Category: High Performance Computing
Dr. Kevin Leyton-Brown and Neil Newman are computer scientists at the University of British Columbia (UBC) working at the intersection of artificial intelligence (AI) and microeconomic theory. Their research demands large-scale, high-performance computing, in episodic bursts, to run parallel simulations of complex auctions. When Leyton-Brown and Newman began research into the computationally complex auction theory behind the 2016 United States wireless spectrum auction, their ML models required significantly more computing power than their on-premises infrastructure could provide. The UBC team turned to RONIN, an AWS Partner, and the virtually unlimited infrastructure of the AWS Cloud, to accelerate their time to answers and new discoveries.
In the spring of 2019, environmental modelers at the Lake Michigan Air Directors Consortium (LADCO) had a new problem to solve. Emerging research on air pollution along the shores of the Great Lakes in the United States showed that to properly simulate the pollution episodes in the region we needed to apply our models at a finer spatial granularity than the computational capacity of our in-house HPC cluster could handle. The LADCO modelers turned to AWS ParallelCluster to access the HPC resources needed to do this modeling faster and scale for our member states.
The concept of a COVID-19 High Performance Computing (HPC) Consortium emerged from a roundtable discussion at the White House in March and included input from industry, government, and academic leaders. Following the announcement of the consortium, AWS has been collaborating with teams on a growing number of projects to provide cloud computing resources from AWS. I want to share three early learnings and insights into some of the innovative projects on which we are collaborating with the world’s leading researchers.