In this video, Oded Green from NVIDIA unboxes a DGX-1 supercomputer at the College of Computing Data Center at Georgia Tech. “And while the DGX-1 arriving at Georgia Tech for student-use is exciting enough, there is cause for more celebration as a DGX Station also arrived this year as part of a new NVIDIA Artificial Intelligence Lab (NVAIL) grant awarded to CSE. The NVAIL grant focuses on developing multi-GPU graph analytics and the DGX station is constructed specifically for data science and artificial intelligence development.”
Volkov and Demmel Paper on GPUs Wins SC19 Test of Time Award
August 14, 2019 by Leave a Comment
Today SC19 announced the winners of the Test of Time Award. The annual award recognizes an outstanding paper that has deeply influenced the HPC discipline. We are pleased to announce the selection of the SC08 paper, “Benchmarking GPUs to Tune Dense Linear Algebra”, by Vasily Volkov (NVIDIA) and James Demmel (UC Berkeley) as the SC19 ToTA winner.
The paper was deemed deserving of the SC19 ToTA due to its first-of-its-kind vision of GPU architectures as a vector machine. By building on this vision, Volkov and Demmel defined techniques to achieve greater efficiency and performance.
Video: NVIDIA Accelerates Conversational AI
August 14, 2019 by Leave a Comment
In this video, NVIDIA’s Bryan Catanzaro explains how recent breakthroughs in natural language understanding bring us one step closer to conversational AI. “Today NVIDIA announced breakthroughs in language understanding that allow businesses to engage more naturally with customers using real-time conversational AI. “NVIDIA’s groundbreaking work accelerating these models allows organizations to create new, state-of-the-art services that can assist and delight their customers in ways never before imagined.”
AMD to Power Two Cray CS500 Systems at Army Research Centers
August 8, 2019 by Leave a Comment
Today Cray announced that the U.S. Department of Defense (DOD) has selected two Cray CS500 systems for its High Performance Computing Modernization Program (HPCMP) annual technology procurement known as TI-18. The Army Research Lab (ARL) and the U.S. Army Engineering and Research Development Center (ERDC) will each deploy a Cray CS500 to help serve the U.S. through accelerated research in science and technology. The two contracts are valued at more than $46M and the CS500 systems are expected to be delivered to ARL and ERDC in the fourth quarter of 2019.
OSU Invests $2.6 million in AI Computing Resources
August 1, 2019 by Leave a Comment
Oregon State University’s College of Engineering is accelerating its work in artificial intelligence, robotics, driverless vehicles and other areas by acquiring six advanced NVIDIA systems that give the college some of the most powerful computing resources among universities worldwide. “The computing power we now possess will accelerate our research in artificial intelligence and machine learning, while exposing our computer science students to the most advanced technology available in higher education.”
Exploring the Universe with the SKA Radio Telescope and CUDA
July 31, 2019 by Leave a Comment
In this video, Wes Armour from the Oxford eResearch Centre discusses the role of GPUs in processing large amounts of astronomical data collected by the Square Kilometre Array and how CUDA is the best suited option for their signal processing software. “The massive computational power of modern day GPUs allows code to perform algorithms such as de-dispersion, single pulse searching and Fourier Domain Acceleration Searching in real-time on very large data-sets which are comparable to those which will be produced by next generation radio-telescopes such as the SKA.”
Fujitsu to Deploy Gadi Supercomputer at NCI in Australia
July 29, 2019 by Leave a Comment
Today Fujitsu announced a contract to upgrade the Australia’s fastest supercomputer at NCI. Called “Gadi,” the new supercomputer will replace the NCI’s current supercomputer, Raijin, which was also provided by Fujitsu back in 2012. “The upgrade of this critical infrastructure will see Australia continue to play a leading role in addressing some of our greatest global challenges. This new machine will keep Australian research and the 5,000 researchers who use it at the cutting-edge.”
Accelerating High-Resolution Weather Models with Deep-Learning Hardware
July 26, 2019 by Leave a Comment
Sam Hatfield from the University of Oxford gave this talk at the PASC19 conference. “In this paper, we investigate the use of mixed-precision hardware that supports floating-point operations at double-, single- and half-precision. In particular, we investigate the potential use of the NVIDIA Tensor Core, a mixed-precision matrix-matrix multiplier mainly developed for use in deep learning, to accelerate the calculation of the Legendre transforms in the Integrated Forecasting System (IFS), one of the leading global weather forecast models.”
Video: Update on the Exascale Computing Project
July 25, 2019 by Leave a Comment
In this video, ECP Director Doug Kothe provides an update on the Exascale Computing Project. ECP has mission to ensure that a capable exascale computing ecosystem will come to fruition with the arrival of the nation’s first exascale systems. “Enduring legacy translates to having dozens of application technologies that will be used to tackle some of the toughest problems in DOE and the nation, and so the applications are now going to be positioned to address their challenge problems and in many cases help solve them or be a part of the solution.”
AI Approach Points to Bright Future for Fusion Energy
July 25, 2019 by 1 Comment
Researchers are using Deep Learning techniques on DOE supercomputers to help develop fusion energy. “Unlike classical machine learning methods, FRNN—the first deep learning code applied to disruption prediction—can analyze data with many different variables such as the plasma current, temperature, and density. Using a combination of recurrent neural networks and convolutional neural networks, FRNN observes thousands of experimental runs called “shots,” both those that led to disruptions and those that did not, to determine which factors cause disruptions.”
