Abstract
To take advantage of distributed-memory parallel machines it is essential to have good control of task granularity. This paper describes a fairly accurate parallel simulator for Haskell, based on the Glasgow compiler, and complementary tools for visualising task granularities. Together these tools allow us to study the effects of various annotations on task granularity on a variety of simulated parallel architectures. They also provide a more precise tool for the study of parallel execution than has previously been available for Haskell programs.
These tools have already confirmed granularity results previously obtained for our novel GRIP architecture, demonstrated a close correlation between thread execution times and total heap allocations, and revealed that conservative granularity analysis may well be too conservative
Supported by a SOED Research Fellowship from the Royal Society of Edinburgh and the UK EPSRC Parade project.
Supported by a Kurt-Gödel scholarship (GZ 558.012/38-IV/5a/93) of the Austrian Ministry of Science and Research and by a KIP scholarship of the government of Upper Austria.
Winnow (v.): To treat (as grain) by exposure to a current of air so that waste matter is eliminated.
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Hammond, K., Loidl, H.W., Partridge, A. (1995). Improving Granularity in Parallel Functional Programs: A Graphical Winnowing System for Haskell. In: Hammond, K., Turner, D.N., Sansom, P.M. (eds) Functional Programming, Glasgow 1994. Workshops in Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3573-9_8
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