Abstract
In simulating large parallel systems, bottom-up approaches exercise detailed hardware models with effects from simplified software models or traces, whereas top-down approaches evaluate the timing and functionality of detailed software models over coarse hardware models. Here, we focus on the top-down approach and significantly advance the scale of the simulated parallel programs. Via the direct execution technique combined with parallel discrete event simulation, we stretch the limits of the top-down approach by simulating message passing interface (MPI) programs with millions of tasks. Using a timing-validated benchmark application, a proof-of-concept scaling level is achieved to over 0.22 billion virtual MPI processes on 216,000 cores of a Cray XT5 supercomputer, representing one of the largest direct execution simulations to date, combined with a multiplexing ratio of 1024 simulated tasks per real task.
[Pub 143]
Kalyan Perumalla
As a Federal Program Manager in Advanced Scientific Computing Research at the U.S. Dept. of Energy, Office of Science, Kalyan Perumalla manages a $100-million R&D portfolio covering AI, HPC, Quantum, SciDAC, and Basic Computer Science. In his 25-year R&D leadership experience, he previously led advanced R&D as Distinguished Research Staff Member at the Oak Ridge National Laboratory (ORNL) developing scalable software and applications on the world’s largest supercomputers for 17 years, including as a line manager and a founding group leader. He has held senior faculty and adjunct appointments at UTK, GT, and UNL, and was an IAS Fellow at Durham University.