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At least 1,675 records · Page 93

GPU Acceleration of Large-Scale Full-Frequency GW Calculations

Many-body perturbation theory is a powerful method to simulate electronic excitations in molecules and materials starting from the output of density functional theory calculations. By implementing the theory efficiently so as to run at scale on the latest leadership high-performance computing systems it is possible to extend the scope of GW calculations. Here, we present a GPU acceleration study of the full-frequency GW method as implemented in the WEST code. Excellent performance is achieved through the use of (i) optimized GPU libraries, e.g., cuFFT and cuBLAS, (ii) a hierarchical parallelization strategy that minimizes CPU-CPU, CPU-GPU, and GPU-GPU data transfer operations, (iii) nonblocking MPI communications that overlap with GPU computations, and (iv) mixed precision in selected portions of the code. A series of performance benchmarks has been carried out on leadership high-performance computing systems, showing a substantial speedup of the GPU-accelerated version of WEST with respect to its CPU version. Good strong and weak scaling is demonstrated using up to 25 920 GPUs. Finally, we showcase the capability of the GPU version of WEST for large-scale, full-frequency GW calculations of realistic systems, e.g., a nanostructure, an interface, and a defect, comprising up to 10 368 valence electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Porting Fragmentation Methods to Graphical Processing Units Using an OpenMP Application Programming Interface: Offloading the Fock Build for Low Angular Momentum Functions

Here, a framework to offload four-index two-electron repulsion integrals to graphical processing units (GPUs) using OpenMP is discussed. The method has been applied to the Fock build for low angular momentum s and p functions in both the restricted Hartree–Fock (RHF) and in the effective fragment molecular orbital (EFMO) framework. Benchmark calculations for the GPU code for the pure RHF method show an increasing speedup relative to the existing OpenMP CPU code in GAMESS from 1.04 to 52× for clusters of 70–569 water molecules. The parallel efficiency on 24 NVIDIA V100 GPU boards also increases when increasing the system size: from 75 to 94% for water clusters that contain 303–1120 molecules. In the EFMO framework, the GPU Fock build shows a high linear scalability up to 4608 V100s with a parallel efficiency of 96% for calculations on a solvated mesoporous silica nanoparticle system with ~67,000 basis functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid Evaluation of Amine-Functionalized Solvents for Biomass Deconstruction Using High-Throughput Screening and One-Pot Enzymatic Saccharification

Efficient and sustainable pretreatment of lignocellulosic biomass is critical for biofuel and biochemical production, yet its optimization is often hindered by slow, labor-intensive experimental methods. Here, we report the first demonstration of a custom-built, miniaturized, high-throughput screening platform integrated with one-pot enzymatic saccharification, enabling parallel evaluation of solvent type, feedstock, and temperature with minimal material use and high reproducibility. As a proof-of-concept, the HTX platform was used to screen five amine-functionalized solvents, including isopropanolamine, butylamine, N-methylbutylamine, ethanolamine, and ethanolamine acetate across three bioenergy crops (sorghum, poplar, and switchgrass) and pretreatment temperatures ranging from 80 to 140 °C. Vacuum drying successfully removed more than 99% of the solvents from the pretreated biomass, eliminating the need for water washing prior to saccharification. Isopropanolamine and N-methylbutylamine yielded the highest glucose (70–80%) and xylose (58–67%) release, with trends reflecting feedstock recalcitrance. The produced hydrolysates supported robust growth of an engineered strain of the yeast Rhodosporidium toruloides, confirming biocompatibility. This high-throughput platform provides a scalable, feedstock-agnostic framework for rapid pretreatment screening, accelerating solvent–feedstock pairing and process optimization. Its ability to integrate pretreatment, solvent removal, saccharification, and microbial conversion in a miniaturized format offers significant advantages for cost-competitive biorefinery development.

Biomass↗

Monte Carlo explicitly correlated second-order many-body perturbation theory

A stochastic algorithm is proposed and implemented that computes a basis-set-incompleteness (F12) correction to an ab initio second-order many-body perturbation energy as a short sum of 6- to 15-dimensional integrals of Gaussian-type orbitals, an explicit function of the electron-electron distance (geminal), and its associated excitation amplitudes held fixed at the values suggested by Ten-no. The integrals are directly evaluated (without a resolution-of-the-identity approximation or an auxiliary basis set) by the Metropolis Monte Carlo method. Applications of this method to 17 molecular correlation energies and 12 gas-phase reaction energies reveal that both the nonvariational and variational formulas for the correction give reliable correlation energies (98% or higher) and reaction energies (within 2 kJ mol -1 with a smaller statistical uncertainty) near the complete-basis-set limits by using just the aug-cc-pVDZ basis set. The nonvariational formula is found to be 2–10 times less expensive to evaluate than the variational one, though the latter yields energies that are bounded from below and is, therefore, slightly but systematically more accurate for energy differences. Being capable of using virtually any geminal form, the method confirms the best overall performance of the Slater-type geminal among 6 forms satisfying the same cusp conditions. Lastly, not having to precompute lower-dimensional integrals analytically, to store them on disk, or to transform them in a nonscalable dense-matrix-multiplication algorithm, the method scales favorably with both system size and computer size; the cost increases only as O(n 4 ) with the number of orbitals (n), and its parallel efficiency reaches 99.9% of the ideal case on going from 16 to 4096 computer processors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NEW TECHNIQUES FOR HIGH-CONTRAST IMAGING WITH ADI: THE ACORNS-ADI SEEDS DATA REDUCTION PIPELINE

We describe Algorithms for Calibration, Optimized Registration, and Nulling the Star in Angular Differential Imaging (ACORNS-ADI), a new, parallelized software package to reduce high-contrast imaging data, and its application to data from the SEEDS survey. We implement several new algorithms, including a method to register saturated images, a trimmed mean for combining an image sequence that reduces noise by up to {approx}20%, and a robust and computationally fast method to compute the sensitivity of a high-contrast observation everywhere on the field of view without introducing artificial sources. We also include a description of image processing steps to remove electronic artifacts specific to Hawaii2-RG detectors like the one used for SEEDS, and a detailed analysis of the Locally Optimized Combination of Images (LOCI) algorithm commonly used to reduce high-contrast imaging data. ACORNS-ADI is written in python. It is efficient and open-source, and includes several optional features which may improve performance on data from other instruments. ACORNS-ADI requires minimal modification to reduce data from instruments other than HiCIAO. It is freely available for download at www.github.com/t-brandt/acorns-adi under a Berkeley Software Distribution (BSD) license.

79 ASTRONOMY AND ASTROPHYSICS↗

Probing plasma wakefields using electron bunches generated from a laser wakefield accelerator

Here, we show experimental results of probing the electric field structure of plasma wakes by using femtosecond relativistic electron bunches generated from a laser wakefield accelerator. Snapshots of laser-driven linear wakes in plasmas with different densities and density gradients are captured. The spatiotemporal evolution of the wake in a plasma density up-ramp is recorded. Two parallel wakes driven by a laser with a main spot and sidelobes are identified in the experiment and reproduced in simulations. The capability of this new method for capturing the electron- and positron-driven wakes is also shown via 3D particle-in-cell simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Aces4: A Platform for Computational Chemistry Calculations with Extremely Large Block-Sparse Arrays

Aces4 is a parallel programming platform comprising a DSL for Computational Chemistry and its runtime system. It offers a convenient way to express parallelism together with extensive support for extremely large, possibly sparse, distributed arrays. It aids scientists in the creation of performant, scalable, massively parallel programs that can effectively take advantage of leadership class computing systems to address important scientific questions. Aces4 has enabled the development and implementation of new methods in electronic structure theory which are breaking new ground in their ability to perform highly accurate calculations on ever larger molecular systems. In this paper the design of Aces4, which is based on the the Super Instruction Architecture approach, is described. Experimental scaling results for Molecular Cluster Perturbation Theory, a new method enabled by Aces4, and CCSD, a widely used computational chemistry method are given.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Distributed-Memory Parallel Symmetric Nonnegative Matrix Factorization

We develop the first distributed-memory parallel implementation of Symmetric Nonnegative Matrix Factorization (SymNMF), a key data analytics kernel for clustering and dimensionality reduction. Our implementation includes two different algorithms for SymNMF, which give comparable results in terms of time and accuracy. The first algorithm is a parallelization of an existing sequential approach that uses solvers for non symmetric NMF. The second algorithm is a novel approach based on the Gauss-Newton method. It exploits second-order information without incurring large computational and memory costs. We evaluate the scalability of our algorithms on the Summit system at Oak Ridge National Laboratory, scaling up to 128 nodes (4,096 cores) with 70% efficiency. Additionally, we demonstrate our software on an image segmentation task.

Eswar, Srinivas↗

Modeling of single event transients with dual double-exponential current sources: Implications for logic cell characterization

Single event effects (SEE) are a reliability concern for modern microelectronics. Bit corruptions can be caused by single event upsets (SEUs) in the storage cells or by sampling single event transients (SETs) from a logic path. Likewise, an accurate prediction of soft error susceptibility from SETs requires good models to convert collected charge into compact descriptions of the current injection process. This paper describes a simple, yet effective, method to model the current waveform resulting from a charge collection event for SET circuit simulations. The model uses two double-exponential current sources in parallel, and the results illustrate why a conventional model based on one double-exponential source can be incomplete. Furthermore, a small set of logic cells with varying input conditions, drive strength, and output loading are simulated to extract the parameters for the dual double-exponential current sources. As a result, the parameters are based upon both the node capacitance and the restoring current (i.e., drive strength) of the logic cell.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Improving I/O Performance for Exascale Applications through Online Data Layout Reorganization

The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity and record turn-around time. Many of these codes are based on particle-mesh methods and use advanced algorithms, especially dynamic load-balancing and mesh-refinement, to achieve high performance on Exascale machines. Yet, as such algorithms improve parallel application efficiency, they raise new challenges for I/O logic due to their irregular and dynamic data distributions. Thus, while the enormous data rates of Exascale simulations already challenge existing file system write strategies, the need for efficient read and processing of generated data introduces additional constraints on the data layout strategies that can be used when writing data to secondary storage. We review these I/O challenges and introduce two online data layout reorganization approaches for achieving good tradeoffs between read and write performance. We demonstrate the benefits of using these two approaches for the ECP particle-in-cell simulation WarpX, which serves as a motif for a large class of important Exascale applications. Here, we show that by understanding application I/O patterns and carefully designing data layouts we can increase read performance by more than 80 percent.

97 MATHEMATICS AND COMPUTING↗

Fast optimization and dose calculation in scanned ion beam therapy

Purpose: Particle therapy (PT) has advantages over photon irradiation on static tumors. An increased biological effectiveness and active target conformal dose shaping are strong arguments for PT. However, the sensitivity to changes of internal geometry complicates the use of PT for moving organs. In case of interfractionally moving objects adaptive radiotherapy (ART) concepts known from intensity modulated radiotherapy (IMRT) can be adopted for PT treatments. One ART strategy is to optimize a new treatment plan based on daily image data directly before a radiation fraction is delivered [treatment replanning (TRP)]. Optimizing treatment plans for PT using a scanned beam is a time consuming problem especially for particles other than protons where the biological effective dose has to be calculated. For the purpose of TRP, fast optimization and fast dose calculation have been implemented into the GSI in-house treatment planning system (TPS) TRiP98. Methods: This work reports about the outcome of a code analysis that resulted in optimization of the calculation processes as well as implementation of routines supporting parallel execution of the code. To benchmark the new features, the calculation time for therapy treatment planning has been studied. Results: Compared to the original version of the TPS, calculation times for treatment planning (optimization and dose calculation) have been improved by a factor of 10 with code optimization. The parallelization of the TPS resulted in a speedup factor of 12 and 5.5 for the original version and the code optimized version, respectively. Hence the total speedup of the new implementation of the authors' TPS yielded speedup factors up to 55. Conclusions: The improved TPS is capable of completing treatment planning for ion beam therapy of a prostate irradiation considering organs at risk in this has been overseen in the review process. Also see below 6 min.

60 APPLIED LIFE SCIENCES↗

SU-E-T-19: A Comparison of the Dosimetric Effects of Brass Mesh and Superflab Boluses

Purpose: We compared the dosimetric effects of brass mesh (Whiting and Davis, Attleboro Falls, MA) and Superflab (CNMC, Nashville, TN) boluses to verify equivalence between the two. Brass mesh bolus may be a convenient alternative to traditional bolus as it better conforms to the skin surface. Methods: Measurements were taken using a 6MV 10×10cm field produced by an Infinity linear accelerator (Elekta, Stockholm, Sweden) in a solid water phantom using a parallel plate ion chamber (Model 96035, Keithley Instruments, Cleveland, OH). Measurements compared 0.5cm and 1cm of Superflab to one to six layers of brass bolus mesh. Measurements were performed at depths from 0cm (‘skin’) to 10cm. Oblique beams were not studied. Results: Four layers of brass mesh were equivalent to 0.5cm Superflab within 5% at all depths. Six layers of brass compares most favorably with 0.5cm Superflab, with doses at all depths within 3%. Six layers of brass were not fully equivalent to 1cm Superflab, although the agreement was within 5% for depths greater than 3mm. Surface dose was 12% lower than 1cm Superflab. Surface dose can be up to 34% different between Superflab and brass mesh, but is less than 5% different with 4–6 layers of brass when compared to 0.5cm Superflab. To achieve surface dose agreement better than 5% compared to 1cm Superflab, more than 6 layers would be needed. The attenuation at depth was a maximum of 0.17cm per layer. Conclusion: Between four and six layers of brass mesh can be equivalent to 0.5cm Superflab, depending on the level of agreement desired. Equivalence within 5% at all depths to 1cm Superflab was not achieved even with six layers. This data agrees with measurements taken by Utsunomiya et al. (2010). More point measurements at shallower depths should be taken prior to clinical implementation of brass bolus mesh.

60 APPLIED LIFE SCIENCES↗

Controlling colloidal crystals via morphing energy landscapes and reinforcement learning

We report a feedback control method to remove grain boundaries and produce circular shaped colloidal crystals using morphing energy landscapes and reinforcement learning–based policies. We demonstrate this approach in optical microscopy and computer simulation experiments for colloidal particles in ac electric fields. First, we discover how tunable energy landscape shapes and orientations enhance grain boundary motion and crystal morphology relaxation. Next, reinforcement learning is used to develop an optimized control policy to actuate morphing energy landscapes to produce defect-free crystals orders of magnitude faster than natural relaxation times. Morphing energy landscapes mechanistically enable rapid crystal repair via anisotropic stresses to control defect and shape relaxation without melting. This method is scalable for up to at least N = 10 3 particles with mean process times scaling as N 0.5 . Further scalability is possible by controlling parallel local energy landscapes (e.g., periodic landscapes) to generate large-scale global defect-free hierarchical structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Study of a macrodefect in a silicon carbid single crystal by means of X-ray phase contrast

The morphology of a macrodefect in a single-crystal silicon carbide wafer has been investigated by the computer simulation of an experimental X-ray phase-contrast image. A micropipe, i.e., a long cavity with a small (elliptical in the general case) cross section, in a single crystal has been considered as a macrodefect. A far-field image of micropipe has been measured with the aid of synchrotron radiation without a monochromator. The parameters of micropipe elliptical cross section are determined based on one projection in two directions: parallel and perpendicular to the X-ray beam propagation direction, when scanning along the pipe axis. The results demonstrate the efficiency of the phase contrast method supplemented with computer simulation for studying such macrodefects when the defect position in the sample volume is unknown beforehand.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Polynomial Preconditioned Arnoldi with Stability Control

Polynomial preconditioning can improve the convergence of the Arnoldi method for computing eigenvalues. Such preconditioning significantly reduces the cost of orthogonalization; for difficult problems, it can also reduce the number of matrix-vector products. Parallel computations can particularly benefit from the reduction of communication-intensive operations. Additoinally, the GMRES algorithm provides a simple and effective way of generating the preconditioning polynomial. For some problems high degree polynomials are especially effective, but they can lead to stability problems that must be mitigated. A two-level “double polynomial preconditioning” strategy provides an effective way to generate high-degree preconditioners.

97 MATHEMATICS AND COMPUTING↗

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

Abstract Background Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. Methods We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Results Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. Conclusion The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

GEOS Code Development Road Map

GEOS is a massively parallel computational framework designed to enable HPC-based simulations of subsurface reservoir stimulation activities with the goal of optimizing current operations and evaluating innovative stimulation methods. GEOS will enable coupling of different solvers associated with the various physical processes occurring during reservoir stimulation in unique and sophisticated ways, adapted to various geologic settings, materials and stimulation methods. The overall architecture of the framework includes consistent data structures and will allow incorporation of additional physical and materials models as demanded by future applications. Along with predicting the initiation, propagation and reactivation of fractures, GEOS will also generate a seismic source term that can be linked with seismic wave propagation codes to generate synthetic microseismicity at surface and downhole arrays. Similarly, the output from GEOS can be linked with existing fluid/thermal transport codes. GEOS can also be linked with existing, non-intrusive uncertainty quantification schemes to constrain uncertainty in its predictions and sensitivity to the various parameters describing the reservoir and stimulation operations. We anticipate that an implicit-explicit 3D version of GEOS, including a preliminary seismic source model, will be available for parametric testing and validation against experimental and field data by Oct. 1, 2013.

02 PETROLEUM↗

Massively Parallel Capability in Sierra/SD for Simulation Vibration with Piezoelectrics

Sierra/SD is an engineering structural dynamics code that provides Sandia and other customers a tool to model structural and acoustic physics on large complex physical systems using massively parallel processing. This report provides a detailed overview on Sierra/SD’s most recent physics package: coupled electro-mechanical physics. This capability uses the finite element method to model coupled electro-mechanical physics exhibited by piezoelectric materials. This report provides an applications overview, theory overview, and verification examples demonstrating the electro-mechanical physics modeling capabilities of Sierra/SD.

97 MATHEMATICS AND COMPUTING↗