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We present the Glasgow Parallel Reduction Machine (GPRM), a novel, flexibleframework for parallel task-composition based many-core programming. We allowthe programmer to structure programs into task code, written as C++ classes,and communication code, written in a restricted subset of C++ with functionalsemantics and parallel evaluation. In this paper we discuss the GPRM, thevirtual machine framework that enables the parallel task composition approach.We focus the discussion on GPIR, the functional language used as theintermediate representation of the bytecode running on the GPRM. Using examplesin this language we show the flexibility and power of our task compositionframework. We demonstrate the potential using an implementation of a merge sortalgorithm on a 64-core Tilera processor, as well as on a conventional Intelquad-core processor and an AMD 48-core processor system. We also compare ourframework with OpenMP tasks in a parallel pointer chasing algorithm running onthe Tilera processor. Our results show that the GPRM programs outperform thecorresponding OpenMP codes on all test platforms, and can greatly facilitatewriting of parallel programs, in particular non-data parallel algorithms suchas reductions.

The Glasgow Parallel Reduction Machine: Programming Shared-memory Many-core Systems using Parallel Task Composition