Both teams made use of Summit’s ability to handle data-intensive first-principles equations

It has been a little over a year since the Oak Ridge Leadership Computing Facility (OLCF), a US Department of Energy (DOE) Office of Science User Facility, officially debuted the Summit supercomputer at DOE’s Oak Ridge National Laboratory (ORNL). Since then, the 200-petaflop IBM AC922 system has maintained its position as the smartest and most powerful supercomputer in the world for open science.

Powered by over 27,648 GPUs across 4,608 nodes, Summit has consistently made waves in the computing world for the unprecedented speed at which it can solve data-intensive, complex computational problems. It makes sense, then, that Summit would be the driving force behind this year’s 2019 Gordon Bell finalists.

The proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC19) revealed that two teams were named as finalists for the prestigious Gordon Bell Prize, presented each year at the conference to recognize researchers who have made significant strides in applying high-performance computing systems to scientific applications.

Both finalist teams used Summit to solve ab initio, or first-principles, calculations. These types of approaches attempt to solve the fundamental equations accurately within a specific domain—in this case, quantum mechanics and condensed matter physics—to predict the practical phenomena of interest with that domain.

“These first-principles equations are some of the leading problems in condensed matter and materials physics and are a huge topic in high-performance computing today, consuming lots of resources in data centers around the world,” said OLCF Director of Science Jack Wells. “It’s really satisfying to see these two projects pushing back the frontier of what we considered possible on Summit be selected as finalists for the Gordon Bell Prize.”

The Gordon Bell Prize winner will be announced in November at SC19 in Denver from among the following two finalists:

  • A Data-Centric Approach to Extreme-Scale Ab Initio Dissipative Quantum Transport Simulations.” Technological development means that researchers now have more compute power at their disposal than ever before. For this rapid progress to continue, however, certain technological barriers must be overcome—specifically the soon-to-become unmanageable problem of heat dissipation in compute units. The team, a group of researchers from ETH Zurich, is using Summit to improve the computational efficiency of an ab initio quantum transport solver designed to reveal the coupled electro-thermal properties of atomically resolved nanotransistors.
  • Fast, Scalable, and Accurate Finite-Element Based Ab Initio Calculations Using Mixed Precision Computing.” This study, led by researchers from the University of Michigan, in collaboration with researchers from ORNL and Los Alamos National Laboratory, works with first-principles calculations based on density functional theory in metallic systems. By employing finite-element discretization and mixed-precision strategies, these calculations can be sped up an order of magnitude faster than previous methods. The ability to handle these large-scale metallic systems efficiently benefits numerous application areas, including the design and discovery of new catalytic materials, studies on high entropy alloys, novel energy storage materials, and organometallic complexes in biomolecular electronics. The speedup also means that molecular dynamics simulations can run for timescales longer than what was previously possible.

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