A group of HPC thinkers, including the estimable Satoshi Matsuoka of the RIKEN Center for Computational Science in Japan, have come together to challenge common lines of thought they say have become, to varying degrees, accepted wisdom in HPC. In a paper entitled “Myths and Legends of High-Performance Computing” appearing this week on the Arvix […]
Double-precision CPUs vs. Single-precision GPUs; HPL vs. HPL-AI HPC Benchmarks; Traditional vs. AI Supercomputers
July 20, 2021 by
If you’ve wondered why GPUs are faster than CPUs, in part it’s because GPUs are asked to do less – or, to be more precise, to be less precise. Next question: So if GPUs are faster than CPUs, why aren’t GPUs the mainstream, baseline processor used in HPC server clusters? Again, in part it gets […]
A Data-Centric Approach to Extreme-Scale Ab initio Dissipative Quantum Transport Simulations
May 7, 2020 by
Alexandros Ziogas from ETH Zurich gave this talk at Supercomputing Frontiers Europe. “The computational efficiency of a state of the art ab initio #quantum transport (QT) solver, capable of revealing the coupled electro-thermal properties of atomically-resolved nano-transistors, has been improved by up to two orders of magnitude through a data centric reorganization of the application. The approach yields coarse-and fine-grained data-movement characteristics that can be used for performance and communication modeling, communication-avoidance, and dataflow transformations.”
Accelerating High-Resolution Weather Models with Deep-Learning Hardware
July 26, 2019 by
Sam Hatfield from the University of Oxford gave this talk at the PASC19 conference. “In this paper, we investigate the use of mixed-precision hardware that supports floating-point operations at double-, single- and half-precision. In particular, we investigate the potential use of the NVIDIA Tensor Core, a mixed-precision matrix-matrix multiplier mainly developed for use in deep learning, to accelerate the calculation of the Legendre transforms in the Integrated Forecasting System (IFS), one of the leading global weather forecast models.”
Summit Supercomputer Triples Performance Record on new HPL-AI Benchmark
July 1, 2019 by
“Using HPL-AI, a new approach to benchmarking AI supercomputers, ORNL’s Summit system has achieved unprecedented performance levels of 445 petaflops or nearly half an exaflops. That compares with the system’s official performance of 148 petaflops announced in the new TOP500 list of the world’s fastest supercomputers.”
Radio Free HPC Looks at the coming wave of 40+ Different AI Chips
June 11, 2019 by
In this podcast, the Radio Free HPC Team asks, “What are we going to do with 40+ AI chips?” One such chip, Graphcore, is touted as “the most complex processor” ever at some 20 billion transistors. The VC-backed company out of Bristol, UK is also valued on paper at $1.7b, gaining it the coveted “unicorn” status, apparently the “only western semi-conductor unicorn.”
Achieving ExaOps with the CoMet Comparative Genomics Application
May 16, 2019 by
Wayne Joubert’s talk at the HPC User Forum described how researchers at the US Department of Energy’s Oak Ridge National Laboratory (ORNL) achieved a record throughput of 1.88 ExaOps on the CoMet algorithm. As the first science application to run at the exascale level, CoMet achieved this remarkable speed analyzing genomic data on the recently launched Summit supercomputer.
