One of our simulations is featured in the video “Improving Earthquake Simulation Modeling That May Save Lives” which is part of Intel’s “TACC: Engineering Research in HPC” piece. The simulation was conducted on the supercomputer Frontera, located at the Texas Advanced Computing Center (TACC). Frontera is a machine funded by the National Science Foundation and hosts a total of 8,368 dual-socket compute nodes using CPUs with Intel’s Cascade Lake microarchitecture.
Arm’s Pierre Blanchard will give a guest lecture on “Accuracy and Performance of libm Functions”. The presentation is part of the classes Rechnerstrukturen and High Performance Computing taught at Friedrich Schiller University Jena. Pierre’s virtual lecture is on Thursday, 1st of July 2021. Time is 02:15 - 03:45PM (GMT+2). Students outside of the specific classes are cordially invited to attend and may obtain access information by writing an e-mail to email@example.com.
Abstract: Arm IP can now be found at the cutting edge of HPC, running scientific computing workloads that stress all aspects of the system and software stack. The increasing need for optimised elementary math routines expressed by leading actors in the HPC community, such as the US National Labs, has driven the design and productisation of libamath; a library delivering the best available performance on AArch64. While most commonly used routines have been extensively optimised and made publicly available in Arm Optimized Routines (AOR), efforts are made towards upstreaming optimisations and development of new routines (available in the productised version) into AOR. This lecture describes the main stages involved in designing efficient implementations of elementary math functions in floating-point arithmetic, while thoroughly controlling their accuracy and performance. We also show how vector units can be used to leverage performance. In particular, we point out some of the issues exposed by vectorising such routines and we explain how to overcome them on both Neon and SVE enabled micro-architectures. Examples of routines will be given throughout the presentation to illustrate our approach, including: trigonometric functions; exponentials; as well as more exotic routines such as error functions.
About the Speaker: After completing a masters in computational mechanics at the Ecole Normale Supérieure de Cachan, Pierre defended his Ph.D. thesis in applied mathematics and scientific computing at the University of Bordeaux. In 2017 he moved to Manchester (UK) to work as a postdoctoral research assistant at the Maths Department of the University of Manchester under the supervision of Nick Higham and Jack Dongarra. Pierre’s research has ranged from hierarchical matrix algorithms for High Performance Computing (HPC) to fast algorithms for standard and randomised numerical linear algebra, as well as mixed-precision floating point arithmetic. He joined the Arm Performance Libraries team in Manchester two years ago as a software engineer to work on the optimisation of elementary math functions on AArch64.
Jared Bryan, a graduate student in Earth, Atmospheric and Planetary Sciences at the Massachusetts Institute of Technology, will present his recent work “Seismic Monitoring of Mount St. Helens from Summit to Slab” in our Advanced Computing Seminar. The seminar will be online and take place on Friday, June 18 2021, at 5PM (GMT+2). Send an e-mail to firstname.lastname@example.org if you’d like to attend.
Abstract: Mount St. Helens is the most active volcano in the Cascadia volcanic arc. To forecast its future eruptions and understand their driving processes, we need to link changes in the state of the volcano to changes in seismic observables. Noise-based seismic interferometry has emerged as a useful tool for monitoring magma transfer and the pressurization state of volcanic systems, but its sensitivity to velocity perturbations decreases rapidly with depth. We need new methods to monitor deep crustal processes. This presentation discusses our approach to seismic monitoring, which uses receiver functions, a form of event-based seismic interferometry, to quasi-continuously sample the crust beneath Mount St. Helens. We first validated the method with synthetic receiver functions, and then built a catalog of over 27,000 receiver functions at Mount St. Helens using magnitude 5.0+ teleseismic earthquakes from 2009-2020. Considering the seismic monitoring problem within the optimal transport framework, we used the Wasserstein distance and associated transport map to characterize the changes to receiver function waveforms. We discuss the possible mechanisms for these waveform variations, including slow-slip events on the nearby Cascadia megathrust. In future work, we plan to use this method to directly measure the rheology of magmatic systems and to observe the full migration pathways of magma from its source to the surface.
About the Speaker: Jared Bryan is a graduate student in Earth, Atmospheric and Planetary Sciences at the Massachusetts Institute of Technology, studying seismology. His research focuses on using passive seismic monitoring methods to understand dynamic processes in fault zones and volcanoes, with a particular interest in slow slip events and deep volcanic processes. He received bachelor’s degrees in physics and geosciences from Utah State University in 2020. He participated in the SCEC internship program in 2018, hosted by Dr. Alexander Breuer at the San Diego Supercomputer Center, and in 2019, hosted by Dr. Marine Denolle at Harvard University.