{"id":122944,"date":"2021-08-17T15:00:15","date_gmt":"2021-08-17T15:00:15","guid":{"rendered":"https:\/\/blogs.nvidia.com\/?p=52000"},"modified":"2021-08-17T15:00:15","modified_gmt":"2021-08-17T15:00:15","slug":"big-computer-on-campus-universities-graduate-to-ai-super-systems","status":"publish","type":"post","link":"https:\/\/webdomino.net\/index.php\/nvidia\/big-computer-on-campus-universities-graduate-to-ai-super-systems\/","title":{"rendered":"Big Computer on Campus: Universities Graduate to AI Super Systems"},"content":{"rendered":"

This back-to-school season, many universities are powering on brand new AI supercomputers. Researchers and students working in fields from basic science to liberal arts can\u2019t wait to log on.<\/p>\n

\u201cThey would like to use it right now,\u201d said James Wilgenbusch, director of research computing at the University of Minnesota, speaking of Agate, an accelerated supercomputer <\/a>Hewlett Packard Enterprise is building.<\/p>\n

It\u2019s one of at least eight new academic systems lighting up around the world \u2014 four in America\u2019s heartland and two in the U.K.<\/p>\n

Before the semester\u2019s end, Agate will deliver seven petaflops of umph. It will crunch through \u201cresearch from socio-economic trends to celestial objects \u2014 it really will serve the full gamut,\u201d he said of the system to be housed at the Minnesota Supercomputing Institute (MSI) that will link 265 NVIDIA A100 Tensor Core GPUs<\/a> on an NVIDIA HDR 200Gb\/s InfiniBand network.<\/p>\n

Agate will serve about 4,500 users, working under a thousand principal investigators who since January have already run a whopping 138,612 GPU-accelerated jobs on MSI\u2019s existing systems.<\/p>\n

\"Agate<\/a>
Getting fired up: The Agate supercomputer in Chippewa Falls undergoes burn-in testing. (Picture courtesy HPE)<\/figcaption><\/figure>\n

\u201cWe\u2019re seeing annual user growth, the greatest amount of it in life sciences and liberal arts \u2014 fields like geology, history, poli-sci, marketing \u2014 anywhere people have vast quantities of unstructured data and they\u2019re attempting to make sense of it,\u201d he said.<\/p>\n

AI Supercomputer Helps Fight COVID<\/b><\/h2>\n

Demonstrating the power of accelerated computing, the Minnesota Department of Health reserved a portion of MSI\u2019s system in its fight against COVID-19. It\u2019s sequencing genomes for contract tracing and to track variants of the coronavirus.<\/p>\n

\u201cCollaborations like this make the role of universities in innovation and life saving more obvious to the public,\u201d said Wilgenbusch, pointing to articles in a Minneapolis newspaper.<\/p>\n

Virtual GPUs Power Indiana Classrooms<\/b><\/h2>\n

Some 600 miles southeast, Indiana University (IU) is standing up two AI supercomputers packing a total of 616 A100 GPUs.<\/p>\n

Big Red 200, built by Hewlett Packard Enterprise, will serve the nine IU campuses. Jetstream-2, built by Dell Technologies, will power work at several partner institutions from Cornell to the University of Hawaii.<\/p>\n

Tapping the A100\u2019s ability to offer fractions of a processor, Jetstream-2 will host classes with hundreds of students, each using a slice of a GPU\u2019s performance to learn popular AI skills like image classification. One IU researcher presented a paper<\/a> last November benchmarking the virtual GPU capability.<\/p>\n

\u201cNow whole classrooms can be trained in one go, so more people get access,\u201d said Winona Snapp-Childs, chief operating officer of IU\u2019s Pervasive Technology Institute and leader of an AI-for-everyone initiative.<\/p>\n

A Vision of Ubiquitous AI<\/b><\/h2>\n

More than 2,500 students use IU\u2019s current GPU-accelerated systems. They ran more than 40 percent of the work for the university\u2019s record $1 billion of research contracts and grants spread across 178 departments last year.<\/p>\n

\u201cFunding agencies realize the importance of machine learning in academic fields across the spectrum,\u201d said Snapp-Childs.<\/p>\n

\u201cAI and accelerated computing help push the boundaries of science, and I can imagine they will come to handle half of our research over the next 5 to 10 years as these techniques become ubiquitous and imperative for research,\u201d she added.<\/p>\n

The work spans a spectrum that can set your head spinning. Researchers are tapping AI for everything from tracking down COVID misinformation on social networks to studying the genome of rice to improve harvests.<\/p>\n

Delta Pioneers Accessible Supercomputing<\/b><\/h2>\n

Next door, the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign is expanding use of accelerated computing with Delta, an AI supercomputer packing more than 800 A100 GPUs.<\/p>\n

\u201cWe will help emerging research areas such as computational archaeology and digital agriculture take advantage of new computing methods and hardware while making advanced systems more usable and accessible to a broad community of researchers,\u201d said William Gropp, a principal investigator and NCSA director who oversees Delta.<\/p>\n

The system is one way the National Science Foundation is spreading GPU-based computing as a common tool for accelerating research. The work includes an initiative to make Delta and future systems more accessible to people with disabilities.<\/p>\n

Florida Spreads the AI Sunshine<\/b><\/h2>\n

A thousand miles south, the University of Florida\u2019s HiPerGator AI<\/a> system provides another shining example of accelerated computing.<\/p>\n

In a recent article<\/a> in the Gainesville Sun, provost Joe Glover said the system will spread AI skills much like Henry Ford\u2019s first assembly line made cars affordable for Americans. The university aims to add 100 AI-focused faculty to make machine learning ubiquitous across its curriculum with a stated goal of creating 30,000 AI-enabled graduates by 2030.<\/p>\n

HiPerGator AI linked a whopping 1,120 A100 GPUs on a HDR 200Gb\/s InfiniBand network to take the No. 22 spot in the latest TOP500 list<\/a> of the world\u2019s fastest supercomputers. It was built in just a few weeks thanks to its use of the NVIDIA DGX SuperPOD<\/a> reference architecture, a recipe for stacking NVIDIA DGX systems in Lego-like style.<\/p>\n

Studying Abroad: AI Supercomputing\u2019s Far Reach<\/b><\/h2>\n

These five AI supercomputers represent just a few peaks in a rising range that crisscrosses the U.S. and Europe.<\/p>\n