Vortices in high-performance high-temperature superconductors
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phonons, thermal conductivity, energy storage (inc↗
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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↗
Many-Core Acceleration of a Discrete Ordinates Transport Mini-App at Extreme Scale, In: ISC High Performance 2016: High Performance Computing
Time-dependent deterministic discrete ordinates transport codes are an important class of application which provide significant challenges for large, many-core systems. One such challenge is the large memory capacity needed by the solve step, which requires us to have a scalable solution in order to have enough node-level memory to store all the data. In our previous work, we demonstrated the first implementation which showed a significant performance benefit for single node solves using GPUs. In this paper we extend our work to large problems and demonstrate the scalability of our solution on two Petascale GPU-based supercomputers: Titan at Oak Ridge and Piz Daint at CSCS. Our results show that our improved node-level parallelism scheme scales just as well across large systems as previous approaches when using the tried and tested KBA domain decomposition technique. We validate our results against an improved performance model which predicts the runtime of the main ‘sweep’ routine when running on different hardware, including CPUs or GPUs.
Computer Science↗
Early Experiences Porting the NAMD and VMD Molecular Simulation and Analysis Software to GPU-Accelerated OpenPOWER Platforms, In: ISC High Performance 2016: High Performance Computing
All-atom molecular dynamics simulations of biomolecules provide a powerful tool for exploring the structure and dynamics of large protein complexes within realistic cellular environments. Unfortunately, such simulations are extremely demanding in terms of their computational requirements, and they present many challenges in terms of preparation, simulation methodology, and analysis and visualization of results. We describe our early experiences porting the popular molecular dynamics simulation program NAMD and the simulation preparation, analysis, and visualization tool VMD to GPU-accelerated OpenPOWER hardware platforms. We report our experiences with compiler-provided autovectorization and compare with hand-coded vector intrinsics for the POWER8 CPU. We explore the performance benefits obtained from unique POWER8 architectural features such as 8-way SMT and its value for particular molecular modeling tasks. Finally, we evaluate the performance of several GPU-accelerated molecular modeling kernels and relate them to other hardware platforms.
Computer Science↗
Accurately constituting robust interfaces for high-performance high-energy lithium metal batteries
High-energy lithium metal batteries (LMBs) have received ever-increasing interest. Among them, coupling lithium metal (Li) with nickel-rich material, LiNi x Mn y Co z O 2 (NMCs, x ≥ 0.6, x + y + z = 1), is promising because Li anodes enable an extremely high capacity (∼3860 mA h g −1 ) and the lowest redox potential (−3.04 V vs. standard hydrogen electrode), while NMCs can achieve a much higher capacity of ∼200 mA h g −1 and lower cost than those of LiCoO 2 . However, the resultant Li‖NMC cells have been hindered from commercialization due to a series of challenges related to the interface stability of both Li anodes and NMC cathodes. Specifically, Li anodes suffer from Li dendritic growth and the formation of solid electrolyte interphase (SEI), while NMC cathodes suffer from the formation of cathode electrolyte interphase (CEI) and other interface-related issues, including transition metal dissolution, oxygen release, cracking, and so on. To tackle these issues, recently, two sister techniques, atomic and molecular layer deposition (ALD and MLD), have emerged and exhibit tremendous capabilities to accurately constitute robust interfaces to achieve high-performance Li‖NMC LMBs. They can uniquely develop uniform and conformal films as surface coatings of LMBs in a precisely controllable mode at the atomic/molecular level, while proceeding with film deposition at low temperatures (e.g., ≤250 °C). In this Feature Article, we review the latest research progress in developing novel surface coatings via ALD and MLD for Li‖NMC LMBs and discuss outcomes for pursuing high performance.
25 ENERGY STORAGE↗
High-Performance Molecular Dynamics Simulation for Biological and Materials Sciences: Challenges of Performance Portability, Dallas, TX, November 2018.
Highly-optimized parallel molecular dynamics programs have allowed researchers to achieve ground-breaking results in biological and materials sciences. This type of performance has come at the expense of portability: a significant effort is required for performance optimization on each new architecture. Using a metric that emphasizes speedup, we assess key accelerating programming components of four different best-performing molecular dynamics programs - GROMACS, NAMD, LAMMPS and CP2K-- each having a particular scope of application, for contribution to performance and for portability. We use builds with and without these components, tested on HPC systems. We also analyze the code-bases to determine compliance with portability recommendations. We find that for all four programs, the contributions of the non-portable components to speed are essential to the programs' performances; without them we see a reduction in time-to-solution of a magnitude that is insufferable to domain scientists. This characterizes the performance efficiency that must be approached for good performance portability on a programmatic level, suggesting solutions to this difficult problem, which should come from developers, industry and funding institutions, and possibly new research in programming languages.
Computer Science↗
Towards Autonomous Experiments by Connecting High Performance Microscopy with High Performance Computing
The digitization of controls, data, and analysis in microscopy is bringing the idea of autonomous microscopes closer to reality than ever before. Automated transmission electron microscopy (TEM) is already fairly routine for some experiments the only require simple repetitive tasks such as imaging biological macromolecules for single particle cryoEM [1], tilt series for electron tomography [2], and movies for crystallography [3]. The vast majority of TEM experiments are conducted completely by human operators who choose the regions of interest, optimize experimental parameters, and make decisions about data quality visually during an experiment. The field is still a long way from having completely autonomous TEMs that can adapt to sample difficulties and tune experimental parameters based on data quality and desired experimental outcomes. Part of the issue is the lack of capability for feeding information learned from on-line, live data analysis back into the on-going experiment [4]. Furthermore, this presentation will discuss current capabilities for large scale data reduction and analysis using high performance computing (i.e. supercomputing) and progress towards developing a true feed-back loop that places data analysis and theory in the experimental loop.
97 MATHEMATICS AND COMPUTING↗
Accelerating Simulation for High-Fidelity PV Inverter System Reliability Assessment with High-Performance Computing
The overall cost of photovoltaic (PV) systems has shown a downward trend during the last decade; however, PV inverter failures account for the highest cost of operation and maintenance. To address this, reliability tools with powerful computation and better accuracy are required for the lifetime prediction and degradation evaluation of PV inverters. This paper proposes an event-driven parallel computing-based simulator. The proposed simulator applies high-performance computing techniques and other accessory optimization techniques-including cluster merging, adaptive model updates, and steady-state identification-to make reliability assessments for PV inverters under given input mission profiles and operating conditions with high efficiency and high fidelity. The main idea of the simulator and its workflow are introduced. Then, a demo PV inverter system simulator is implemented, and the speedup of the total simulations of the switching model reaches 123.03 times.
high-performance computing↗
Ultra-High Performance, High-Temperature Superconducting Wires via Cost-effective, Scalable, Co-evaporation Process
Long-length, high-temperature superconducting (HTS) wires capable of carrying high critical current, Ic, are required for a wide range of applications. Here, we report extremely high performance HTS wires based on 5 m thick SmBa2Cu3O7- (SmBCO) single layer films on textured metallic templates. SmBCO layer wires over 20 meters long were deposited by a cost-effective, scalable co-evaporation process using a batch-type drum in a dual chamber. All deposition parameters influencing the composition, phase, and texture of the films were optimized via a unique combinatorial method that is broadly applicable for co-evaporation of other promising complex materials containing several cations. Thick SmBCO layers deposited under optimized conditions exhibit excellent cube-on-cube epitaxy. Such excellent structural epitaxy over the entire thickness results in exceptionally high Ic performance, with average Ic over 1000 A/cm for the entire 22 meter long wire and maximum Ic over 1,500 A/cm for a short 12 cm long tape. The Ic values reported in this work are the highest values ever reported from any lengths of cuprate-based HTS wire or conductor.
Kim, Dr. Hosup↗
A High Performance Computing Platform for Performing High-Volume Studies With Windows-based Power Grid Tools
Serial Windows-based programs are widely used in power utilities. For applications that require high volume simulations, the single CPU runtime can be on the order of days or weeks. The lengthy runtime, along with the availability of low cost hardware, is leading utilities to seriously consider High Performance Computing (HPC) techniques. However, the vast majority of the HPC computers are still Linux-based and many HPC applications have been custom developed external to the core simulation engine without consideration for ease of use. This has created a technical gap for applying HPC-based tools to today’s power grid studies. To fill this gap and accelerate the acceptance and adoption of HPC for power grid applications, this paper presents a prototype of generic HPC platform for running Windows-based power grid programs on Linux-based HPC environment. The preliminary results show that the runtime can be reduced from weeks to hours to improve work efficiency.
High-performance computing, power grid, power syst↗
High performance aluminum–cerium alloys for high-temperature applications
Light-weight high-temperature alloys are important to the transportation industry where weight, cost, and operating temperature are major factors in the design of energy efficient vehicles. Aluminum alloys fill this gap economically but lack high-temperature mechanical performance. Alloying aluminum with cerium creates a highly castable alloy, compatible with traditional aluminum alloy additions, that exhibits dramatically improved high-temperature performance. These compositions display a room temperature ultimate tensile strength of 400 MPa and yield strength of 320 MPa, with 80% mechanical property retention at 240 °C. A mechanism is identified that addresses the mechanical property stability of the Al-alloys to at least 300 °C and their microstructural stability to above 500 °C which may enable applications without the need for heat treatment. Lastly, neutron diffraction under load provides insight into the unusual mechanisms driving the mechanical strength.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Characterization of organosolv switchgrass lignin by using high performance liquid chromatography/high resolution tandem mass spectrometry using hydroxide-doped negative-ion mode electrospray ionization
Method for identification of compounds in organosolv lignin.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Comparative Performance Evaluation of High-performance Data Transfer Tools
Data transfer in wide-area networks has been long studied in different contexts, from data sharing among data centers to online access to scientific data. Many software tools and platforms have been developed to facilitate easy, reliable, fast, and secure data transfer over wide area networks, such as GridFTP, FDT, bbcp, mdtmFTP, and XDD. However, few studies have shown the full capabilities of existing data transfer tools from the perspective of whether such tools have fully adopted state-of-the-art techniques through meticulous comparative evaluations. In this paper, we evaluate the performance of the four highperformance data transfer tools (GridFTP, FDT, mdtmFTP, and XDD) in various environments. Our evaluation suggests that each tool has strengths and weaknesses. FDT and GridFTP perform consistently in diverse environments. XDD and mdtmFTP show improved performance in limited environments and datasets during our evaluation. Unlike other studies on data transfer tools, we also evaluate the predictability of the tools' performance, an important factor for scheduling different stages of science workflows. Performance predictability also helps in (auto)tuning the configurable parameters of the data transfer tool. We apply statistical learning techniques such as linear/polynomial regression, and k-nearest neighbors (kNN), to assess the performance predictability of each tool using its control parameters. Our results show that we can achieve good prediction performance for GridFTP and mdtmFTP using linear regression and kNN, respectively.
Nadig, Deepak↗
Structure of Methylammonium Lead Iodide Within Mesoporous Titanium Dioxide: Active Material in High Performance Perovskite Solar Cells
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solar (photovoltaic), electrodes - solar, charge t↗
PandAna: A Python Analysis Framework for Scalable High Performance Computing in High Energy Physics
Modern experiments in high energy physics analyze millions of events recorded in particle detectors to select the events of interest and make measurements of physics parameters. These data can often be stored as tabular data in files with detector information and reconstructed quantities. Current techniques for event selection in these files lack the scalability needed for high performance computing environments. We describe our work to develop a high energy physics analysis framework suitable for high performance computing. This new framework utilizes modern tools for reading files and implicit data parallelism. Framework users analyze tabular data using standard, easy-to-use data analysis techniques in Python while the framework handles the file manipulations and parallelism without the user needing advanced experience in parallel programming. In future versions, we hope to provide a framework that can be utilized on a personal computer or a high performance computing cluster with little change to the user code.
Groh, Micah↗
Scalability of high-performance PDE solvers
Performance tests and analyses are critical to effective high-performance computing software development and are central components in the design and implementation of computational algorithms for achieving faster simulations on existing and future computing architectures for large-scale application problems. In this article, we explore performance and space-time trade-offs for important compute-intensive kernels of large-scale numerical solvers for partial differential equations (PDEs) that govern a wide range of physical applications. We consider a sequence of PDE-motivated bake-off problems designed to establish best practices for efficient high-order simulations across a variety of codes and platforms. We measure peak performance (degrees of freedom per second) on a fixed number of nodes and identify effective code optimization strategies for each architecture. In addition to peak performance, we identify the minimum time to solution at 80% parallel efficiency. The performance analysis is based on spectral and p-type finite elements but is equally applicable to a broad spectrum of numerical PDE discretizations, including finite difference, finite volume, and h-type finite elements.
97 MATHEMATICS AND COMPUTING↗
High-performance high-resolution semi-Lagrangian tracer transport on a sphere
Current climate models have a limited ability to increase spatial resolution because numerical stability requires the time step to decrease. We describe a semi-Lagrangian method for tracer transport that is stable for arbitrary Courant numbers, and we test a parallel implementation discretized on the cubed sphere. The method includes a fixer that conserves mass and constrains tracers to a physical range of values. The method shows third-order convergence and maintains nonlinear tracer correlations to second order. It shows optimal accuracy at Courant numbers of 10-20, more than an order of magnitude higher than explicit methods. We present parallel performance in terms of strong scaling, weak scaling, and spatial scaling (where the time step stays constant while the resolution increases). For a 0.2° test with 100 tracers, the implementation scales efficiently to 10,000 MPI tasks.
Computer Science↗