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November 19, 2010
If there was a dominating theme at the Supercomputing Conference this year, it had to be GPU computing. 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…
November 15, 2010
Data-intensive applications are quickly emerging as a significant new class of HPC workloads. For this class of applications, a new kind of supercomputer, and a different way to assess them, will be required. That is the impetus behind the Graph 500, a set of benchmarks that aim to measure the suitability of systems for data-intensive analytics applications. Read more…
November 15, 2010
SGI has made good on its promise to create a petaflop-in-a-cabinet supercomputer that can scale up to tens and even hundreds of cabinets. Developed under the code name "Project Mojo," the company has dubbed the new product Prism XL. SGI will be showcasing the system this week in their exhibit booth at the Supercomputing Conference in New Orleans. Read more…
November 14, 2010
Like every technology-based sector, high performance computing takes its biggest leaps by the force of disruptive innovation, a term coined by the man who will keynote this year's Supercomputing Conference (SC10) in New Orleans. Clayton M. Christensen doesn't know a whole lot about supercomputing, but he knows a great deal about the forces that drive it. Read more…
Next-generation imaging technologies are producing a wealth of rich data to advance Life Sciences research. Artificial intelligence and machine learning can help researchers quickly derive insights from such data. However, many organizations do not have the infrastructures to handle the combination of enormous imaging data volumes and demanding analysis compute requirements.
What’s needed is an infrastructure that supports mixed genomic analysis and image analysis workloads. This paper discusses the new compute and storage demands for Cryogenic Electron Microscopy (CryoEM) and Lattice Light Sheet Microscopy (LLS) image analysis pipelines and the need for an easy to manage data storage foundation that delivers high performance in a reliable, scalable, and adaptable way.
In this webinar, Martijn de Vries, CTO at Bright Computing and Robert Stober, Director of Product Management at Bright Computing, discuss the convergence of HPC and AI in the context of current industry trends and practices being used by organizations. They will discuss and demonstrate the convergence of HPC and AI on a shared infrastructure using Bright auto-scaler to enable efficient use of compute resources based on workload demand and policies, and also cover how to extend HPC/A.I. infrastructure to edge locations. Don’t miss out on this opportunity to gain valuable insight into innovative ways HPC and AI are being used together today.
In this SpotlightON we take a look at the fast-expanding world of AI use cases. In some sense it’s harder to identify what won’t be a potential use case for AI. Today, finance, internet commerce, healthcare, energy discovery and management, and IoT applications are all hot beds of AI development and deployment. Many more will follow. Learn how your work day and business may benefit from these experiences.
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