“The basic idea of deep learning is to automatically learn to represent data in multiple layers of increasing abstraction, thus helping to discover intricate structure in large datasets. NVIDIA has invested in SaturnV, a large GPU-accelerated cluster, (#28 on the November 2016 Top500 list) to support internal machine learning projects. After an introduction to deep learning on GPUs, we will address a selection of open questions programmers and users may face when using deep learning for their work on these clusters.”
Today Fujitsu announced that it has received RIKEN’s order for the “Deep learning system,” one of the largest supercomputers in Japan specializing in AI research. “NVIDIA DGX-1, the world’s first all-in-one AI supercomputer, is designed to meet the enormous computational needs of AI researchers,” said Jim McHugh, VP & GM at Nvidia. “Powered by 24 DGX-1s, the RIKEN Center for Advanced Intelligence Project’s system will be the most powerful DGX-1 customer installation in the world. Its breakthrough performance will dramatically speed up deep learning research in Japan, and become a platform for solving complex problems in healthcare, manufacturing and public safety.”
In this video, NYU researchers describe their plans to advance deep learning with their new Nvidia DGX-1 AI supercomputer. “The DGX-1 is going to be used in just about every research project we have here,” said Yann LeCun, founding director of the NYU Center for Data Science and a pioneer in the field of AI. “The students here can’t wait to get their hands on it.”
Today NVIDIA announced APAC’s first deployment of NVIDIA DGX-1 deep learning supercomputers CSIRO in Australia. “There is a growing interest from research groups to adopt machine learning techniques to support their projects,” said Angus Macoustra, executive manager for Scientific Computing at CSIRO. “CSIRO research projects are already using the DGX-1 systems, and in time, it is expected that machine learning will have applicability across all our areas of research and be used by hundreds of researchers.”
This week Nvidia CEO Jen-Hsun Huang hand-delivered one of the company’s new DGX-1 Machine Learning supercomputers to the OpenAI non-profit in San Francisco. “The DGX-1 is a huge advance,” OpenAI Research Scientist Ilya Sutskever said. “It will allow us to explore problems that were completely unexplored before, and it will allow us to achieve levels of performance that weren’t achievable.”
In this video from ISC 2016, Marc Hamilton from Nvidia describes the new DGX-1 Deep Learning Supercomputer. “The NVIDIA DGX-1 is the world’s first purpose-built system for deep learning with fully integrated hardware and software that can be deployed quickly and easily. Its revolutionary performance significantly accelerates training time, making the NVIDIA DGX-1 the world’s first deep learning supercomputer in a box.”
In this special guest feature, Robert Roe from Scientific Computing World describes why Nvidia is in the driver’s seat for Deep Learning. “Nvidia CEO Jen-Hsun Huang’s theme for the opening keynote was based on “a new computing model.” Huang explained that Nvidia builds computing technologies for the most demanding computer users in the world and that the most demanding applications require GPU acceleration. ‘The computers you need aren’t run of the mill. You need supercharged computing, GPU accelerated computing’ said Huang.”
The NVIDIA DGX-1 features up to 170 teraflops of half precision (FP16) peak performance, 8 Tesla P100 GPU accelerators with 16GB of memory per GPU, 7TB SSD DL Cache, and a NVLink Hybrid Cube Mesh. Packaged with fully integrated hardware and easily deployed software, it is the world’s first system built specifically for deep learning and with NVIDIA’s revolutionary, Pascal-powered Tesla P100 accelerators, interconnected with NVIDIA’s NVLink. NVIDIA designed the DGX-1 to meet the never-ending computing demands of artificial intelligence and claims it can provide the throughput of 250 CPU-based servers delivered via a single box.