• Will Chapel Mark Next Great Awakening for Parallel Programmers?

    April 10, 2018

    Just because supercomputers are engineered to be far more powerful over time does not necessarily mean programmer productivity will follow the same curve. Added performance means more complexity, which for parallel programmers means working harder, especially when accelerators are thrown into the mix.

    It was with all of this in mind that DARPA’s High Productivity Computing Systems (HPCS) project rolled out in 2009 to support higher performance but more usable HPC systems. This is the era that spawned systems like Blue Waters, for instance, and various co-design efforts from IBM and Intel to make parallelism within broader reach to the …

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  • Julia Language Delivers Petascale HPC Performance

    November 28, 2017 Rob Farber

     

    Written in the productivity language Julia, the Celeste project—which aims to catalogue all of the telescope data for the stars and galaxies in in the visible universe—demonstrated the first Julia application to exceed 1 PF/s of double-precision floating-point performance (specifically 1.54 PF/s).

    The project took advantage of all 9300 Intel Xeon Phi Phase II nodes on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer.

    Even in HPC terms, the Celeste project is big, as it created the first comprehensive catalog of visible objects in our universe by processing 178 terabytes of SDSS (Sloan Digital …

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  • Dirt Simple HPC: Making the Case for Julia

    January 26, 2016 Douglas Eadline

    Choosing a programming language for HPC used to be an easy task. Select an MPI version then pick Fortran or C/C++. Today there are more choices and options, but due to the growth of both multi-core processors and accelerators there is no general programming method that provides an “easy” portable way to write code for HPC (and there may never be). Indeed, it seems writing applications is getting more complicated because HPC projects often require a combination of messaging (MPI), threads (OpenMP), and accelerators (Cuda, OpenCL, OpenACC). In other words, to the HPC code practitioner things seem to be getting …

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