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Summit Achieves 445 Petaflops on New ‘HPL-AI’ Benchmark
June 19, 2019
Summit -- the world's top-ranking supercomputer -- has been used to test-drive a new mixed-precision Linpack benchmark, which for now is being called HPL-AI. Traditionally, supercomputer performance is measured using the High-Performance Linpack (HPL) benchmark, which is the basis for the Top500 list that biannually ranks world's fastest supercomputers. Read more…
Azure Edges AWS in Linpack Benchmark Study
February 15, 2017
The “when will clouds be ready for HPC” question has ebbed and flowed for years. It seems clear that for at least some workloads and on some clouds, the ans Read more…
Blue Waters Opts Out of TOP500
November 16, 2012
NCSA's Blue Waters system is one of the fastest supercomputers in the world, but it won't be appearing on the TOP500 list, nor will it be taking part in the HPC Challenge awards. HPCwire spoke with Project Director Bill Kramer to get the full story on this important decision. Read more…
Graph 500 Takes Aim at a New Kind of HPC
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…
Should I Buy GPGPUs or Blue Gene?
November 4, 2010
Given the recent ascent of the GPU-powered Tianhe-1A system to the top of the supercomputing heap, a current paper from Department of Computer Science at the University of Warwick should be of particular interest to those in the market for a petascale supercomputer. Essentially their study asks the question: As an organization, should I commit to a platform based on general-purpose GPUs or an IBM Blue Gene? Read more…
Compilers and More: Hardware/Software Codesign
November 2, 2010
There is a growing feeling that merely taking the latest processor offerings from Intel, AMD or IBM will not get us to exascale in a reasonable time frame, cost budget, and power constraint. One avenue to explore is designing and building more specialized systems, aimed at the types of problems seen in HPC, or at least at the problems seen in some important subset of HPC. Of course, such a strategy loses the advantages we've enjoyed over the past two decades of commoditization in HPC; however, a more special purpose design may be wise, or necessary. Read more…
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