Patrick Maier, Rob Stewart, Phil Trinder

Reliable scalable symbolic computation: The design of SymGridPar2

ABSTRACT:
Symbolic computation is an important area of both Mathematics and
Computer Science, with many large computations that would benefit from
parallel execution. Symbolic computations are, however, challenging to
parallelise as they have complex data and control structures, and both
dynamic and highly irregular parallelism. The SymGridPar framework
(SGP) has been developed to address these challenges on small-scale
parallel architectures. However the multicore revolution means that
the number of cores and the number of failures are growing
exponentially, and that the communication topology is becoming
increasingly complex. Hence an improved parallel symbolic computation
framework is required.

This paper presents the design and initial evaluation of SymGridPar2
(SGP2), a successor to SymGridPar that is designed to provide
scalability onto 10^5 cores, and hence also provide fault
tolerance. We present the SGP2 design goals, principles and
architecture. We describe how scalability is achieved using layering
and by allowing the programmer to control task placement. We outline
how fault tolerance is provided by supervising remote computations,
and outline higher-level fault tolerance abstractions.

We describe the SGP2 implementation status and development plans. We
report the scalability and efficiency, including weak scaling to about
32,000 cores, and investigate the overheads of tolerating faults for
simple symbolic computations.

KEYWORDS:
Parallel functional programming;
Locality control;
Fault tolerance