ALCF – The March toward Exascale

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In this video from the HPC User Forum in Detroit, David E. Martin presents: ALCF – The March toward Exascale.

In 2021, the Argonne Leadership Computing Facility (ALCF) will deploy Aurora, a new Intel-Cray system. Aurora, will be capable of over 1 exaflops. It is expected to have over 50,000 nodes and over 5 petabytes of total memory, including high bandwidth memory. The Aurora architecture will enable scientific discoveries using simulation, data and learning. The detailed architecture of Aurora is protected by RSNDA (Restricted Secret Nondisclosure Agreement).

Before the plan to shift from a 2018-delivery (180 petaflops) Aurora based on third-generation Intel Xeon Phi processors to the 2021-delivery (1 exaflops) Aurora, we had already selected 10 Aurora ESP projects. These will continue, and serve as the Simulation based projects targeting Aurora 2021 (A21). This is reflected in the topmost, red bar in the timeline figure. An important part of the shift to A21 is the shift from primarily traditional, simulation-based computing at ALCF to expanded scope including data-centric and machine/deep learning projects. We now refer to Simulation, Data, and Learning as the “three pillars” of leadership computing going forward. This call for proposals is for projects in the Data and Learning pillars.

For the Aurora Early Science Program (ESP) Data and Learning call, we will select 10 new projects, all chosen competitively based on this call for proposals. With this CFP, we are specifically targeting applications in the areas of Data and Learning. These should have strong aspects of data science (Big Data, data-intensive computing, experimental/observational/simulation data analytics, etc.) and/or machine learning (deep learning, neural networks, discovery of patterns and reduced models for scientific data and/or simulation modeling, etc.). Cross-cutting proposals targeting the convergence of simulation, data and learning are very much encouraged.

With Aurora being a dramatically bigger and faster machine than Theta or Mira, the three months of pre-production Early Science time will be a large and valuable allocation of core-hours, with the potential for truly unprecedented computational science—as well as being the United States’ first exascale system. ALCF will fully fund 10 postdoctoral appointees for Aurora ESP—one for each selected project.

David Martin is Manager, Industry Partnerships and Outreach at the Argonne Leadership Computing Facility at Argonne National Laboratory, where he works with industrial users to harness high performance computing and take advantage of the transformational capabilities of modeling and simulation. David brings broad industry and research experience to ALCF. Prior to joining ALCF, David led IBM’s integration of internet standards, grid and cloud computing into offerings from IBM’s Systems and Technology Group. Before IBM, David managed networks and built network services for the worldwide high-energy physics community at Fermilab. David began his career at AT&T Bell Laboratories, doing paradigm-changing work in software engineering and high-speed networking. David has a BS from Purdue and an MS from the University of Illinois at Urbana-Champaign, both in Computer Science.

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