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Compilers and More: The Past, Present and Future of Parallel Loops

Apr 6, 2015 |

Let’s talk about parallel loops. In parallel computing, we’ve been designing, describing, implementing and using parallel loops almost since the beginning. The advantage of parallel loops (over almost all other forms of parallelism) is that the parallelism scales up with the data set size or loop trip count (number of iterations). So what exactly is a parallel Read more…

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HSA Spec Lays Out Architecture for Acceleration

Mar 17, 2015 |

The Heterogeneous System Architecture (HSA) Foundation marked what it says will be known as a watershed event in heterogeneous computing with the release of the HSA 1.0 specification. The new spec, nearly three years in the making, brings the foundation closer to its goal of enabling write-once run-anywhere programming for accelerated computing on devices ranging from the Read more…

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A Comparison of Heterogeneous and Manycore Programming Models

Mar 2, 2015 |

The high performance computing (HPC) community is heading toward the era of exascale machines, expected to exhibit an unprecedented level of complexity and size. The community agrees that the biggest challenges to future application performance lie with efficient node-level execution that can use all the resources in the node. These nodes might be comprised of Read more…

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BSC, Intel Extend Exascale Research Effort

Feb 17, 2015 |

Intel’s efforts to advance exascale computing concepts received a boost with the extension of the company’s research collaboration with the Barcelona Supercomputing Center (BSC) – one of four Intel exascale labs in Europe. Begun in 2011 and now extended to September 2017, the Intel-BSC work focuses on scalability issues with parallel applications. “[A major goal] Read more…

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Run Anywhere Big Data and HPC Workloads

Feb 9, 2015 |

A classical problem in software development is how you manage your software applications dependencies. This extends all the way from the time you program your application to the time you run or deploy it. The typical application is almost always dependent on specific versions of libraries, compilers or the OS level package management system. Organizations Read more…

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Short Takes

The Portability Mandate

Jul 24, 2014 |

Argonne National Laboratory recently published several sessions from its Summer 2013 Extreme-Scale Computing program to YouTube. One of these is a lesson on combining performance and portability presented by Argonne Assistant Computational Scientist Jeff Hammond. For some reason the video image does not match the lecture, but you will find a link to Hammond’s slide deck here. Read more…

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Parallel Computing Trends

Jul 22, 2014 |

One of the most pressing issues faced by the HPC community is how to go about attracting and training the next generation of HPC users. The staff at Argonne National Laboratory is tackling this challenge head on by holding an intensive summer school in extreme-scale computing. One of the highlights of the 2013 summer program was a Read more…

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The Case for a Parallel Programming Alternative

Jul 2, 2014 |

Cray engineers have been working on a new parallel computing language, called Chapel. Aimed at large-scale parallel computing environments, Chapel was designed with a focus on productivity and accessibility. The project originated from the DARPA High Productivity Computing Systems (HPCS) program, which challenged HPC vendors to improve the productivity of high-end computing systems. To explain Read more…

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Programmability Matters

Jun 30, 2014 |

While discussions of HPC architectures have long centered on performance gains, that is not the only measure of success, according to Petteri Laakso of Vector Fabrics. Spurred by ever-proliferating core counts, programmability is taking on new prominence. Vector Fabrics is a Netherlands-based company that specializes in multicore software parallelization tools, so programmability is high on Read more…

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An Easier, Faster Programming Language?

Jun 18, 2014 |

The HPC community has turned out supercomputers surpassing tens of petaflops of computing power by stringing together thousands of multicore processors, often in tandem with accelerators like NVIDIA GPUs and Intel Phi coprocessors. Of course, these multi-million dollar systems are only as useful as the programs that run on them, and developing applications that can Read more…

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Off the Wire