Domain specific languages for parallel numerical modeling on structured grids
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De Rango, Alessio
Leone, Nicola
D'Ambrosio, Donato
Spataro, William
Mudalige, Gihan
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Dottorato di Ricerca in Matematica ed Informatica. Ciclo XXXI; High performance computing (HPC) is undergoing a period of enormous
change. Due to the di culties in increasing clock frequency inde nitely
(i.e., the breakdown of Dennard's scaling and power wall), the current direction
is towards improving performance through increasing parallelism.
However, there is no clear consensus yet on the best architecture for HPC,
and di erent solutions are currently employed. As a consequence, applications
targeting a given architecture can not be easily adapted to run on
alternative solutions, since this would require a great e ort due to the need
to deal with platform-speci c details. Since it is not known a priori which
HPC architecture will prevail, the Scienti c Community is looking for a solution
that could tackle the above mentioned issue. A possible solution consists
in the adoption of a high-level abstraction development strategy based
on Domain Speci c Languages (DSLs). Among them, OpenCAL (Open
Computing Abstraction Layer) and OPS (Oxford Parallel Structured) have
been proposed as domain speci c C/C++ data parallel libraries for structured
grids. The aim of these libraries is to provide an abstract computing
model able to hide any parallelization detail by targeting, at the same time,
di erent current (and possibly future) parallel architectures. In this Thesis,
I have contributed to the design and development of both the OpenCAL
and OPS projects. In particular, my contribution to OpenCAL has regarded
the development of the single-GPU and multi-GPU/multi-node components,
namely OpenCAL-CL and OpenCAL-CLM, while my contribution to OPS
has regarded the introduction of the OpenMP 4.0/4.5 support, as an alternative
to OpenCL, CUDA and OpenACC, for exploiting modern many-core
computing systems. Both the improved DSLs have been tested on di erent
benchmarks, among which a fractal set generator, a graphics lter routine,
and three di erent
uid-
ows applications, with more than satisfying results.
In particular, OpenCAL was able to e ciently scale over larger computational
domains with respect to its original implementation, thanks to
the new multi-GPU/multi-node capabilities, while OPS was able to reach
near optimal performance using the high-level OpenMP 4.0/4.5 speci cations
on many-core accelerators with respect to the alternative low-level
CUDA-based version.; Università della CalabriaSoggetto
Computer science; Parallel processing; Computer graphics
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