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Software Development Standards for Next-gen HPC Systems

John Barr asks what standard approach can the industry agree on to make next-generation HPC systems easier to program? When the architecture of high-performance computing (HPC) systems changes, the tools and programming paradigms used to develop applications may also have to change. We have seen several such evolutions in recent decades, including the introduction of multiprocessors, the use of heterogeneous processors to accelerate applications, vector processors, and cluster computing. .

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Interview: The Software Imperative for Supercomputing

In a newly posted interview, Cray’s Jay Gould describes how the supercomputing world has changed and why the company has nearly a 5:1 ratio of software engineers to hardware engineers. You can’t just clock processors faster or add more cores and expect a supercomputer to go faster. What if the code is...

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ARM for HPC Will be Build-what-you-want Style

Over at the ARM Blog, Andrew Sloss writes that the ARM approach to Big Data and HPC sets out to maximize efficiency by not over-designing any particular component. The next era of systems will follow a-build-what-you-want style. By allowing the targeting of a SoC (System-on-Chip) to solve specific problems –...

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When Virtualized HPC Speeds Past Bare Metal

Virtualization has attractive features that could benefit HPC, but many have waved it off due to the perceived performance hit. That may be changing. Over at the Long White Virtual Clouds Blog, Michael Webster writes that an upcoming session at VMworld will show how HPC performance in a virtualized system can actually surpass Monte Carlo Grid performance on bare metal. The Air and Missile Defense Department’s Combat Systems Development Facility at JHU Applied Physics Laboratory relies on large-scale, Monte-Carlo simulations to perform classified combat systems performance assessments and concept studies for multiple Department of Defense...

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Parallella University Program to Bring Parallel Computing to Higher Education

Adapteva today introduced its Parallella University Program (PUP) for parallel programing research and/or education. Designed so universities can access inexpensive and open parallel computing hardware, the PUP program provides free hardware and developmental software specifically focused on parallel computing. The first offering via the PUP program will be the Parallella-16 computer, Adapteva’s Kickstarter-funded credit-card sized multicore processing platform. Adapteva is donating one Parallella-16 platform for each 100 units sold via the company’s online store. The present and future of computing is clearly...

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