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All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Streamline Integration Using MPI-Hybrid Parallelism on a Large Multicore Architecture

Streamline computation in a very large vector field data set represents a significant challenge due to the nonlocal and data-dependent nature of streamline integration. In this paper, we conduct a study of the performance characteristics of hybrid parallel programming and execution as applied to streamline integration on a large, multicore platform. With multicore processors now prevalent in clusters and supercomputers, there is a need to understand the impact of these hybrid systems in order to make the best implementation choice. We use two MPI-based distribution approaches based on established parallelization paradigms, parallelize over seeds and parallelize over blocks, and present a novel MPI-hybrid algorithm for each approach to compute streamlines. Our findings indicate that the work sharing between cores in the proposed MPI-hybrid parallel implementation results in much improved performance and consumes less communication and I/O bandwidth than a traditional, nonhybrid distributed implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

Since the beginning of the industrial age, material performance and design have been in the midst of innovation of many disruptive technologies. Today's electronics, space, medical, transportation, and other industries are enriched by development, design and deployment of composite, heterogeneous and multifunctional materials. As a result, materials innovation is now considerably outpaced by other aspects from component design to product cycle. In this article, we review predictive nonlinear theories for multiscale modeling of heterogeneous materials. Deeper attention is given to multiscale modeling in space and to computational homogenization in addressing challenging materials science questions. Moreover, we discuss a state-of-the-art platform in predictive image-based, multiscale modeling with co-designed simulations and experiments that executes on the world's largest supercomputers. Such a modeling framework consists of experimental tools, computational methods, and digital data strategies. Once fully completed, this collaborative and interdisciplinary framework can be the basis of Virtual Materials Testing standards and aids in the development of new material formulations. Moreover, it will decrease the time to market of innovative products.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Designing a Scalable Fault Tolerance Model for High Performance Computational Chemistry: A Case Study with Coupled Cluster Perturbative Triples

In the last couple of decades, the massive computational power provided by the most modern supercomputers has resulted in simulation of higher order computational chem- istry methods, previously considered intractable. As the system sizes continue to increase, computational chemistry domain continues to escalate this trend using parallel comput- ing with programming models such as Message Passing Interface (MPI) and Partitioned Global Address Space (PGAS) programming models such as Global Arrays. The ever increasing scale of these supercomputers comes at a cost of reduced mean time between failures, currently in the order of days, and projected to be in the order of hours for up- coming extreme scale systems. While traditional disk based checkpointing methods are ubiquitous for storing intermediate solutions, they suffer from high overhead of writing and recovering from checkpoints. In practice, checkpointing itself often brings the system down. Clearly, methods beyond checkpointing are imperative to handling the aggravating issue of reducing MTBF. In this paper, we address this challenge by designing and im- plementing an efficient fault tolerant version of coupled cluster method with NWChem, using in memory data redundancy. We present the challenges associated with our de- sign including efficient data storage model, maintenance of at least one consistent data copy and the recovery process. Our performance evaluation without faults shows that the current design exhibits negligible overhead. In the presence of a fault, the proposed design incurs negligible overhead in comparison to the state of the art implementation without faults.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

The prediction of protein 3D structure from amino acid sequence is a computational grand challenge in biophysics and plays a key role in robust protein structure prediction algorithms, from drug discovery to genome interpretation. The advent of AI models, such as AlphaFold, is revolutionizing applications that depend on robust protein structure prediction algorithms. To maximize the impact, and ease the usability, of these AI tools we introduce APACE, AlphaFold2 and advanced computing as a service, a computational framework that effectively handles this AI model and its TB-size database to conduct accelerated protein structure prediction analyses in modern supercomputing environments. We deployed APACE in the Delta and Polaris supercomputers and quantified its performance for accurate protein structure predictions using four exemplar proteins: 6AWO, 6OAN, 7MEZ, and 6D6U. Using up to 300 ensembles, distributed across 200 NVIDIA A100 GPUs, we found that APACE is up to two orders of magnitude faster than off-the-self AlphaFold2 implementations, reducing time-to-solution from weeks to minutes. This computational approach may be readily linked with robotics laboratories to automate and accelerate scientific discovery.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Simulation-based Performance Analysis and Tuning for a Two-level Directly Connected System

Hardware and software co-design is becoming increasingly important due to complexities in supercomputing architectures. Simulating applications before there is access to the real hardware can assist machine architects in making better design decisions that can optimize application performance. At the same time, the application and runtime can be optimized and tuned beforehand. BigSim is a simulation-based performance prediction framework designed for these purposes. It can be used to perform packet-level network simulations of parallel applications using existing parallel machines. In this paper, we demonstrate the utility of BigSim in analyzing and optimizing parallel application performance for future systems based on the PERCS network. We present simulation studies using benchmarks and real applications expected to run on future supercomputers. Future petascale systems will have more than 100,000 cores, and we present simulations at that scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Earth Scientists Shake Things up on Titan

Two recent projects have used the Cray XK7 Titan supercomputer at the US Department of Energy's Oak Ridge National Laboratory to study Earth's dynamics, specifically seismology-related studies. Using Titan, one team of researchers modeled Earth's interior using earthquake data, while a second team developed physics-based earthquake simulations for disaster management applications. Together, the projects demonstrate how leadership-class supercomputing provides context to scientific discussions and informs decision making among civic leaders.

58 GEOSCIENCES↗
DOE OSTI2011

The Argonne Leadership Computing Facility 2010 annual report.

Researchers found more ways than ever to conduct transformative science at the Argonne Leadership Computing Facility (ALCF) in 2010. Both familiar initiatives and innovative new programs at the ALCF are now serving a growing, global user community with a wide range of computing needs. The Department of Energy's (DOE) INCITE Program remained vital in providing scientists with major allocations of leadership-class computing resources at the ALCF. For calendar year 2011, 35 projects were awarded 732 million supercomputer processor-hours for computationally intensive, large-scale research projects with the potential to significantly advance key areas in science and engineering. Argonne also continued to provide Director's Discretionary allocations - 'start up' awards - for potential future INCITE projects. And DOE's new ASCR Leadership Computing (ALCC) Program allocated resources to 10 ALCF projects, with an emphasis on high-risk, high-payoff simulations directly related to the Department's energy mission, national emergencies, or for broadening the research community capable of using leadership computing resources. While delivering more science today, we've also been laying a solid foundation for high performance computing in the future. After a successful DOE Lehman review, a contract was signed to deliver Mira, the next-generation Blue Gene/Q system, to the ALCF in 2012. The ALCF is working with the 16 projects that were selected for the Early Science Program (ESP) to enable them to be productive as soon as Mira is operational. Preproduction access to Mira will enable ESP projects to adapt their codes to its architecture and collaborate with ALCF staff in shaking down the new system. We expect the 10-petaflops system to stoke economic growth and improve U.S. competitiveness in key areas such as advancing clean energy and addressing global climate change. Ultimately, we envision Mira as a stepping-stone to exascale-class computers that will be faster than petascale-class computers by a factor of a thousand. Pete Beckman, who served as the ALCF's Director for the past few years, has been named director of the newly created Exascale Technology and Computing Institute (ETCi). The institute will focus on developing exascale computing to extend scientific discovery and solve critical science and engineering problems. Just as Pete's leadership propelled the ALCF to great success, we know that that ETCi will benefit immensely from his expertise and experience. Without question, the future of supercomputing is certainly in good hands. I would like to thank Pete for all his effort over the past two years, during which he oversaw the establishing of ALCF2, the deployment of the Magellan project, increases in utilization, availability, and number of projects using ALCF1. He managed the rapid growth of ALCF staff and made the facility what it is today. All the staff and users are better for Pete's efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Science & Technology Review June 2012

This month's issue has the following articles: (1) A New Era in Climate System Analysis - Commentary by William H. Goldstein; (2) Seeking Clues to Climate Change - By comparing past climate records with results from computer simulations, Livermore scientists can better understand why Earth's climate has changed and how it might change in the future; (3) Finding and Fixing a Supercomputer's Faults - Livermore experts have developed innovative methods to detect hardware faults in supercomputers and help applications recover from errors that do occur; (4) Targeting Ignition - Enhancements to the cryogenic targets for National Ignition Facility experiments are furthering work to achieve fusion ignition with energy gain; (5) Neural Implants Come of Age - A new generation of fully implantable, biocompatible neural prosthetics offers hope to patients with neurological impairment; and (6) Incubator Busy Growing Energy Technologies - Six collaborations with industrial partners are using the Laboratory's high-performance computing resources to find solutions to urgent energy-related problems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

Reliable High Performance Peta- and Exa-Scale Computing

As supercomputers become larger and more powerful, they are growing increasingly complex. This is reflected both in the exponentially increasing numbers of components in HPC systems (LLNL is currently installing the 1.6 million core Sequoia system) as well as the wide variety of software and hardware components that a typical system includes. At this scale it becomes infeasible to make each component sufficiently reliable to prevent regular faults somewhere in the system or to account for all possible cross-component interactions. The resulting faults and instability cause HPC applications to crash, perform sub-optimally or even produce erroneous results. As supercomputers continue to approach Exascale performance and full system reliability becomes prohibitively expensive, we will require novel techniques to bridge the gap between the lower reliability provided by hardware systems and users unchanging need for consistent performance and reliable results. Previous research on HPC system reliability has developed various techniques for tolerating and detecting various types of faults. However, these techniques have seen very limited real applicability because of our poor understanding of how real systems are affected by complex faults such as soft fault-induced bit flips or performance degradations. Prior work on such techniques has had very limited practical utility because it has generally focused on analyzing the behavior of entire software/hardware systems both during normal operation and in the face of faults. Because such behaviors are extremely complex, such studies have only produced coarse behavioral models of limited sets of software/hardware system stacks. Since this provides little insight into the many different system stacks and applications used in practice, this work has had little real-world impact. My project addresses this problem by developing a modular methodology to analyze the behavior of applications and systems during both normal and faulty operation. By synthesizing models of individual components into a whole-system behavior models my work is making it possible to automatically understand the behavior of arbitrary real-world systems to enable them to tolerate a wide range of system faults. My project is following a multi-pronged research strategy. Section II discusses my work on modeling the behavior of existing applications and systems. Section II.A discusses resilience in the face of soft faults and Section II.B looks at techniques to tolerate performance faults. Finally Section III presents an alternative approach that studies how a system should be designed from the ground up to make resilience natural and easy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Analyzing the Effects of Water Output Rates on the Strategic Computing Complex

At the Los Alamos National Laboratory, the Strategic Computing Complex (SCC) requires chilled water to properly allow its supercomputers and other systems to properly function. In order to do so, the SCC heavily relies on the use of treated water from the Sanitary Waste Water System (SWWS) and the Sanitary Effluent Reclamation Facility (SERF). Industrial water that can be reused, such as from toilets and sinks, as well as rain and well water, arrives at the SWWS where it is aerated and processed. From there, a portion of the water can evaporate, while some of it is removed in the form of sludge or discharged into the nearby canyon. However, a majority of this reuse water is transported to SERF, where it is further processed and treated. Here is the location where this water becomes “usable” once again. From there, is transported to cooling towers where the water becomes chilled and can properly cool the supercomputers at the SCC. In fact, nearly all of the reuse water utilized by the SCC is treated and processed at SERF. This analysis specifically examines the water that leaves SWWS for SERF.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2010

2009 ALCF annual report.

This year the Argonne Leadership Computing Facility (ALCF) delivered nearly 900 million core hours of science. The research conducted at their leadership class facility touched our lives in both minute and massive ways - whether it was studying the catalytic properties of gold nanoparticles, predicting protein structures, or unearthing the secrets of exploding stars. The authors remained true to their vision to act as the forefront computational center in extending science frontiers by solving pressing problems for our nation. Our success in this endeavor was due mainly to the Department of Energy's (DOE) INCITE (Innovative and Novel Computational Impact on Theory and Experiment) program. The program awards significant amounts of computing time to computationally intensive, unclassified research projects that can make high-impact scientific advances. This year, DOE allocated 400 million hours of time to 28 research projects at the ALCF. Scientists from around the world conducted the research, representing such esteemed institutions as the Princeton Plasma Physics Laboratory, National Institute of Standards and Technology, and European Center for Research and Advanced Training in Scientific Computation. Argonne also provided Director's Discretionary allocations for research challenges, addressing such issues as reducing aerodynamic noise, critical for next-generation 'green' energy systems. Intrepid - the ALCF's 557-teraflops IBM Blue/Gene P supercomputer - enabled astounding scientific solutions and discoveries. Intrepid went into full production five months ahead of schedule. As a result, the ALCF nearly doubled the days of production computing available to the DOE Office of Science, INCITE awardees, and Argonne projects. One of the fastest supercomputers in the world for open science, the energy-efficient system uses about one-third as much electricity as a machine of comparable size built with more conventional parts. In October 2009, President Barack Obama recognized the excellence of the entire Blue Gene series by awarding it to the National Medal of Technology and Innovation. Other noteworthy achievements included the ALCF's collaboration with the National Energy Research Scientific Computing Center (NERSC) to examine cloud computing as a potential new computing paradigm for scientists. Named Magellan, the DOE-funded initiative will explore which science application programming models work well within the cloud, as well as evaluate the challenges that come with this new paradigm. The ALCF obtained approval for its next-generation machine, a 10-petaflops system to be delivered in 2012. This system will allow us to resolve ever more pressing problems, even more expeditiously through breakthrough science in the years to come.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2012

Compilation of Abstracts for SC12 Conference Proceedings

1 A Breakthrough in Rotorcraft Prediction Accuracy Using Detached Eddy Simulation; 2 Adjoint-Based Design for Complex Aerospace Configurations; 3 Simulating Hypersonic Turbulent Combustion for Future Aircraft; 4 From a Roar to a Whisper: Making Modern Aircraft Quieter; 5 Modeling of Extended Formation Flight on High-Performance Computers; 6 Supersonic Retropropulsion for Mars Entry; 7 Validating Water Spray Simulation Models for the SLS Launch Environment; 8 Simulating Moving Valves for Space Launch System Liquid Engines; 9 Innovative Simulations for Modeling the SLS Solid Rocket Booster Ignition; 10 Solid Rocket Booster Ignition Overpressure Simulations for the Space Launch System; 11 CFD Simulations to Support the Next Generation of Launch Pads; 12 Modeling and Simulation Support for NASA's Next-Generation Space Launch System; 13 Simulating Planetary Entry Environments for Space Exploration Vehicles; 14 NASA Center for Climate Simulation Highlights; 15 Ultrascale Climate Data Visualization and Analysis; 16 NASA Climate Simulations and Observations for the IPCC and Beyond; 17 Next-Generation Climate Data Services: MERRA Analytics; 18 Recent Advances in High-Resolution Global Atmospheric Modeling; 19 Causes and Consequences of Turbulence in the Earths Protective Shield; 20 NASA Earth Exchange (NEX): A Collaborative Supercomputing Platform; 21 Powering Deep Space Missions: Thermoelectric Properties of Complex Materials; 22 Meeting NASA's High-End Computing Goals Through Innovation; 23 Continuous Enhancements to the Pleiades Supercomputer for Maximum Uptime; 24 Live Demonstrations of 100-Gbps File Transfers Across LANs and WANs; 25 Untangling the Computing Landscape for Climate Simulations; 26 Simulating Galaxies and the Universe; 27 The Mysterious Origin of Stellar Masses; 28 Hot-Plasma Geysers on the Sun; 29 Turbulent Life of Kepler Stars; 30 Modeling Weather on the Sun; 31 Weather on Mars: The Meteorology of Gale Crater; 32 Enhancing Performance of NASAs High-End Computing Applications; 33 Designing Curiosity's Perfect Landing on Mars; 34 The Search Continues: Kepler's Quest for Habitable Earth-Sized Planets.

HPC↗
DOE OSTI2011

Provisioning a Multi-Tiered Data Staging Area for Extreme-Scale Machines

Massively parallel scientific applications, running on extreme-scale supercomputers, produce hundreds of terabytes of data per run, driving the need for storage solutions to improve their I/O performance. Traditional parallel file systems (PFS) in high performance computing (HPC) systems are unable to keep up with such high data rates, creating a storage wall. In this work, we present a novel multi-tiered storage architecture comprising hybrid node-local resources to construct a dynamic data staging area for extreme-scale machines. Such a staging ground serves as an impedance matching device between applications and the PFS. Our solution combines diverse resources (e.g., DRAM, SSD) in such a way as to approach the performance of the fastest component technology and the cost of the least expensive one. We have developed an automated provisioning algorithm that aids in meeting the checkpointing performance requirement of HPC applications, by using a least-cost storage configuration. We evaluate our approach using both an implementation on a large scale cluster and a simulation driven by six-years worth of Jaguar supercomputer job-logs, and show that our approach, by choosing an appropriate storage configuration, achieves 41.5% cost savings with only negligible impact on performance.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2011

Evaluation of Simple Causal Message Logging for Large-Scale Fault Tolerant HPC Systems

The era of petascale computing brought machines with hundreds of thousands of processors. The next generation of exascale supercomputers will make available clusters with millions of processors. In those machines, mean time between failures will range from a few minutes to few tens of minutes, making the crash of a processor the common case, instead of a rarity. Parallel applications running on those large machines will need to simultaneously survive crashes and maintain high productivity. To achieve that, fault tolerance techniques will have to go beyond checkpoint/restart, which requires all processors to roll back in case of a failure. Incorporating some form of message logging will provide a framework where only a subset of processors are rolled back after a crash. In this paper, we discuss why a simple causal message logging protocol seems a promising alternative to provide fault tolerance in large supercomputers. As opposed to pessimistic message logging, it has low latency overhead, especially in collective communication operations. Besides, it saves messages when more than one thread is running per processor. Finally, we demonstrate that a simple causal message logging protocol has a faster recovery and a low performance penalty when compared to checkpoint/restart. Running NAS Parallel Benchmarks (CG, MG and BT) on 1024 processors, simple causal message logging has a latency overhead below 5%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Particle Communication and Domain Neighbor Coupling: Scalable Domain Decomposed Algorithms for Monte Carlo Particle Transport

In order to run Monte Carlo particle transport calculations on new supercomputers with hundreds of thousands or millions of processors, care must be taken to implement scalable algorithms. This means that the algorithms must continue to perform well as the processor count increases. In this paper, we examine the scalability of:(1) globally resolving the particle locations on the correct processor, (2) deciding that particle streaming communication has finished, and (3) efficiently coupling neighbor domains together with different replication levels. We have run domain decomposed Monte Carlo particle transport on up to 2 21 = 2,097,152 MPI processes on the IBM BG/Q Sequoia supercomputer and observed scalable results that agree with our theoretical predictions. These calculations were carefully constructed to have the same amount of work on every processor, i.e. the calculation is already load balanced. We also examine load imbalanced calculations where each domain’s replication level is proportional to its particle workload. In this case we show how to efficiently couple together adjacent domains to maintain within workgroup load balance and minimize memory usage.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

Scalable three-dimensional thermal-hydraulic best-estimate code BAGIRA

The three-dimensional thermal-hydraulic best-estimate code BAGIRA for modeling of multi-phase flows was developed without any artificial physical assumptions or simplifications. The mathematical model is based on numerical approximations of exact three-dimensional equations, including effective multi-dimensional models for turbulent heat and mass transfer. With use of BAGIRA All-Russian Scientific Research Inst. of Nuclear Power Plants (VNIIAES) has developed a full-scope and analytical simulators using BAGIRA for a number of power plants with VVER-1000 and RBMK type design, which are being used in Kalinin, Kursk, Smolensk, Chernobyl, and Bilibino NPPs. The comparison of calculated and experimental results shows that BAGIRA can successfully reproduce the most important processes observed in experiments. BAGIRA is implemented in FORTRAN. It is a relatively complicated code that tends to decompose task by aspects. Such a style is welcoming for extensions, which can be added without code redesign. We would like to present an aspect-oriented mix-in approach for BAGIRA code extension. It allows to make it scalable in number of directions leaving original code base untouched. It is possible to add new effects/units, and even to produce a supercomputer version of the code. The last is a key point today due to availability of low-cost compact supercomputers, which makes building compact NPP simulators possible. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Massive hybrid parallelism for fully implicit multiphysics

As hardware advances continue to modify the supercomputing landscape, traditional scientific software development practices will become more outdated, ineffective, and inefficient. The process of rewriting/retooling existing software for new architectures is a Sisyphean task, and results in substantial hours of development time, effort, and money. Software libraries which provide an abstraction of the resources provided by such architectures are therefore essential if the computational engineering and science communities are to continue to flourish in this modern computing environment. The Multiphysics Object Oriented Simulation Environment (MOOSE) framework enables complex multiphysics analysis tools to be built rapidly by scientists, engineers, and domain specialists, while also allowing them to both take advantage of current HPC architectures, and efficiently prepare for future supercomputer designs. MOOSE employs a hybrid shared-memory and distributed-memory parallel model and provides a complete and consistent interface for creating multiphysics analysis tools. In this paper, a brief discussion of the mathematical algorithms underlying the framework and the internal object-oriented hybrid parallel design are given. Representative massively parallel results from several applications areas are presented, and a brief discussion of future areas of research for the framework are provided. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Simulation of unsteady blood flows in a patient-specific compliant pulmonary artery with a highly parallel monolithically coupled fluid-structure interaction algorithm

Computational fluid dynamics (CFD) is increasingly used to study blood flows in patient-specific arteries for understanding certain cardiovascular diseases. The techniques work quite well for relatively simple problems, but need improvements when the problems become harder in the case when (1) the geometry becomes complex (from a few branches to a full pulmonary artery), (2) the model becomes more complex (from fluid-only calculation to coupled fluid-structure interaction calculation), (3) both the fluid and wall models become highly nonlinear, and (4) the computer on which we run the simulation is a supercomputer with tens of thousands of processor cores. To push the limit of CFD in all four fronts, in this paper, we develop and study a highly parallel algorithm for solving a monolithically coupled fluid-structure system for the modeling of the interaction of the blood flow and the arterial wall. As a case study, we consider a patient-specific, full size pulmonary artery obtained from CT (Computed Tomography) images, with an artificially added layer of wall with a fixed thickness. The fluid is modeled with a system of incompressible Navier-Stokes equations and the wall is modeled by a geometrically nonlinear elasticity equation. As far as we know this is the first time the unsteady blood flow in a full pulmonary artery is simulated without assuming a rigid wall. We report the proposed numerical algorithm and software scale well beyond 10,000 processor cores on a supercomputer for solving the fluid-structure interaction problem discretized with a stabilized finite element method in space and an implicit scheme in time involving hundreds of millions of unknowns.

97 MATHEMATICS AND COMPUTING↗