Argonne OutLoud: Rise of the Super Smart Supercomputer
The rapidly changing world of supercomputing and how it is changing our own world.
97 MATHEMATICS AND COMPUTING↗
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Results for “Supercomputer”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Introducing Mira, Argonne's Next-Generation Supercomputer
Mira, the new petascale IBM Blue Gene/Q system installed at the ALCF, will usher in a new era of scientific supercomputing. An engineering marvel, the 10-petaflops machine is capable of carrying out 10 quadrillion calculations per second.
97 MATHEMATICS AND COMPUTING↗
Supercomputing and the Search for Supernovae
Berkeley Lab's Peter Nugent discusses "Supercomputing and the search for supernovae" in this Oct. 28, 2013 talk, which is part of a Science at the Theater event entitled Eight Big Ideas.
79 ASTRONOMY AND ASTROPHYSICS↗
#AskBerkeleyLab: What's a Supercomputer?
Berkeley Lab computational scientist and Head of NERSC's Services Department, Katie Antypas, answers a question from Alameda resident, Marina, on supercomputers.
97 MATHEMATICS AND COMPUTING↗
Energy Efficient Supercomputing
Katie Anypas, Head of NERSC's Services Department discusses the Lab's research into developing increasingly powerful and energy efficient supercomputers at our '8 Big Ideas' Science at the Theater event on October 8th, 2014, in Oakland, California.
97 MATHEMATICS AND COMPUTING↗
Supercomputers Join the Fight against Cancer – U.S. Department of Energy
The Department of Energy has some of the best supercomputers in the world. Now, they’re joining the fight against cancer. Learn about our new partnership with the National Cancer Institute and GlaxoSmithKline Pharmaceuticals.
59 BASIC BIOLOGICAL SCIENCES↗
Supercomputer Simulations Help Develop New Approach to Fight Antibiotic Resistance
ORNL leveraged powerful supercomputing to support research led by University of Oklahoma scientists to identify chemicals that seek out and disrupt bacterial proteins called efflux pumps, known to be a major cause of antibiotic resistance. By running simulations on Titan, the team selected molecules most likely to target and potentially disable the assembly of efflux pumps found in E. coli bacteria cells.
47 OTHER INSTRUMENTATION↗
A Layered Solution for Supercomputing Storage
To solve the supercomputing challenge of memory keeping up with processing speed, a team at Los Alamos National Laboratory developed two innovative memory management and storage technologies. Burst buffers peel off data onto flash memory to support the checkpoint/restart paradigm of large simulations. MarFS adds a thin software layer enabling a new tier for campaign storage—based on inexpensive, failure-prone disk drives—between disk drives and tape archives.
97 MATHEMATICS AND COMPUTING↗
A Long History of Supercomputing
As part of its national security science mission, Los Alamos National Laboratory and HPC have a long, entwined history dating back to the earliest days of computing. From bringing the first problem to the nation’s first computer to building the first machine to break the petaflop barrier, Los Alamos holds many “firsts” in HPC breakthroughs. Today, supercomputers are integral to stockpile stewardship and the Laboratory continues to work with vendors in developing the future of HPC.
97 MATHEMATICS AND COMPUTING↗
Introducing Argonne’s Theta Supercomputer
Theta, the Argonne Leadership Computing Facility’s (ALCF) new Intel-Cray supercomputer, is officially open to the research community. Theta’s massively parallel, many-core architecture puts the ALCF on the path to Aurora, the facility’s future Intel-Cray system. Capable of nearly 10 quadrillion calculations per second, Theta enables researchers to break new ground in scientific investigations that range from modeling the inner workings of the brain to developing new materials for renewable energy applications.
97 MATHEMATICS AND COMPUTING↗
The mystery of dark energy: Investigating potential flaws in theory with supercomputers
Dark energy makes up roughly 70% of our universe, but what is it? With the help of the Mira supercomputer, located at the Argonne Leadership Computing Facility, scientists are investigating the nature of dark energy, one of the universe’s greatest mysteries.
79 ASTRONOMY AND ASTROPHYSICS↗
Accelerating virtual high-throughput ligand docking: current technology and case study on a petascale supercomputer
In this paper, we give the current state of high-throughput virtual screening. We describe a case study of using a task-parallel Message Passing Interface version of AutoDock4 to run a virtual high-throughput screen of one million compounds on the Jaguar Cray XK6 Supercomputer at Oak Ridge National Laboratory. We include a description of scripts developed to increase the efficiency of the predocking file preparation and postdocking analysis. A detailed tutorial, scripts, and source code for this Message Passing Interface version of AutoDock4 are available online at http://www.bio.utk.edu/baudrylab/autodockmpi.htm.
97 MATHEMATICS AND COMPUTING↗
Evaluating the networking characteristics of the Cray XC-40 Intel Knights Landing-based Cori supercomputer at NERSC
There are many potential issues associated with deploying the Intel Xeon Phi™ (code named Knights Landing [KNL]) manycore processor in a large-scale supercomputer. One in particular is the ability to fully utilize the high-speed communications network, given that the serial performance of a Xeon Phi TM core is a fraction of a Xeon®core. In this paper, we take a look at the trade-offs associated with allocating enough cores to fully utilize the Aries high-speed network versus cores dedicated to computation, e.g., the trade-off between MPI and OpenMP. In addition, we evaluate new features of Cray MPI in support of KNL, such as internode optimizations. We also evaluate one-sided programming models such as Unified Parallel C. We quantify the impact of the above trade-offs and features using a suite of National Energy Research Scientific Computing Center applications.
97 MATHEMATICS AND COMPUTING↗
Porting Adaptive Ensemble Molecular Dynamics Workflows to the Summit Supercomputer
Molecular dynamics (MD) simulations must take very small (femtosecond) integration steps in simulation-time to avoid numerical errors. Efficient use of parallel programming models and accelerators in state-of-the art MD programs now is pushing Moore’s limit for time-per-MD step. As a result, directly simulating timescales beyond milliseconds will not be attainable directly, even at exascale. However, concepts from statistical physics can be used to combine many parallel simulations to provide information about longer timescales and to adequately sample the simulation space, while preserving details about the dynamics of the system. Implementing such an approach requires a workflow program that allows adaptable steering of task assignments based on extensive statistical analysis of intermediate results. Here we report the implementation of such an adaptable workflow program to drive simulations on the Summit IBM Power System AC922, a pre-exascale supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). We compare to experiences on Titan, Summit’s predecessor, report the performance of the workflow and its components, and describe the porting process. We find that using a workflow program managed by a Mongo database can provide the fault tolerance, scalable performance, task dispatch rate, and reconfigurability required for robust and portable implementation of ensemble simulations such as are used in enhanced-sampling molecular dynamics. This type of workflow generator can also be used to provide adaptive steering of ensemble simulations for other applications in addition to MD.
Ossyra, John R.↗
Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers
We report the first congruent integration of HPC, AI, and multiscale modeling (MSM) for solving a mainstream biomechanical problem of thrombogenesis involving 6 million particles at record molecular-scale resolutions in space and at simulation rates of milliseconds per day. The two supercomputers, the IBM Summit-like AiMOS and our University’s SeaWulf, are used for scalability analysis of, and production runs with, the LAMMPS with our customization and AI augmentation and they attained optimal simulation speeds of 3,077 µs/day and 266 µs/day respectively. The long-time and large scales simulations enable the first study of the integrated platelet flowing, flipping, aggregating dynamics in one dynamically-coupled production run. The platelets’ angular and translational speeds, membrane particles’ speeds, and the membrane stress distributions are presented for the analysis of platelets’ aggregations.
Zhu, Yicong↗
Supercomputing Centers and Electricity Service Providers: A Geographically Distributed Perspective on Demand Management in Europe and the United States, In: ISC High Performance 2016: High Performance Computing
Supercomputing Centers (SCs) have high and variable power demands, which increase the challenges of the Electricity Service Providers (ESPs) with regards to efficient electricity distribution and reliable grid operation. High penetration of renewable energy generation further exacerbates this problem. In order to develop a symbiotic relationship between the SCs and their ESPs and to support effective power management at all levels, it is critical to understand and analyze how the existing relationships were formed and how these are expected to evolve.
Computer Science↗
Evaluation of pre-training large language models on leadership-class supercomputers
Large language models (LLMs) have arisen rapidly to the center stage of artificial intelligence as the foundation models applicable to many downstream learning tasks. However, how to effectively build, train, and serve such models for many high-stake and first-principle-based scientific use cases are both of great interests and of great challenges. Moreover, pre-training LLMs with billions or even trillions of parameters can be prohibitively expensive not just for academic institutions, but also for well-funded industrial and government labs. Furthermore, the energy cost and the environmental impact of developing LLMs must be kept in mind. Here, in this work, we conduct a first-of-its-kind performance analysis to understand the time and energy cost of pre-training LLMs on the Department of Energy (DOE)’s leadership-class supercomputers. Employing state-of-the-art distributed training techniques, we evaluate the computational performance of various parallelization approaches at scale for a range of model sizes, and establish a projection model for the cost of full training. Our findings provide baseline results, best practices, and heuristics for pre-training such large models that should be valuable to HPC community at large. We also offer insights and optimization strategies for using the first exascale computing system, Frontier, to train models of the size of GPT-3 and beyond.
97 MATHEMATICS AND COMPUTING↗
Development of a River Dynamical Core for E3SM to simulate compound flooding on Exascale-class heterogeneous supercomputers
Flooding events pose significant risk to human life, property, and infrastructure. Physically-consistent quantification of altered flood risks in global models requires hyper-resolution (~1 km) or fine flood simulations using two-dimensional (2D) physics schemes, both of which are unavailable in the current generation Earth System Models. Here, in this work, we have developed the River Dynamical Core (RDycore), which is an open-source, 2D shallow water equation (SWE) library for the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM). RDycore uses PETSc and libCEED libraries that allows it to run efficiently on CPUs and GPUs, as well as select a time-integration algorithm at runtime without requiring any code modifications. RDycore achieves spatial error convergence rates for problems with analytical and manufactured solutions similar to those reported previously in the literature, or consistent with the implemented first-order spatial discretization scheme. RDycore's accuracy in predicting flooding for a well-studied dam break problem is comparable to existing SWE models. For a problem with 471 million grid cells, RDycore achieves a speedup of 6.6x and 7.6x on GPUs compared to CPUs when using 320 compute nodes on DOE's Perlmutter and Frontier supercomputers, respectively. The one-way coupling of the RDycore library within E3SM is demonstrated by performing multiple 5-day flooding simulations during Hurricane Harvey driven by five precipitation datasets. The E3SM--RDycore simulations at 30 m spatial resolution accurately simulate maximum water height during the hurricane when benchmarked against a previously published study and achieve a speedup of 15x (Perlmutter) and 21x (Frontier) on GPUs relative to CPUs. The work presented here is the foundational step in providing hardware and algorithmic portability framework for simulating kilometer-scale river dynamics within E3SM.
Flood Simulation↗