The rapid emergence of AI and machine learning within the HPC and advance scale computing industries looks to be a dominant topic – from vendor product announcements to analyst market forecasts to end user presentations – at next week’s SC16 conference in Salt Lake City.

The AI theme starts with the keynote address from former IBM Watson executive Dr. Katharine Frase, until recently head of strategy and business development for IBM’s Watson Education unit, who will talk about the new human-computer decision making partnership that AI is enabling.

“The price of computing, the density of computing, has improved so much that we can get enough circuits firing to have a system that looks like it’s reading and learning,” Frase told EnterpriseTech. “And there’s the recognition that we as humans are great but fallible decision makers. There’s this notion coming out of cognitive science around the places where we bring bias to a problem, whereas a system does not have biases but also does not have some of the advantages that humans have. This is where a partnership between computers and humans can really move us forward.”

She added that cognitive computing has entered a new era in which we not only “revel in the facts of processing power and increased computing capacity and capability, but also unleash that transformational power on some of the most complex and multidimensional problems faced by humanity.” Frase will cite examples in healthcare, life sciences, education and financial services. The keynote will take place at 8:30 am, Tuesday, Nov. 15 in the ballroom at the Salt Palace Convention Center.

Many SC16 workshops, sessions and panel discussion will focus on technologies used in AI and machine learning strategies. Events that are specifically AI-oriented at SC16 include:

A consumer market-based discussion of AI will be offered on Thursday at 1:30 by Lei Wu of Ancestry.Com, who will deliver an end-user HPC Impact Showcase called “Using Machine Learning to Organize and Contextualize the Largest Consumer DNA Database in the World.” The session will look at how Ancestry builds a family history graph that reveals the connections between billions of people, locations around the world, and tens of thousands of historical events using machine learning.

“Machine Learning in HPC Environments,” a workshop on Monday, Nov. 14 from 9 a.m. to 12:30 p.m. led by Dr. Robert M. Patton of Oak Ridge National Laboratory; Dr. Barry Y. Chen of the Lawrence Livermore National Laboratory; and Dr. Lawrence Carin of Duke University. They will discuss extreme scale systems for machine learning for exploiting data parallelism, model parallelism, ensembles and parameter search.

A reception will be held on Tuesday at 5:15 in the lobby concourse of Exhibit Hall E, Booth 104, called “Toward Portable Machine Learning Kernels for Deep Neural Networks with Autotuning on Top of OpenCL and High Bandwidth Memory GPUs.” The event will be hosted by Jack Dongarra of the University of Tennessee and Oak Ridge National Laboratory; and Yaohung Tsai, Jakub Kurzak and Piotr Luszczek of the University of Tennessee.

Also Tuesday at 5:15, a Birds of a Feather session will be offered entitled “Distributed Machine Intelligence Using Tensorflow.” Tensorflow is the second-generation machine learning system from the Google Brain team, and it uses tensor notation to describe neural networks as stateful dataflow graphs. The session will be led by Karan Bhatia and Kevin Kissel of Google.

On Wednesday afternoon at 2 p.m., a paper will be presented by four researchers from Lawrence Livermore National Laboratory entitled “A Machine Learning Framework for Performance Coverage Analysis of Proxy Applications.” It will present novel machine-learning techniques to quantify the coverage of performance behaviors of parent codes by their proxy applications, which are written to represent subsets of performance behaviors of more complex applications.

In addition to the strong showing for AI content on this year’s agenda, we expect HPC vendors and other community partners to be making some major AI-themed announcements over the next seven days. Stay tuned…