Tag: GPUs

AMD’s Exascale Strategy Hinges on Heterogeneity

Jul 29, 2015 |

In a recent IEEE Micro article, a team of engineers and computers scientists from chipmaker Advanced Micro Devices (AMD) detail AMD’s vision for exascale computing, which in its most essential form combines CPU-GPU integration with hardware and software support to facilitate the running of scientific workloads on exascale-class systems.

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IDC: The Changing Face of HPC

Jul 16, 2015 |

At IDC’s annual ISC breakfast there was a good deal more than market update numbers although there were plenty of those: “We try to track every server sold, every quarter, worldwide,” said Earl Joseph, IDC program vice president and executive director HPC User Forum. Perhaps more revealing and as important this year was IDC’s unveiling Read more…

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NVIDIA Wades Farther into Deep Learning Waters

Jul 7, 2015 |

Continuing the machine learning push that set the tone for this year’s GPU Technology Conference, NVIDIA is refreshing its GPU-accelerated deep learning software in tandem with the 2015 International Conference on Machine Learning (ICML), one of the major international conferences focused on the burgeoning domain. The announcement involves updates to CUDA, cuDNN, and DIGITS. Altogether the new features provide significant Read more…

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Shining a Light on SKA’s Massive Data Processing Requirements

Jun 4, 2015 |

One of the many highlights of the fourth annual Asia Student Supercomputer Challenge (ASC15) was the MIC optimization test, which this year required students to optimize a gridding algorithm used in the world’s largest international astronomy effort, the Square Kilometre Array (SKA) project. Gridding is one of the most time-consuming steps in radio telescope data processing. Read more…

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Tech Giants Battle for Image Recognition Supremacy

May 13, 2015 |

The race to exascale isn’t the only rivalry stirring up the advanced computing space. Artificial intelligence sub-fields, like deep learning, are also inspiring heated competition from tech conglomerates around the globe. When it comes to image recognition, computers have already passed the threshold of average human competency, leaving tech titans, like Baidu, Google and Microsoft, vying to Read more…

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Machine Learning Guru Sees Future in Multi-GPU Clusters

Apr 30, 2015 |

Machine learning has made enormous strides in the few years, owing in large part to powerful and efficient parallel processing provided by general-purpose GPUs. The latest example of this trend is exemplified by a partnership between New York University’s Center for Data Science and NVIDIA. The mission, says the pair, is to develop next-gen deep learning Read more…

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Summit Puts 13 Code Projects Into Readiness Program

Apr 15, 2015 |

When the Oak Ridge National Laboratory’s Summit supercomputer powers up in 2018, it will provide the Department of Energy (DOE) research community with 150 to 300 peak petaflops of computational performance. To extract the highest benefit from this multi-million dollar machine that will be five to ten times the capability of the current fastest US Read more…

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Something for Everyone at GPU Technology Conference

Mar 23, 2015 |

Once relegated to the category of specialized gaming hardware, today’s graphics processors are solving some of the world’s toughest computing problems. During GTC15 last week in San Jose, the full breadth and depth of session topics provided even more evidence of how far graphics processors have come from their gaming roots. And while this year deep Read more…

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GPU-Powered Simulations Advance Heart Research

Feb 5, 2015 |

With heart disease topping the list as the number one cause of death worldwide, heart rhythms disorders, or arrhythmias, are worthy of serious concern. Hoping to halt the devastating effects of the disorder is the Victor Chang Cardiac Research Institute (VCCRI) in Darlinghurst, Australia, where researchers are using a supercomputer to better understand, diagnose and Read more…

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Baidu Supercomputer Tops Google in Image Recogition

Jan 20, 2015 |

In an effort to oust Google from its the top spot in image recognition, Baidu, Inc. has dedicated a supercomputer to what it claims to be the world’s most accurate computer vision system. Using the ImageNet object classification benchmark, the Chinese search engine company claims that their system managed a 5.98 percent error rate, which Read more…

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