Argonne’s Margaret Butler Fellowship Offers Opportunity to Work on Exascale Computing Applications

Argonnes Margaret Butler Fellowship Offers Opportunity to Work on Exascale
May 10, 2021 — As a PhD student at Oklahoma State University, Romit Maulik was brimming with ideas on how supercomputers could advance his computational physics research, but he lacked the resources to put his plans into action. That all changed in 2019, when he joined the Argonne Leadership Computing Facility (ALCF) as the recipient of its Margaret Butler Fellowship in Computational Science. “On paper, you can write out ideas, but to execute them, you often need help from experts,” says Maulik. ​“Since joining the ALCF, I have been able to take simple problems in my thesis and scale them up to much larger ones.” The ALCF, a U.S. Department of Energy (DOE) Office of Science User Facility at DOE’s Argonne National Laboratory, is now granting the same opportunity to a new class of postdoctoral researchers through an open call for...

Exascale Computing Project Moves Needle on Earthquake Risk Assessment

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As part of the US Department of Energy’s Exascale Computing Project (ECP), the Earthquake Simulation (EQSIM) application development team is creating a computational tool set and workflow for earthquake hazard and risk assessment that moves beyond the traditional empirically based techniques which are dependent on historical earthquake data. With software assistance from the ECP’s software technology group, the EQSIM team is working to give scientists and engineers the ability to simulate full end-to-end earthquake processes. This means understanding what takes place from the initiation of fault rupture (i.e., start of an earthquake) to modeling surface ground motions (i.e., earthquake hazard) to providing engineers with precise information that they can use to evaluate infrastructure response and evaluate the risk to people and property....

Exascale Computing Project Presents TAU, a CPU/GPU/MPI Profiler

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Programmers cannot blindly guess which sections of their code might bottleneck performance. This problem is worsened when codes run across the variety of hardware platforms supported by the Exascale Computing Project (ECP). A section of code that runs well on one system might be a bottleneck on another system. Differing hardware execution models further compound the performance challenges that face application developers; these models can include the somewhat restricted SIMD (Single Instruction Multiple Data) and SIMT (Single Instruction Multiple Thread) computing for GPU models and the more complex and general MIMD (Multiple Instruction Multiple Data) for CPUs. New software programming models, such as Kokkos, also introduce multiple layers of abstraction and lambda functions that can hide or obscure the low-level execution details due to their...