Marcin Copik

New York, NY, October 19, 2022 – ACM, the Association for Computing Machinery, and the IEEE Computer Society announced today that Marcin Copik of ETH Zurich of ETH Zurich and Masado Alexander Ishii of the University of Utah are the recipients of the 2022 ACM-IEEE CS George Michael Memorial HPC Fellowships. Shelby Lockhart of the University of Illinois at Urbana-Champaign received an Honorable Mention. 

Marcin Copik
Copik’s research bridges the gap between high-performance programming and serverless computing. He is bringing the Function-as-a-Service (FaaS) programming model into the HPC domain by developing high-performance software and hardware solutions for the serverless stack. By solving the fundamental performance challenges of FaaS, he is building a fast, efficient programming model that brings innovative cloud techniques into HPC data centers, allowing users to benefit from pay-as-you-go billing and helping operators to decrease running costs and their environmental impact.To that end, he has been working on tailored solutions for different levels of the FaaS computing stack, from computing and network devices up to high-level optimizations and efficient system designs. He has also proposed a new design for serverless platforms that applies HPC practices such as low-latency networking, data locality, and efficient communication.

Masado Alexander Ishii
Ishii is the main developer for the University of Utah’s Dendro-KT framework for four-dimensional adaptivity and parallel in time formulations. Given the ever-increasing levels of parallelism in the largest machines, parallelizing across space is not sufficient—and in many cases the inability to parallelize in time is the biggest bottleneck for several important problems. The Dendro-KT framework addresses this problem and also enables the development of high-orders and variable order in time formulation (similar to p-refinement). Working with collaborators, Ishii has also been involved in developing methods and codes for large-scale fluid simulations around complex objects, including a case with multiple complex objects, to evaluate COVID-19 transmission risk in classrooms.

Shelby Lockhart
Lockhart has made contributions in parallel communication, core parallel numerical algorithms, and advancing capabilities of large-scale predictive simulation. Her focus has been on modeling performance in heterogeneous settings, with an eye on redesigning the message communication “under-the-hood” (aspects of the high-performance architecture that are not readily visible) as well as looking at fundamental algorithmic changes in order to significantly improve achievable performance. Among her research highlights, she has provided detailed communication models to drive the selection of message routing, yielding impressive improvements across a range of problem types. She has also presented a strategy for achieving impressive reductions in communication costs in graphic processing unit (GPU) systems by communication through the host, accounting for different data volumes and GPU counts. Additionally, Lockhart’s thesis work on fixed point solvers has made important contributions to the Suite of Nonlinear and Differential/Algebraic Equation Solvers (SUNDIALS) project.

The ACM-IEEE CS George Michael Memorial HPC Fellowship is endowed in memory of George Michael, one of the founders of the SC Conference series. The fellowship honors exceptional PhD students throughout the world whose research focus is on high performance computing applications, networking, storage, or large-scale data analytics using the most powerful computers that are currently available. The Fellowship includes a $5,000 honorarium and travel expenses to attend the SC conference, where the Fellowships are formally presented.