{"id":1269,"date":"2021-11-30T08:28:25","date_gmt":"2021-11-30T08:28:25","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2021\/11\/30\/if-i-had-a-hammer-purdues-anvil-supercomputer-will-see-use-all-over-the-land\/"},"modified":"2021-11-30T08:28:25","modified_gmt":"2021-11-30T08:28:25","slug":"if-i-had-a-hammer-purdues-anvil-supercomputer-will-see-use-all-over-the-land","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2021\/11\/30\/if-i-had-a-hammer-purdues-anvil-supercomputer-will-see-use-all-over-the-land\/","title":{"rendered":"If I Had a Hammer: Purdue\u2019s Anvil Supercomputer Will See Use All Over the Land"},"content":{"rendered":"
\n

Carol Song is opening a door for researchers to advance science on Anvil, Purdue University\u2019s new AI-ready supercomputer, an opportunity she couldn\u2019t have imagined as a teenager in China.<\/p>\n

\u201cI grew up in a tumultuous time when, unless you had unusual circumstances, the only option for high school grads was to work alongside farmers or factory workers, then suddenly I was told I could go to college,\u201d said Song, now the project director of Anvil.<\/p>\n

And not just any college. Her scores on a national entrance exam opened the door to Tsinghua University, home to China\u2019s most prestigious engineering school.<\/p>\n

Along the way, someone told her computers would be big, so she signed up for computer science before she had ever seen a computer. She learned soon enough.<\/p>\n

\u201cWe were building hardware from the ground up, designing microinstructions and logic circuits, so I got to understand computers from the inside out,\u201d she said.<\/p>\n

Easing Access to Supercomputers<\/b><\/h2>\n

Skip forward a few years to grad school at the University of Illinois when another big door opened.<\/p>\n

While working in distributed systems, she was hired as one of the first programmers at the National Center for Supercomputing Applications, \u00a0one of the first sites in a U.S. program funding supercomputers that researchers shared.<\/p>\n

To make the systems more accessible, she helped develop alternatives to the crude editing tools of the day that displayed one line of a program at a time. And she helped pioneering researchers like Michael Norman create visualizations of their work.<\/p>\n

GPUs Add AI to HPC<\/b><\/h2>\n

In 2005, she joined Purdue, where she has helped manage nearly three dozen research projects representing more than $60 million in grants as a senior research scientist in the university\u2019s supercomputing center.<\/p>\n

\u201cAll that helped when we started defining Anvil. I see researchers\u2019 pain points when they are getting on a new system,\u201d said Song.<\/p>\n

Anvil links 1,000 Dell EMC PowerEdge C6525 server nodes with 2,000 of the latest AMD x86 CPUs and 64 NVIDIA A100 Tensor Core GPUs<\/a> on a NVIDIA Quantum InfiniBand<\/a> network to handle traditional HPC and new AI workloads.<\/p>\n

The system, built by Dell Technologies, will deliver 5.3 petaflops and half a million GPU cycles per year to tens of thousands of researchers across the U.S. working on the National Science Foundation\u2019s XSEDE network.<\/p>\n

Anvil Forges Desktop, Cloud Links<\/b><\/h2>\n

To harness that power, Anvil supports interactive user interfaces as well as the batch jobs that are traditional in high performance computing.<\/p>\n

\u201cResearchers can use their favorite tools like Jupyter notebooks and remote desktop interfaces so the cluster can look just like in their daily work environment,\u201d she said.<\/p>\n

Anvil will also support links to Microsoft Azure, so researchers can access its large datasets and commercial cloud-computing muscle. \u201cIt\u2019s an innovative part of this system that will let researchers experiment with creating workflows that span research and commercial environments,\u201d Song said.<\/p>\n

Fighting COVID, Exploring AI<\/b><\/h2>\n

More than 30 research teams have already signed up to be early users of Anvil.<\/p>\n

One team will apply deep learning to medical images to improve diagnosis of respiratory diseases including COVID-19. Another will build causal and logical check points into neural networks to explore why deep learning delivers excellent results.<\/p>\n

\u201cWe\u2019ll support a lot of GPU-specific tools like NGC<\/a> containers for accelerated applications, and as with every new system, users can ask for additional toolkits and libraries they want,\u201d she said.<\/p>\n

The Anvil team aims to invite industry collaborations to test new ideas using up to 10 percent of the system\u2019s capacity. \u201cIt\u2019s a discretionary use we want to apply strategically to enable projects that wouldn\u2019t happen without such resources,\u201d she said.<\/p>\n

Opening Doors for Science and Inclusion<\/b><\/h2>\n

Early users are working on Anvil today and the system will be available for all users in about a month.<\/p>\n

Anvil\u2019s opening day has a special significance for Song, one of the few women to act as a lead manager for a national supercomputer site.<\/p>\n

<\/p>\n

\"Carol<\/p>\n

<\/a>

Carol Song and Purdue\u2019s Anvil supercomputer<\/figcaption><\/figure>\n

\u201cI\u2019ve been fortunate to be in environments where I\u2019ve always been encouraged to do my best and given opportunities,\u201d she said.<\/p>\n

\u201cAround the industry and the research computing community there still aren\u2019t a lot of women in leadership roles, so it\u2019s an ongoing effort and there\u2019s a lot of room to do better, but I\u2019m also very enthusiastic about mentoring women to help them get into this field,\u201d she added.<\/p>\n

Purdue\u2019s research computing group shares Song\u2019s enthusiasm about getting women into supercomputing. It\u2019s home to one of the first chapters of the international Women in High-Performance Computing<\/a> organization.<\/p>\n

Purdue\u2019s Women in HPC chapter sent an all-female team to a student cluster competition at SC18. It also hosts outside speakers, provides travel support to attend conferences and connects students and early career professionals to experienced mentors like Song.<\/p>\n

Pictured at top: Carol Song, Anvil\u2019s <\/i>principal investigator (PI) and project director along with Anvil co-PIs (from left) Rajesh Kalyanam, Xiao Zhu and Preston Smith.\u00a0<\/i><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

https:\/\/blogs.nvidia.com\/blog\/2021\/11\/29\/purdue-anvil-supercomputer\/<\/p>\n","protected":false},"author":0,"featured_media":1270,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/1269"}],"collection":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/comments?post=1269"}],"version-history":[{"count":0,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/1269\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media\/1270"}],"wp:attachment":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media?parent=1269"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/categories?post=1269"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/tags?post=1269"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}