November 18, 2010
The increased awareness in the HPC community of the need to maximize energy efficiency in compute-intensive environments has never been greater. With The Green500 results coming out this week, HPCwire's Caroline Connor turned to Professor Wu Feng from Virginia Tech, the man largely credited with the movement towards environmentally-sustainable supercomputing. Read more…
November 17, 2010
Interpreted programming languages usually don't find too many friends in high performance computing. Yet Python, one of the most popular general-purpose interpreted languages, has garnered a small community of enthusiastic followers. True believers got the opportunity to hear about the language in the HPC realm in a tutorial session on Monday and a BoF session on Wednesday. Argonne National Lab's William Scullin, who participated in both events, talked with HPCwire about the status of Python in this space and what developers might look forward to. Read more…
November 16, 2010
Although the parallel programming landscape is relatively young, it's already easy to get lost in. Beside legacy frameworks like MPI and OpenMP, we now have NVIDIA's CUDA, OpenCL, Cilk, Intel Threading Building Blocks, Microsoft's parallel programming extensions for .NET, and a whole gamut of PGAS languages. And according to Intel's Tim Mattson, that's not necessarily a good thing. Read more…
November 16, 2010
NVIDIA's CUDA is easily the most popular programming language for general-purpose GPU computing. But one of the more interesting developments in the CUDA-verse doesn't really involve GPUs at all. In September, HPC compiler vendor PGI (The Portland Group Inc.) announced its intent to build a CUDA compiler for x86 platforms. The technology will be demonstrated for the first time in public at SC10 this week in New Orleans. Read more…
Did you miss out on Supercomputing 2017? Did you attend, but were stuck in meetings the whole time without an opportunity to walk the show floor and see what new announcements were being made? HPCwire's got you covered, we visited some of the hottest booths in the exhibit hall and spoke with their top executives to get the scoop on the latest solutions, partnerships, and product announcements.
From mismatches between compute and storage capabilities to colossal data volumes, data storage presents a number of challenges for scientific research. And as silos pop up and challenges expand, the pace of research often suffers.
As genomic data becomes ubiquitous, infrastructure bottlenecks for life sciences organizations are narrowing. But speedy analysis and real-time decision making don't have to remain out of reach: modern end-to-end systems are emerging as flexible solutions for a competitive edge.
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