Tag: parallel computing

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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Argonne’s Paul Messina on Training for Extreme-Scale

Mar 12, 2015 |

Paul Messina, director of science for the Argonne Leadership Computing Facility (ALCF), discusses the primary objectives, curriculum and importance of the Argonne Training Program on Extreme-Scale Computing (ATPESC), now in its third year. HPCwire: Can you give us an overview of the Argonne Training Program on Extreme-Scale Computing (ATPESC)? Paul Messina: Absolutely, Tiffany. The ATPESC 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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The Democratization of Parallel Computing

Aug 20, 2014 |

Virginia Tech College of Engineering Professor Wu Feng has a vision to broadly apply parallel computing to advance science and address major challenges. A recent expose on Feng’s work details his involvement with the NSF, Microsoft, and the Air Force using innovative computing techniques to solve problems. “Delivering personalized medicine to the masses is just 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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Stanford Lights Up One Million Sequoia Cores

Jan 28, 2013 |

<img style=”float: left;” src=”http://media2.hpcwire.com/hpcwire/Stanford_jet_noise_simulation_150x.jpg” alt=”” width=”95″ height=”54″ />The 20 petaflop, third-generation IBM BlueGene system, Sequoia, may be the number two supercomputer according to the latest TOP500 rankings, but when it comes to max core usage, Sequoia has apparently set a new record. A team of Stanford engineers harnessed one million of Sequoia’s nearly 1.6 CPUs in parallel to solve a sophisticated fluid dynamics problem.

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Kepler GPU Makes Quick Work of Quicksort

Sep 13, 2012 |

Dynamic parallelism enables the graphics processor to act more like a CPU.

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Intel Adds Programming Support for Latest Silicon

Sep 6, 2012 |

<img style=”float: left;” src=”http://media2.hpcwire.com/hpcwire/Parallel_Studio_Cluster_XE_2013_small.bmp” alt=”” width=”146″ height=”96″ />We’re only a little more than halfway through 2012, but Intel has already announced the 2013 versions Parallel Studio XE and Cluster Studio XE, two software suites that support x86-based parallel programming for high performance computing and beyond. Intel refreshes their software development offerings each year at about this time to sync up its tool support with the latest and greatest silicon and to add new features for developers.

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Microsoft Cranks its AMP

Feb 7, 2012 |

Software maker offers heterogeneous computing in a C++ wrapper.

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