S&TR Preview: High-Performance Computing Takes Aim at Cancer
Lawrence Livermore’s supercomputers are playing a crucial role in advancing cancer research and treatment.
60 APPLIED LIFE SCIENCES↗
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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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Science on Sequoia
With Sequoia at Lawrence Livermore National Laboratory, researchers explore grand challenging problems and are generating results at scales never before achieved. Sequoia is the first computer to have more than one million processors and is one of the fastest supercomputers in the world.
97 MATHEMATICS AND COMPUTING↗
What is the Universe made of?
A team of physicists and astrophysicists at Los Alamos National Laboratory, in collaboration with leading universities around the country, are using the Laboratory’s supercomputers to simulate the Big Bang nucleosynthesis and the early universe to unprecedented precision. These researchers developed a code, called BURST that describes the universe from a time of a few seconds after the Big Bang to several hundred thousand years later. BURST allows physicists to study the microscopic, quantum nature of fundamental particles — like nuclei and the ghostly, weakly interacting neutrinos — by simulating the universe at its largest, cosmological scale. BURST simultaneously describes all the particles present in the early universe as they develop, tracking their evolution, particularly the amounts of light nuclei fused in the cosmic soup.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
What Lies Beneath Can Be Imaged
The Hanford Site was quickly established to help end World War II, making history for producing the plutonium used in the world’s first nuclear weapons. Throughout the Cold War years, Hanford employees produced plutonium for most of the more than 60,000 weapons in the U.S. nuclear arsenal stockpile. Today, the once highly active nuclear reactors are shut down. And the mission at Hanford turned full-circle as scientists, engineers and specialists work to clean up our nation’s most contaminated nuclear site. PNNL Computational Geophysicist Tim Johnson is helping decision-makers understand the complexity and breadth of the contamination in soils at Hanford. Tim and others are applying remote, high-resolution geophysical imaging to determine the extent of contamination in the soil below the surface and understand the processes controlling its movement. They also provide real-time imaging of remediation processes that are working to limit the movement of contaminants below the surface and toward water resources. Geophysical imaging simply means that PNNL scientists are combining the techniques of geology, physics, mathematics and chemistry with supercomputer modeling to create three-dimensional images of the waste and its movement. These real-time, remote images are essential in reducing the uncertainty associated with cleanup costs and remediation technologies.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Saturday Science with Geoff Fairchild
In this first episode, we sit down (on a chairlift) with Computer Scientist Geoff Fairchild to talk about how his team is using Los Alamos National Laboratory’s supercomputing capabilities to data mine social media and reveal trends relating to health and safety.
97 MATHEMATICS AND COMPUTING↗
PCS: A Productive Computational Science Platform
As modern supercomputers continue to be increasingly heterogeneous with diverse computational accelerators, software becomes a critical aspect necessary to fully exploit these accelerators while not increasing the effort and time required to make variable scientific discovery in the face of complicated programming environments introduced by these accelerators. This paper presents PCS, a productive computational science platform for cluster-scale heterogeneous computing. The PCS platform by design follows a basic principle that, multiple programming models in a unified programming environment, is essential to facilitate large-scale, accelerator-aware, heterogeneous computing for next- generation scientific applications. We propose a new scheme — Edge Neural Network — for managing regularity in large dataflow graphs using higher-order bulk synchronous operators, providing a foundation for formalizing computational models for cluster-wide dataflow programming of heterogeneous clusters.
36 MATERIALS SCIENCE↗
PCS: A Productive Computational Science Platform
As modern supercomputers continue to be increasingly heterogeneous with diverse computational accelerators, software becomes a critical aspect necessary to fully exploit these accelerators while not increasing the effort and time required to make variable scientific discovery in the face of complicated programming environments introduced by these accelerators. This paper presents PCS, a productive computational science platform for cluster-scale heterogeneous computing. The PCS platform by design follows a basic principle that, multiple programming models in a unified programming environment, is essential to facilitate large-scale, accelerator-aware, heterogeneous computing for next- generation scientific applications. We propose a new scheme - Edge Neural Network - for managing regularity in large dataflow graphs using higher-order bulk synchronous operators, providing a foundation for formalizing computational models for cluster-wide dataflow programming of heterogeneous clusters.
36 MATERIALS SCIENCE↗
Simulation of a Next Generation Plasma Accelerator
Supercomputer simulations of plasma-based accelerators typically use a “moving window” to restrict the simulation area to a “small” region of interest that encompasses the laser beam and the portion of wakefield that accelerates the electron beam. In this simulation, a laser beam (red and blue disks) propagating through an under-dense plasma displaces electrons, creating a wake that supports very high electric fields, or “wakefield” (pale blue and yellow), that can be used to accelerate a short electron beam (white) to high-energy over a very short distance. While the simulation box is spatially much smaller, the number of time steps that are required to simulate the crossing of the laser through the plasma is still very large, typically over a million. (Credit: Jean-Luc Vay/Berkeley Lab)
43 PARTICLE ACCELERATORS↗
Modeling Future Scenarios to Make Airport Travel More Efficient
Watch this animation to see how the ATHENA project is applying the power of U.S. Department of Energy supercomputers to inform efficiency improvements at transportation hubs like Dallas-Fort Worth Airport.
97 MATHEMATICS AND COMPUTING↗
NREL HPC FY22 Allocation Webinar
This talk provides an overview of the FY22 allocation process for obtaining computing time on the Eagle supercomputer. The overall process is outlined, with specific instructions on completing the request.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Scalable load balancing for massively parallel distributed Monte Carlo particle transport
In order to run computer simulations efficiently on massively parallel computers with hundreds of thousands or millions of processors, care must be taken that the calculation is load balanced across the processors. Examining the workload of every processor leads to an unscalable algorithm, with run time at least as large as O(N), where N is the number of processors. We present a scalable load balancing algorithm, with run time 0(log(N)), that involves iterated processor-pair-wise balancing steps, ultimately leading to a globally balanced workload. We demonstrate scalability of the algorithm up to 2 million processors on the Sequoia supercomputer at Lawrence Livermore National Laboratory. (authors)
97 MATHEMATICS AND COMPUTING↗
Multi-node and Multi-core Performance Studies of a Monte Carlo code RMC
Over the past 15 years the architecture of high-performance computing systems has become increasingly heterogeneous with individual computing cores being subdivided into nodes and even auxiliary co-processing units such as graphics processing units or the Intel many integrated core co-processors. In fact, future computer platforms is moving toward a larger number of nodes and cores with lower memory available per node. Today, several production Monte Carlo codes use some types of hybrid parallelism strategy that makes use of shared-memory parallelism within a computing node and message-passing parallelism between nodes, which enables the codes to utilize available computing resources as much as possible, both among and within computing nodes on a cluster. The so-called hybrid parallelization is also possible with Reactor Monte Carlo Code RMC by activating both MPI and OpenMP parallel algorithms together. On HPC' which typically consists of several or several-ten thousand nodes equipping 16-32 computing intra-cores per node, simulation of RMC can be carried out in the hybrid parallelization with the MPI inter-node parallelization and the OpenMP intra-node parallelization. RMC has adopted a hybrid message-passing and shared-memory approach to parallelism, which enables the code to utilize available computing resources, both among and within computing nodes on a cluster. Shared-memory parallelism is especially valuable for large-model simulations because it enables multiple compute cores within a node to share common model information such as the geometry description, material, cross section and tally data, thus reducing the memory usage per processor. The calculation on the Tianhe-2 supercomputer took 6144 cores, resulting in a rate of 173,314,000 neutrons/minute for BEAVRS benchmark. While pin-wise full core H-M benchmark burnup calculations with millions of depletion regions was selected using MPI/OpenMP parallelism, the speed of 6,144 cores reach 1,843,200 burnable regions per minute. Keeping up with the continuing trend for increases in the number of computing resources within modern HPC systems is a significant challenge for teams that develop and maintain high-performance MC radiation transport solvers. order to address this challenge, RMC has adopted a hybrid message-passing and shared-memory approach to parallelism, which enables the code to utilize available computing resources, both among and within computing nodes on a cluster. Shared-memory parallelism is especially valuable for large-model simulations because it enables multiple compute cores within a node to share common model information such as the geometry description, material and composition definitions, and cross section data, thus reducing the memory usage per processor. The parallel performance has been studied by using two complex and representative benchmarks, H-M and BEAVRS benchmark. All simulations were run on Intel Xeon E5-2692 12 core, 2.2 GHz processors at MilkyWay-2 Super Computer with up to 12,288 available computing cores. While employing MPI parallelism, excellent parallel efficiency is achieved even above 12,000 processors and RMC reaches the parallel efficiency of 96% on 12,288 cores for the pin-by-pin computation of the BEAVRS benchmark. While BEAVRS criticality benchmark was selected using MPI/OpenMP parallelism, the speed of 6,144 cores reach 173,314,000 particles per minute. While pin-wise full core H-M benchmark burnup calculations with millions of depletion regions was selected using MPI/OpenMP parallelism, the speed of 6,144 cores reach 1,843,200 burnable regions per minute. Results from these studies demonstrate that RMC, using the hybrid parallel model described in this paper, is able to handle pin-wise full core burnup calculations with millions of depletion regions and scales well through thousands of processors. (authors)
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Single-Bubble Flow Boiling Phenomena - Interface Tracking Simulation
Boiling, as one of the most efficient heat transfer mechanisms, is widely used in various engineering systems. Better understanding and modeling of this process remains a major challenge in multiphase flow research. The distribution of vapor in boiling system affects the heat transfer rate and may cause unfavorable conditions, such as heater burn-out. A number of flow regimes have been observed experimentally. In general, there are three regimes under boiling conditions: nucleate boiling, transition boiling, and film boiling. The nucleate boiling regime is categorized into partial boiling regime and fully developed nucleate boiling, according to behavior of bubble dynamics and heat transfer characteristics. In the first region, as the wall temperature increases, the fraction of the wall surface subject to nucleate boiling increases until bubble formation occupies the entire heated surface. Heat transfer in this region is a complex mixture of single-phase forced convection and nucleate boiling. As bubble density increases, bubbles turn to coalesce and form insulating vapor patches, which impedes liquid flow back to the surface. The heat transfer rate under this condition reduces dramatically. This point is called Critical Heat Flux (CHF), which leads to boiling crisis. The behavior of boiling crisis is dependent on local fluid conditions due to bubble growth and departure. Experiments are the ultimate tool for boiling model development and verification, but they still lack some capabilities needed for better understanding of the local mechanism of this phenomena. It's difficult to capture many important details at the pressure/temperature conditions of interest using experimental techniques, such as full three dimensional measurements of velocity and temperature distribution and estimates of heat flux partitioning during the boiling process. The interface tracking simulation (ITS) is one of the promising approaches to describe heat transfer of boiling phenomena and their underlying mechanisms. The advances of high performance computing (HPC) in recent years made it possible to apply DNS to a wide variety of adiabatic flows. Some work has been done to implement evaporation / condensation models as well. Lee and Nydahl performed a numerical simulation of bubble growth and departure assuming that the bubble has the shape of a truncated sphere and a micro-layer exists during bubble growth. A 2-D cylindrical bubbles simulation has been done by Son with a simplified model to predict the heat flux in a thin liquid micro-layer. A direct simulation of 2D film boiling is conducted by Juric and Tryggvason. The film boiling, below critical pressure with a modified Level Set Method, is studied by Son and Dhir. Ose and Kunugi have developed a boiling and condensation model on subcooled boiling phenomena. Fuchs performed numerical simulations of bubble growth and departure considering wall conduction effects. Fully transient heat and fluid flow is modeled with a free surface of a rising bubble and a periodic calculation of the whole cycling of a growing, detaching, and rising bubble. Mukherjee and Kandikar have done a numerical simulation of an evaporating meniscus on a moving heated surface with level set method. The heat transfer associated with the advancing and receding contact angle has been studied. To develop the capability of physics-based boiling process, in the presented work the energy and momentum equations are coupled to simulate single-bubble growth scenarios. For a single bubble simulation in infinite liquid, the analytical solution exists and can be compared with the numerical results for verification purposes. The presented capabilities will be utilized in the large scale DNS of boiling flows in the future. The finite-element based code, PHASTA is used for the simulation. It is a parallel, hierarchic, higher-order accurate, adaptive, stabilized, transient analysis flow solver, which has been shown to be an effective tool for a wide range of single and two-phase flow problems. It has been shown to be highly scalable on top supercomputers ({approx}85% scaling on up to 3 million mesh partitions using a 92 billion element mesh . PHASTA has been shown to reliably predict the details of adiabatic bubbly flows as well as single-phase flows with heat transfer. To develop the capability of physics-based boiling process, in the presented work the energy and momentum equations are coupled to simulate a single-bubble growth scenario. For a single bubble growth in superheated water, the analytical solution exists and can be compared with the numerical results for verification purposes. The second-order accurate spatial and time discretization is used for the flow solver in the presented work. (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Transforming Energy Through Computational Excellence: NREL HPC Resources for High Performance Computing for Energy Innovation (HPC4EI) Program
NREL hosts computing facilities for the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In 2024, NREL introduced Kestrel, the 3rd generation, EERE-sponsored supercomputer dedicated to renewable energy and energy efficiency research. Kestrel has already been used for hundreds of research projects by NREL, other national laboratories, and university partners. This includes HPC4EI-sponsored industrial partnerships.
high-performance computing↗
Plasticity and Failure in Nanocrystalline BCC Metals via Molecular Dynamics Simulation
Advances in the ability to generate extremely high pressures in dynamic experiments such as at the National Ignition Facility has motivated the need for special materials optimized for those conditions as well as ways to probe the response of these materials as they are deformed. We need to develop a much deeper understanding of the behavior of materials subjected to high pressure, especially the effect of rate at the extremely high rates encountered in those experiments. Here we use large-scale molecular dynamics (MD) simulations of the high-rate deformation of nanocrystalline tantalum at pressures less than 100 GPa to investigate the processes associated with plastic deformation for strains up to 100%. We focus on 3D polycrystalline systems with typical grain sizes of 10-20 nm. We also study a rapidly quenched liquid (amorphous solid) tantalum. We apply a constant volume (isochoric), constant temperature (isothermal) shear deformation over a range of strain rates, and compute the resulting stress-strain curves to large strains for both uniaxial and biaxial compression. We study the rate dependence and identify plastic deformation mechanisms. The identification of the mechanisms is facilitated through a novel technique that computes the local grain orientation, returning it as a quaternion for each atom. This analysis technique is robust and fast, and has been used to compute the orientations on the fly during our parallel MD simulations on supercomputers. We find both dislocation and twinning processes are important, and they interact in the weak strain hardening in these extremely fine-grained microstructures. We also present some results on void growth in nanocrystalline BCC metals under tension.
36 MATERIALS SCIENCE↗
Evaluating the performance of parallel subsurface simulators: An illustrative example with PFLOTRAN
To better inform the subsurface scientist on the expected performance of parallel simulators, this work investigates performance of the reactive multiphase flow and multicomponent biogeochemical transport code PFLOTRAN as it is applied to several realistic modeling scenarios run on the Jaguar supercomputer. After a brief introduction to the code's parallel layout and code design, PFLOTRAN's parallel performance (measured through strong and weak scalability analyses) is evaluated in the context of conceptual model layout, software and algorithmic design, and known hardware limitations. PFLOTRAN scales well (with regard to strong scaling) for three realistic problem scenarios: (1) in situ leaching of copper from a mineral ore deposit within a 5-spot flow regime, (2) transient flow and solute transport within a regional doublet, and (3) a real-world problem involving uranium surface complexation within a heterogeneous and extremely dynamic variably saturated flow field. Weak scalability is discussed in detail for the regional doublet problem, and several difficulties with its interpretation are noted.
54 ENVIRONMENTAL SCIENCES↗
A new synoptic scale resolving global climate simulation using the Community Earth System Model
Abstract High‐resolution global climate modeling holds the promise of capturing planetary‐scale climate modes and small‐scale (regional and sometimes extreme) features simultaneously, including their mutual interaction. This paper discusses a new state‐of‐the‐art high‐resolution Community Earth System Model (CESM) simulation that was performed with these goals in mind. The atmospheric component was at 0.25° grid spacing, and ocean component at 0.1°. One hundred years of “present‐day” simulation were completed. Major results were that annual mean sea surface temperature (SST) in the equatorial Pacific and El‐Niño Southern Oscillation variability were well simulated compared to standard resolution models. Tropical and southern Atlantic SST also had much reduced bias compared to previous versions of the model. In addition, the high resolution of the model enabled small‐scale features of the climate system to be represented, such as air‐sea interaction over ocean frontal zones, mesoscale systems generated by the Rockies, and Tropical Cyclones. Associated single component runs and standard resolution coupled runs are used to help attribute the strengths and weaknesses of the fully coupled run. The high‐resolution run employed 23,404 cores, costing 250 thousand processor‐hours per simulated year and made about two simulated years per day on the NCAR‐Wyoming supercomputer “Yellowstone.”
Small, R. Justin↗
Pore-Scale and Multiscale Numerical Simulation of Flow and Transport in a Laboratory-Scale Column
Pore-scale models are useful for studying relationships between fundamental processes and phenomena at larger (i.e., Darcy) scales. However, the size of domains that can be simulated with explicit pore-scale resolution is limited by computational and observational constraints. Direct numerical simulation of pore-scale flow and transport is typically performed on millimeter-scale volumes at which X-ray computed tomography (XCT), often used to characterize pore geometry, can achieve micrometer resolution. In contrast, the scale at which a continuum approximation of a porous medium is valid is usually larger, on the order of centimeters to decimeters. Furthermore, laboratory experiments that measure continuum properties are typically performed on decimeter-scale columns. At this scale, XCT resolution is coarse (tens to hundreds of micrometers) and prohibits characterization of small pores and grains. We performed simulations of pore-scale processes over a decimeter-scale volume of natural porous media with a wide range of grain sizes, and compared to results of column experiments using the same sample. Simulations were conducted using high-performance codes executed on a supercomputer. Two approaches to XCT image segmentation were evaluated, a binary (pores and solids) segmentation and a ternary segmentation that resolved a third category (porous solids with pores smaller than the imaged resolution). We used a mixed Stokes-Darcy simulation method to simulate the combination of Stokes flow in large open pores and Darcy-like flow in porous solid regions. Simulations based on the ternary segmentation provided results that were consistent with experimental observations, demonstrating our ability to successfully model pore-scale flow over a column-scale domain.
CFD↗