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Tag: GPGPU

GPUs Advance Deep Learning

Sep 18, 2014 |

Over the last decade, GPU-acceleration techniques have infiltrated the high-end of supercomputing, but increased adoption of GPUs is occurring in other compute-driven disciplines too, like deep learning, one of the fastest growing segments of the machine learning field. The trend toward accelerated computing reached a new high at last week’s ImageNet Large Scale Visual Recognition Challenge. The event, Read more…

NVIDIA Boasts ‘Compelling HPC Solution’

Aug 20, 2014 |

Today marks the official release of the NVIDIA CUDA Toolkit version 6.5, which had previously been only available in its pre-release form. In a company blog post, NVIDIA’s Chief Technologist for GPU Computing Software Mark Harris covers the toolkit’s new features and improvements, including “support for CUDA Fortran in developer tools, user-defined callback functions in Read more…

Adapting Algorithms to Modern Hybrid Architectures

Aug 13, 2014 |

Technology, like other facets of life, commonly experiences cycles of rapid change followed by periods of relative stability. Computing has entered a stage of increased architectural diversity, as evidenced by the rise of accelerators, coprocessors, and other alternatives, like ARM processors. An international team of researchers explores how these various supercomputing architectures perform on parallelized turbulent Read more…

Building Parallel Code with Hybrid Fortran

Jul 31, 2014 |

Over at the Typhoon Computing blog, Michel Müller addresses a topic that is top of mind to many HPC programmers: porting code to accelerators. Fortran programmers porting their code to GPGPUs (general purpose graphics processing units) have a new tool at their disposal, called Hybrid Fortran. Müller shows how this open source framework can enhance portability without sacrificing performance and maintainability. From the blog (editor’s note: the site Read more…

ASC14 Marks Seventh Win for GPUs

May 29, 2014 |

The past decade has seen a sharp rise in heterogenous computing, processing or coprocessing using more than one processor type. One of the most prominent examples of heterogenous elements in HPC is the GPU computing ecosystem that has been fostered by NVIDIA and AMD. General-purpose GPU (GPGPU) adoption has become widespread in HPC, and student supercomputing Read more…

HPC Boosts Medical Physics

Sep 5, 2013 |

When it comes to employing physics in medicine, there are two major fields in terms of their relevance in clinical practice: medical imaging and radiation therapy. An Argentinian research duo addresses how these domains can benefit from high-performance computing techniques…

The Modern GPU: A Graphic History

Aug 21, 2013 |

What do the Atari 2600 and Tianhe-1A have in common? It may be difficult to imagine, but both systems are examples of the use of cutting-edge graphic processers for their times. This demonstrates the fascinating evolution of the GPU, which today is one of the most critical hardware components of supercomputer architectures.

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.

Penguin Pushes Envelope on Compute Density

Mar 21, 2013 |

<img src=”http://media2.hpcwire.com/hpcwire/Penguin_Computing_logo_172x.jpg” alt=”” width=”101″ height=”59″ />Penguin Computing keeps finding increasing demand for servers that go heavy on the GPUs (or other coprocessors). Based on feedback from one such customer, it has designed the Relion 2808GT server, which it says now has the highest compute density of any server on the market.

The Week in HPC Research

Feb 14, 2013 |

<img style=”float: left;” src=”http://media2.hpcwire.com/hpcwire/research_globe_150x.jpg” alt=”” width=”95″ height=”89″ />The top research stories of the week have been hand-selected from major science centers, prominent journals and leading conference proceedings. Here’s another diverse set of items, including whole brain simulation; a look at High Performance Linpack; the coming GPGPU cloud paradigm; heterogenous GPU programming; and a comparison of accelerator-based servers.

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