NVIDIA and Microsoft have announced that Microsoft Azure is now supported on the NVIDIA GPU Cloud (NGC) platform.
Google has expanded its NVIDIA GPU offerings on the Google Cloud Platform. These include:
- Performance boost with the public launch of NVIDIA P100 GPUs in beta
- NVIDIA Tesla K80 GPUs available on Google Compute Engine
- Introduction of sustained use discounts on both the Tesla K80 and P100 GPUs
According to a Google Cloud Platform blog, cloud GPUs can accelerate workloads including machine learning training and inference, geophysical data processing, simulation, seismic analysis, molecular modeling, genomics and many more high performance compute use cases.
NVIDIA and Microsoft are working on a new hyperscale GPU accelerator that will provide hyperscale data centres with a fast, flexible path for artificial intelligence (AI).
The new HGX-1 hyperscale GPU accelerator is an open-source design released in conjunction with Microsoft’s Project Olympus.
HGX-1 does for cloud-based AI workloads what ATX — Advanced Technology eXtended — did for PC motherboards when it was introduced more than two decades ago. It establishes an industry standard that can be rapidly and efficiently embraced to help meet surging market demand.
RIKEN, Japan’s largest comprehensive research institution, will have a new supercomputer for deep learning research in April. Built by Fujitsu using 24 NVIDIA DGX-1 AI systems, the new machine will accelerate the application of artificial intelligence (AI) to […]
Tokyo Institute of Technology plans to create Japan’s fastest AI supercomputer, which is will deliver more than twice the performance of its predecessor to slide into the world’s top 10 fastest systems.
Called Tsubame 3.0, it will use Pascal-based NVIDIA P100 GPUs that are nearly three times as efficient as their predecessors, to reach an expected 12.2 petaflops of double precision performance.
Tsubame 3.0 will excel in AI computation with more than 47 PFLOPS of AI horsepower. When operated with Tsubame 2.5, it is expected to deliver 64.3 PFLOPS, making it Japan’s highest performing AI supercomputer.
NVIDIA’s new DGX SATURNV supercomputer is ranked the world’s most efficient — and 28th fastest overall — on the latest Top500 list of supercomputers.
Powered by new Tesla P100 GPUs, it delivers 9.46 gigaflops/watt — a 42 percent improvement from the 6.67 gigaflops/watt delivered by the most efficient machine on the Top500 list released last June.
Compared with a supercomputer of similar performance, the Camphore 2 system, which is powered by Xeon Phi Knights Landing, SATURNV is 2.3x more energy efficient.hat efficiency is key to building machines capable of reaching exascale speeds — that’s 1 quintillion, or 1 billion billion, floating-point operations per second. Such a machine could help design efficient new combustion engines, model clean-burning fusion reactors, and achieve new breakthroughs in medical research.
Australia’s federal research agency Commonwealth Scientific and Industrial Research Organisation (CSIRO) has become the first in Asia-Pacific to deploy the NVIDIA DGX-1 deep learning supercomputers.
Installed in CSIRO’s Canberra data centre, the two supercomputers will expand the capability of Australian scientists and broaden the science impact possibilities for the nation.
The NVIDIA DGX-1 is the world’s first deep learning supercomputer to meet the computing demands of artificial intelligence. It enables researchers and data scientists to easily harness the power of GPU-accelerated computing to create a new class of computers that learn, see and perceive the world as humans do.
NVIDIA has introduced the NVIDIA Tesla P100 GPU, an advanced hyperscale data centre accelerator that can enable a new class of servers that can deliver the performance of hundreds of CPU server nodes.
Today’s data centres process large numbers of transactional workloads, such as web services. But they are inefficient at next-generation artificial intelligence and scientific applications, which require ultra-efficient, lightning-fast server nodes.
Based on the new NVIDIA Pascal GPU architecture, the Tesla P100 provides the performance and efficiency needed to power the computationally demanding applications. It delivers over a 12x increase in neural network training performance compared with a previous-generation NVIDIA Maxwell-based solution.