running on multicore machines. GpH and Eden are both constructed using the highly-optimising sequential GHC compiler, and share thread scheduling, and other elements, from a common code base. The GpH implementation investigated here uses a physically-shared heap, which should be well-suited to multicore architectures. In contrast, the Eden implementation adopts an approach that has been designed for use on distributed-memory parallel machines: a system of multiple, independent heaps (one per core), with inter-core communication handled by message-passing rather
than through shared heap cells. We report two main results. Firstly, we report on the effect of a number of optimisations that we applied to the shared-memory GpH implementation in order to address some performance issues that were revealed by our testing: for example, we implemented a work-stealing approach to task allocation. Our optimisations improved the performance of the shared-heap GpH implementation by as much as 30% on eight cores. Secondly, the shared heap approach is, rather surprisingly, not superior to a distributed heap implementation:
both give similar performance results.
TitelProceedings of the 2009 International Conference on Parallel Processing Workshops : ICPPW '09
Antal sider8
ForlagIEEE Computer Society Press
ISBN (Trykt)978-0-7695-3803-7
StatusUdgivet - 2009
Begivenhed3rd Int. Workshop on Advanced Distributed and Parallel Network Applications (ADPNA-2009) - Vienna, Østrig
Varighed: 22 sep. 200925 sep. 2009
Konferencens nummer: 3


Konference3rd Int. Workshop on Advanced Distributed and Parallel Network Applications (ADPNA-2009)

ID: 16812463