In the first report from last week’s PRACEdays15 conference in Dublin, Tom Wilkie from Scientific Computing World considers why so much Exascale software will be open source and why engineers are not using parallel programs.
In the first report from last week’s PRACEdays15 conference in Dublin, Tom Wilkie from Scientific Computing World considers why so much Exascale software will be open source and why engineers are not using parallel programs.
In this guest article, our friends at Intel discuss how accelerated computing has diversified over the past several years given advances in CPU, GPU, FPGA, and AI technologies. This innovation drives the need for an open and cross-platform language that allows developers to realize the potential of new hardware, minimizes development cost and complexity, and maximizes reuse of their software investments.
Many new technologies used in High Performance Computing (HPC) have allowed new application areas to become possible. Advances like multi-core, GPU, NVMe, and others have created application verticals that include accelerator assisted HPC, GPU based Deep Learning, Fast storage and parallel file systems, and Big Data Analytics systems. In this special insideHPC technology guide sponsored by our friends over at Tyan, we look at practical hardware design strategies for modern HPC workloads.
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