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EXA2PRO: A Framework for High Development Productivity on Heterogeneous Computing Systems

Authors: Lazaros Papadopoulos; Dimitrios Soudris; Christoph W. Kessler; August Ernstsson; Johan Ahlqvist; Nikos Vasilas; Athanasios I. Papadopoulos; +7 Authors

EXA2PRO: A Framework for High Development Productivity on Heterogeneous Computing Systems

Abstract

Programming upcoming exascale computing systems is expected to be a major challenge. New programming models are required to improve programmability, by hiding the complexity of these systems from application developers. The EXA2PRO programming framework aims at improving developers' productivity for applications that target heterogeneous computing systems. It is based on advanced programming models and abstractions that encapsulate low-level platform-specific optimizations and it is supported by a runtime that handles application deployment on heterogeneous nodes. It supports a wide variety of platforms and accelerators (CPU, GPU, FPGAbased Data-Flow Engines), allowing developers to efficiently exploit heterogeneous computing systems, thus enabling more HPC applications to reach exascale computing. The EXA2PRO framework was evaluated using four HPC applications from different domains. By applying the EXA2PRO framework, the applications were automatically deployed and evaluated on a variety of computing architectures, enabling developers to obtain performance results on accelerators, test scalability on MPI clusters and productively investigate the degree by which each application can efficiently use different types of hardware resources.

Countries
France, Sweden
Keywords

Skeleton programming, [INFO.INFO-DC]Computer Science [cs]/Distributed, 000, Programming models, Programming productivity, Parallel, Programming; Skeleton; Computational modeling; Runtime; Exascale computing; Task analysis; Productivity; Programming models; skeleton programming; task-based runtime systems; programming productivity; heterogeneous systems; exascale computing, Heterogeneous systems, 004, Datorsystem, and Cluster Computing [cs.DC], Computer Systems, Exascale computing, Task-based runtime systems, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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5
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34
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