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Argonne Team Breaks Record with 2.9 Petabytes Globus Data Transfer

Today the Globus research data management service announced the largest single file transfer in its history: a team led by Argonne National Laboratory scientists moved 2.9 petabytes of data as part of a research project involving three of the largest cosmological simulations to date. “With exascale imminent, AI on the rise, HPC systems proliferating, and research teams more distributed than ever, fast, secure, reliable data movement and management are now more important than ever,” said Ian Foster.

Supercomputing Neutron Star Structures and Mergers

Over at XSEDE, Kimberly Mann Bruch & Jan Zverina from the San Diego Supercomputer Center write that researchers are using supercomputers to create detailed simulations of neutron star structures and mergers to better understand gravitational waves, which were detected for the first time in 2015. “XSEDE resources significantly accelerated our scientific output,” noted Paschalidis, whose group has been using XSEDE for well over a decade, when they were students or post-doctoral researchers. “If I were to put a number on it, I would say that using XSEDE accelerated our research by a factor of three or more, compared to using local resources alone.”

Video: Flying through the Universe with Supercomputing Power

In this video from SC18, Mike Bernhardt from the Exascale Computing Project talked with Salman Habib of Argonne National Laboratory about cosmological computer modeling and simulation. Habib explained that the ExaSky project is focused on developing a caliber of simulation that will use the coming exascale systems at maximal power. Clearly, there will be different types of exascale machines,” he said, “and so they [DOE] want a simulation code that can use not just one type of computer, but multiple types, and with equal efficiency.”

Watch 5,000 Robots Merge to Map the Universe in 3-D

In this video, scientists describe how the Dark Energy Spectroscopic Instrument (DESI) will measure the effect of dark energy on the expansion of the universe. It will obtain optical spectra for tens of millions of galaxies and quasars, constructing a 3D map spanning the nearby universe to 11 billion light years. “How do you create the largest 3D map of the universe? It’s as easy as teaching 5,000 robots how to “dance.” DESI, the Dark Energy Spectroscopic Instrument, is an experiment that will target millions of distant galaxies by automatically swiveling fiber-optic positioners (the robots) to point at them and gather their light.”

The Galactos Project: Using HPC To Run One of Cosmology’s Hardest Challenges

Debbie Bard from NERSC gave this talk at the HPC User Forum. “We present Galactos, a high performance implementation of a novel, O(N^2 ) algorithm that uses a load-balanced k-d tree and spherical harmonic expansions to compute the anisotropic 3PCF. Our implementation is optimized for the Intel Xeon Phi architecture, exploiting SIMD parallelism, instruction and thread concurrency, and signicant L1 and L2 cache reuse, reaching 39% of peak performance on a single node. Galactos scales to the full Cori system, achieving 9.8 PF (peak) and 5.06 PF (sustained) across 9636 nodes, making the 3PCF easily computable for all galaxies in the observable universe.”

Deep Learning at Scale for Cosmology Research

In this video from Google I/O 2018, Debbie Bard from NERSC describes Deep Learning at scale for cosmology research. “Debbie Bard is acting group lead for the Data Science Engagement Group at the National Energy Research Scientific Computing Center (NERSC) at Berkeley National Lab. A native of the UK, her career spans research in particle physics, cosmology and computing on both sides of the Atlantic.”

Scratch to Supercomputers: Bottoms-up Build of Large-scale Computational Lensing Software

Gilles Fourestey from EPFL gave this talk at the Swiss HPC Conference. “LENSTOOL is a gravitational lensing software that models mass distribution of galaxies and clusters. It is used to obtain sub-percent precision measurements of the total mass in galaxy clusters and constrain the dark matter self-interaction cross-section, a crucial ingredient to understanding its nature.”

Why the World’s Largest Telescope Relies on GPUs

Over at the NVIDIA blog, Jamie Beckett writes that the new European-Extremely Large Telescope, or E-ELT, will capture images 15 times sharper than the dazzling shots the Hubble telescope has beamed to Earth for the past three decades. “are running GPU-powered simulations to predict how different configurations of E-ELT will affect image quality. Changes to the angle of the telescope’s mirrors, different numbers of cameras and other factors could improve image quality.”

HACC: Fitting the Universe inside a Supercomputer

Nicholas Frontiere from the University of Chicago gave this talk at the DOE CSGF Program Review meeting. “In response to the plethora of data from current and future large-scale structure surveys of the universe, sophisticated simulations are required to obtain commensurate theoretical predictions. We have developed the Hardware/Hybrid Accelerated Cosmology Code (HACC), capable of sustained performance on powerful and architecturally diverse supercomputers to address this numerical challenge. We will investigate the numerical methods utilized to solve a problem that evolves trillions of particles, with a dynamic range of a million to one.”

SC17 Keynote Looks at the SKA Telescope: Life, the Universe, and Computing

In this special guest feature, Robert Roe reports from the SC17 conference keynote. “Philip Diamond, director general of SKA and Rosie Bolton, SKA regional centre project scientist and project scientist for the international engineering consortium designing the high performance computing systems used in the project, took to the stage to highlight the huge requirements for computation and data processing required by the SKA project.”