Tag: programming

Exascale Resilience Turns a Corner

Jul 21, 2014 |

While advancing the field of HPC into the exascale era is beset by many obstacles, resiliency might be the most thorny of all. As the number of cores proliferate so too do the number of incorrect behaviors, threatening not just the operation of the machine, but the validity of the results as well. When you Read more…

Internship Program Fosters HPC Talent

May 21, 2014 |

One of the most pressing concerns in HPC circles continues to be a lack of qualified entrants to the field. Not to say there isn’t talent — the popularity and success of the student cluster challenges attest to that — but it’s not enough to span the gap. That’s why efforts to facilitate this unique skill Read more…

Compilers and More: Accelerated Programming

Dec 3, 2013 |

Having just returned from SC13, one burning issue is the choice of a standard approach for programming the next generation HPC systems. While not guaranteed, these systems are likely to be large clusters of nodes with multicore CPUs and some sort of attached accelerators. A standard programming approach is necessary to convince developers, and particularly Read more…

Programming for Unreliable Hardware

Nov 11, 2013 |

As transistors approach sub-atomic sizes, reliability is increasingly jeopardized. Chipmakers keep figuring out technical workarounds to the miniaturization problem; however, prevailing wisdom maintains that current manufacturing techniques will sooner or later run out of steam, and Moore’s Law – the prediction that has yielded huge increases in semiconductor performance for nearly five decades – will Read more…

Controlling Soft Errors at Scale

Oct 2, 2013 |

There are many important issues when it comes to advancing the field of HPC toward the exascale era, but among all these variables, there are about five or so sticking points that really stand-out: one of these is controlling for soft errors. As the number of cores per machine increases, incorrect behaviors, known as soft Read more…

Harlan Targets Complexity for GPGPU Programming

Jul 11, 2013 |

HPC programmers who are tired of managing low-level details when using OpenCL or CUDA to write general purpose applications for GPUs (GPGPU) may be interested in Harlan, a new declarative programming language designed to mask the complexity and eliminate errors common in GPGPU application development.

Research Roundup: Toward a More Efficient Cloud

May 10, 2013 |

In this week’s hand-picked assortment, researchers explore the path to more energy-efficient cloud datacenters, investigate new frameworks and runtime environments that are compatible with Windows Azure, and design a unified programming model for diverse data-intensive cloud computing paradigms.

The Week in HPC Research

May 2, 2013 |

We’ve scoured the journals and conference proceedings to bring you the top research stories of the week. This diverse set of items includes the latest CAREER award recipient; the push to bring parallel computing to the classroom; HPC in accelerator science; the emerging Many-Task Computing paradigm; and a unified programming model for data-intensive computing.

The Week in HPC Research

Apr 18, 2013 |

A giant leap in bone structure research paves the way for advances in osteoporosis treatment; details from UCSD’s Research CyberInfrastructure (RCI) Program reveal what PIs really want; and a cloud computing programming model puts the focus on predictable performance. Plus GPU-related research and more…

ARM Gets Behind Accelerator Programming Project

May 29, 2012 |

<img style=”float: left;” src=”http://media2.hpcwire.com/hpcwire/CARP_logo.png” alt=”” width=”123″ height=”69″ />ARM Holdings, along with seven other academic and industrial partners, is ramping up a European research project designed to bring accelerator programming to mainstream developers. Known as CARP (Correct and Efficient Accelerator Programming), the effort is focused on developing hardware-independent programming tools around OpenCL, the industry standard parallel computing environment for GPUs and other accelerators.