Simplifying the Development, Use and Sustainability of HPC Software
Jeremy Cohen, Chris Cantwell, Neil Chue Hong, David Moxey, Malcolm, Illingworth, Andrew Turner, John Darlington, Spencer Sherwin

TL;DR
This paper discusses developing a framework to simplify HPC software development and execution on heterogeneous infrastructure, addressing sustainability and efficiency challenges in scientific computing.
Contribution
It introduces a framework for richer job specification and efficient execution of scientific software on diverse platforms, enhancing sustainability.
Findings
Framework improves job specification for heterogeneous systems
Enhances efficiency of scientific software execution
Supports sustainability of HPC software
Abstract
Developing software to undertake complex, compute-intensive scientific processes requires a challenging combination of both specialist domain knowledge and software development skills to convert this knowledge into efficient code. As computational platforms become increasingly heterogeneous and newer types of platform such as Infrastructure-as-a-Service (IaaS) cloud computing become more widely accepted for HPC computations, scientists require more support from computer scientists and resource providers to develop efficient code and make optimal use of the resources available to them. As part of the libhpc stage 1 and 2 projects we are developing a framework to provide a richer means of job specification and efficient execution of complex scientific software on heterogeneous infrastructure. The use of such frameworks has implications for the sustainability of scientific software. In…
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Taxonomy
TopicsDistributed and Parallel Computing Systems · Scientific Computing and Data Management · Advanced Data Storage Technologies
