Tag: NVIDIA

Nvidia Launches Pascal GPUs for Deep Learning Inferencing

Sep 12, 2016 |

Already entrenched in the deep learning community for neural net training, Nvidia wants to secure its place as the go-to chipmaker for datacenter inferencing. At the GPU Technology Conference (GTC) in Beijing Tuesday, Nvidia CEO Jen-Hsun Huang unveiled the latest additions to the Tesla line, Pascal-based P4 and P40 GPU accelerators, as well as new software all aimed at improving performance for inferencing workloads that undergird applications like voice-activated assistants, spam filters, and recommendation engines.

IBM Debuts Power8 Chip with NVLink and 3 New Systems

Sep 8, 2016 |

Not long after revealing more details about its next-gen Power9 chip due in 2017, IBM today rolled out three new Power8-based Linux servers and a new version of its Power8 chip featuring on-chip NVLink interconnect. One of the servers – Power S822LC for High Performance Computing – uses the new chip (Power8 with NVLink) to Read more…

IBM Advances Against x86 with Power9

Aug 30, 2016 |

After offering OpenPower Summit attendees a limited preview in April, IBM is unveiling further details of its next-gen CPU, Power9, which the tech mainstay is counting on to regain market share ceded to rival Intel. Built on GlobalFoundries 14nm finFET process technology, Power9 will be the centerpiece in Power-based servers starting in the second half of Read more…

NVIDIA Adds ‘Parker’ CPU to ‘Brain of Autonomous Vehicles’

Aug 25, 2016 |

NVIDIA’s autonomous vehicle strategy took a step forward this week with the announcement of a new mobile CPU, called “Parker,” offered to automakers as a single unit or integrated into the company’s DRIVE PX 2 platform, announced at CES earlier this year. Along with two Parker chips, DRIVE PX 2 will include two Pascal GPUs Read more…

Why 2016 Is the Most Important Year in HPC in Over Two Decades

Aug 23, 2016 |

In 1994, two NASA employees connected 16 commodity workstations together using a standard Ethernet LAN and installed open-source message passing software that allowed their number-crunching scientific application to run on the whole “cluster” of machines as if it were a single entity. Their do-it-yourself, McGyver-like efforts were motivated by a frustration with the pricing, availability Read more…

Intel to Acquire AI Startup Nervana Systems

Aug 9, 2016 |

If we needed another sign that Intel is serious about mining AI market opportunities, it came today when the chip company announced it had inked a “definitive agreement” to acquire artificial intelligence and deep learning company Nervana Systems. Financial terms haven’t been disclosed yet, but a source familiar with the deal told Recode it’s worth more Read more…

Alternative Supercomputing or How to Misuse a Computer

Jul 14, 2016 |

In 2008, the IBM Roadrunner supercomputer broke the petaflops barrier using the power of the heterogeneous Sony Cell Broadband Engine (BE) processor. A year prior, the Cell BE had already made its way into the consumer market as the engine inside the SonyPlaystation 3. The PS3’s accelerated design, Linux-capability and low price point…

NVIDIA Debuts PCIe-based P100; Broadens Aim at CPU Dominance

Jun 19, 2016 |

NVIDIA seems to be mounting a vigorous effort to dethrone the CPU as the leader of the processor pack for HPC and demanding datacenter workloads. That’s a tall order. Introduction at ISC 2016 of a PCIe-based version of is new Tesla P100 card is one element in the strategy. It should ease the upgrade path Read more…

OpenACC Adds Support for OpenPOWER; Touts Growing Traction

Jun 13, 2016 |

In a show of strength leading up to ISC the OpenACC standards group today announced its first OpenPOWER implementation, the addition of three new members – University of Illinois, Brookhaven National Laboratory, and Stony Brook University – and details of its expanding 2016 training schedule. Michael Wolfe, technical director of OpenACC, also talked with HPCwire about thorny compiler challenges still remaining as…

GPU-based Deep Learning Enhances Drug Discovery Says Startup

May 26, 2016 |

Sifting the avalanche of life sciences (LS) data for insight is an interesting and important challenge. Many approaches are used with varying success. Recently, improved hardware – primarily GPU-based – and better neural networking schemes are bringing deep learning to the fore. Two recent papers report the use of deep neural networks is superior to typical machine learning (support vector machine model) in sieving LS data for drug discovery and personalized medicine purposes.