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DOE OSTI2019

Use cases of lossy compression for floating-point data in scientific data sets

Architectural and technological trends of systems used for scientific computing call for a significant reduction of scientific data sets that are composed mainly of floating-point data. Here, this article surveys and presents experimental results of currently identified use cases of generic lossy compression to address the different limitations of scientific computing systems. The article shows from a collection of experiments run on parallel systems of a leadership facility that lossy data compression not only can reduce the footprint of scientific data sets on storage but also can reduce I/O and checkpoint/restart times, accelerate computation, and even allow significantly larger problems to be run than without lossy compression. In conclusion, these results suggest that lossy compression will become an important technology in many aspects of high performance scientific computing. Because the constraints for each use case are different and often conflicting, this collection of results also indicates the need for more specialization of the compression pipelines.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Understanding irradiation growth through atomistic simulations: Defect diffusion and clustering in α-zirconium and the influence of alloying elements - 2016-0093

Irradiation-induced structural changes of α-zirconium alloys and in particular the effect of iron were investigated by molecular dynamics simulations using embedded atom potentials derived from first-principles calculations. The simulations revealed that at temperatures between 500 and 600 K self-interstitial atoms (SIAs) diffuse rapidly in a cooperative movement, preferably parallel to basal planes (a directions; ), forming nano-clusters with an extension in and . Vacancies diffuse more slowly than SIAs and remain isolated for a longer period of time. Nano-clusters associated with SIAs cause a pronounced overall expansion in a directions, as well as local strains. Under compressive strain in the c direction, vacancy diffusivity increases in the c direction. In contrast, the diffusivity of SIAs increases in the c direction under a tensile strain in the c direction. SIA nano-clusters are highly mobile within basal planes. Vacancy clusters grow by merging, leading to a contraction in the a direction, compensating for the expansion caused by SIA nano-clusters and possibly contributing to the plateau in growth after the initial rapid expansion. At the onset of breakaway growth, possibly due to stress buildup, the vacancy nano-clusters can condense into c loops, thereby diminishing the compensation effect. The alloying elements iron, nickel, chromium, and niobium liberated from secondary phase particles under irradiation or already in solution are attracted to vacancies and SIAs and are found inside vacancy and SIA loops. The interaction of alloying elements with defect clusters is discussed, with a particular focus on iron. Iron has been found to promote cluster formation in zirconium, and the structures of zirconium-iron clusters have been analyzed. Tin is repelled by SIA clusters and only weakly attracted by vacancies. Niobium impedes the diffusion of SIAs (and therefore may increase annihilation rates with nearby vacancies) and does not destabilize vacancy or SIA clusters. Ab initio calculations of the dimensional and elastic coefficients of the intermetallic phases occurring in secondary phase particles, such as Zr{sub 2}Fe and Zr{sub 3}Fe, are presented, allowing an assessment of local strains in a zirconium matrix. Thus, novel results from extended molecular dynamics simulations provide new insights and contribute to a deeper understanding of the complex mechanisms causing irradiation-induced dimensional changes and the breakaway growth of zirconium alloys. (authors)

36 MATERIALS SCIENCE↗

DOE OSTI2020

HPC-enabled computation of demand models at scale

The purpose of this project is to examine the energy impact of urban-scale traffic for the Los Angeles Basin by developing and implementing a scalable traffic assignment model. An energy optimization function will be posed and when integrated into the optimization code for travel assignment it can be mathematically proven to converge. The energy optimization function can then be compared to the typical travel time optimization that is traditionally used in traffic assignment models. The analysis will begin with static traffic assignment models with the routing for all origin and destinations computed in parallel on high performance computing facilities. Convergence of the numerical methods rely on the solution of convex programs (or extensions of these). This step will mostly consist of demonstrating the ability to parallelize the Frank Wolfe algorithm on various platforms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

HPC4Mobilty w/ UCB

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Progress Report of Alloy 709 Performance in Liquid Sodium

With improved high-temperature properties, Alloy 709 shows great potential for advanced reactor applications. To understand the effects of sodium on A709, small tensile specimens were machined from two commercial heats and subject to sodium exposure in two forced convection loops operated by Argonne. Thermal aging experiments were also conducted in parallel to isolate any sodium-specific effects. An increasing trend in yield strength and a decrease trend in ultimate tensile strength can be seen with the increasing exposure time, suggesting microstructural changes at these temperatures. Nonetheless, the thermally aged and sodium exposed samples behaved similarly, implying no sodium-specific effect at these temperatures. In contrast, 316H SS exposed to sodium at 650°C showed a strong sodium effect. The different responses of A709 and 316H SS to sodium exposure is of interest and requires additional effort to understand. The cold traps of the sodium loop were replaced early in FY23. During a maintenance operation, an unexpected sodium leak incident occurred at one of the sodium loops, triggering an emergency response. An investigation into the incident revealed that the leak happened at a VCR fitting on the recently replaced cold trap. The metal gasket of the leaked VCR fitting was not compressed sufficiently. A dimensional mismatch between the new component and old piping configuration was responsible for a significant misalignment. A new cold trap with improved design is in production. The new design provides additional flexibility and an access point for post-installation helium leak check and for venting of trapped gas. These design features will make the system more error-tolerant and the installation quality verifiable. A thermodynamic analysis was performed to understand the carburization-decarburization behavior of A709 in sodium environment. The equilibrium carbon activity in the alloy was evaluated with M 23 C 6 , TiC, and NbC. The carburization-decarburization boundary was calculated with different methods developed previously. The results suggests that A709 will be carburized in SMT-1 and SMT-2, and can be decarburized in low-carbon-activity environments such as EBR-II at temperatures above 620-650°C. Nonetheless, A709 should be less likely to be decarburized than 316H SS when exposed to the same low-carbon-activity environment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Solar wind magnetic fluctuations and electron non-thermal temperature anisotropy: survey of Wind-SWE-VEIS observations

The solar wind electron velocity distribution function (eVDF) exhibits a variety of non-thermal features that deviate from thermal equilibrium. These deviations from equilibrium provide a local source for electromagnetic fluctuation emissions, including the commonly observed electron whistler-cyclotron and firehose instabilities. We present a systematic analysis of Wind-SWE-VEIS observations of solar wind electron plasma and associated Wind-MFI observed magnetic fluctuations. For the first time using the full solar wind electron distribution and its moments, without separation of the various electron components, we show clear evidence that the temperature anisotropy threshold of the parallel electron cyclotron anisotropic instability bounds solar wind electrons during slow solar wind periods. We also demonstrate that during periods of slow solar wind, collisions—while infrequent—are the dominant mechanism by which solar wind electrons are constrained, leading to isotropization. During fast solar wind periods, magnetic fluctuations and solar wind anisotropies are enhanced above the parallel whistler anisotropic threshold boundary and collisional effects are significantly reduced. Preliminary calculations further show that the oblique electron whistler mirror anisotropic instability bounds both the slow and fast solar wind. Regardless of speed, the solar wind electron thermal anisotropy appears globally bounded by the parallel electron firehose instability for anisotropies T{sub e⊥}/T{sub e||}<1. Our results indicate that collisions, while infrequent, play a necessary role in regulating the solar wind eVDFs. In striking contrast to solar wind ions, solar wind electron plasma, when considered globally as a single eVDF, is only marginally stable with respect to parallel propagating instabilities.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Global distributed file append using log-structured file system

Techniques are provided for globally appending data from a group of distributed processes to a shared file using a log-structured file system. Data generated by a plurality of processes in a parallel computing system are appended to a shared file by storing the data to the shared file using a log-structured file system (such as a Parallel Log-Structured File System (PLFS)); and generating an index entry for the data, the index entry comprising a logical offset entry and a timestamp entry indicating a time of the storage, wherein the logical offset entry is resolved at read time. The logical offset entry can be populated with an append placeholder that is resolved when the shared file is read. At read time, a plurality of the index entries associated with the shared file can be sorted using the timestamp entry to deliver the requested shared file to a requesting application.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Real-time supervisory control implementation of SmAHTR power plant - 143

This paper discusses an implementation of a supervisory control system for a nuclear power plant model using Small modular Advanced High Temperature Reactors (SmAHTR). The simulation operates in real-time using a network of computer agents, implemented on Raspberry Pi's (RPi's), where each major task is performed by one or more RPi's running calculations in parallel. The system architecture contains local, module, master, and operator actions to automate all aspects of the plant. Local level controllers run individual control loops to ensure the desired reference signals are met. The module level controllers set the local level reference signals within each SMR unit and detect sensor and actuator failures to adjust those reference signals as needed. Master level controllers balance plant power by calculating required heat power from each reactor and electric power from each generator and sending that data to the module controllers. Finally, the operator level contains an operator interface to summarize data and faults gathered through the controller levels, with options to review plant and reactor details as desired. This control implementation allows the plant to run autonomously, load follow a desired electrical power curve, and detect a growing number of fault scenarios. Ultimately, this type of supervisory control system will reduce labor-intensive surveillance and testing and allow fewer operators to more safely monitor an entire plant. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2019

PHISICS User Manual

PHISICS (Parallel and Highly Innovative Simulation for INL Code System) is a reactor physics package developed at the Idaho National Laboratory. It is composed of several modules: a nodal and semi-structured transport core solver (INSTANT), a depletion module (MRTAU), a time-dependent solver (TimeIntegrator), a cross-section interpolation and manipulation framework (MIXER), a SuperHomogenization scheme (SPH) a criticality search module (CRITICALITY), a fuel management and shuffling component (SHUFFLE) and a coupling API with RELAP5-3D. PHISICS has been built in a highly modular fashion so that different physical models can be activated or deactivated depending on the physics relevant to the particular type of analysis. This approach simplifies development as well as mid- and long-term maintenance of the code. PHISICS is entirely written in FORTRAN 95/2003. Each of its components is fully parallelized and designed to take full advantage of shared-memory computers (multiprocessor desktops and workstations) and middle to large high-performance computing systems (10 to 1000 processors). The aim of this document is to detail the input requirements for PHISICS (and all its modules) focusing on the input structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

Real time time-dependent density functional theory using higher order finite-element methods

We present a computationally efficient approach to solve the time-dependent Kohn-Sham equations in real time using higher order finite-element spatial discretization, applicable to both pseudopotential and all-electron calculations. To this end, we develop an a priori mesh adaption technique, based on the semidiscrete (discrete in space but continuous in time) error estimate on the time-dependent Kohn-Sham orbitals, to construct an efficient finite-element discretization. Subsequently, we obtain the full-discrete error estimate to guide our choice of the time step. We employ spectral finite elements along with special reduced order quadrature to render the overlap matrix diagonal, thereby simplifying the inversion of the overlap matrix that features in the evaluation of the discrete time-evolution operator. We use the second-order Magnus operator as the time-evolution operator, wherein the action of the discrete Magnus operator, expressed as exponential of a matrix, on the Kohn-Sham orbitals is obtained efficiently through an adaptive Lanczos iteration. We observe close to optimal rates of convergence of the dipole moment with respect to spatial and temporal discretization, for both pseudopotential and all-electron calculations. We demonstrate a staggering 100-fold reduction in the computational time afforded by higher order finite elements over linear finite elements, for both pseudopotential and all-electron calculations. Further, for similar level of accuracy, we obtain significant computational savings by our approach as compared to state-of-the-art finite-difference methods. Here, we also demonstrate the competence of higher order finite elements for all-electron benchmark systems. Lastly, we observe good parallel scalability of the proposed method on many hundreds of processors.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Toward General Software Level Silent Data Corruption Detection for Parallel Applications

Silent data corruption (SDC) poses a great challenge for high-performance computing (HPC) applications as we move to extreme-scale systems. Mechanisms have been proposed that are able to detect SDC in HPC applications by using the peculiarities of the data (more specifically, its “smoothness” in time and space) to make predictions. However, these data-analytic solutions are still far from fully protecting applications to a level comparable with more expensive solutions such as full replication. In this work, we propose partial replication to overcome this limitation. More specifically, we have observed that not all processes of an MPI application experience the same level of data variability at exactly the same time. Thus, we can smartly choose and replicate only those processes for which the lightweight data-analytic detectors would perform poorly. In addition, we propose a new evaluation method based on the probability that a corruption will pass unnoticed by a particular detector (instead of just reporting overall single-bit precision and recall). Here in our experiments, we use four applications dealing with different explosions. Finally, our results indicate that our new approach can protect the MPI applications analyzed with 7–70% less overhead (depending on the application) than that of full duplication with similar detection recall.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Stable parallel training of Wasserstein conditional generative adversarial neural networks

In this work, we propose a stable, parallel approach to train Wasserstein conditional generative adversarial neural networks (W-CGANs) under the constraint of a fixed computational budget. Differently from previous distributed GANs training techniques, our approach avoids inter-process communications, reduces the risk of mode collapse and enhances scalability by using multiple generators, each one of them concurrently trained on a single data label. The use of the Wasserstein metric also reduces the risk of cycling by stabilizing the training of each generator. We illustrate the approach on the CIFAR10, CIFAR100, and ImageNet1k datasets, three standard benchmark image datasets, maintaining the original resolution of the images for each dataset. Performance is assessed in terms of scalability and final accuracy within a limited fixed computational time and computational resources. To measure accuracy, we use the inception score, the Fréchet inception distance, and image quality. An improvement in inception score and Fréchet inception distance is shown in comparison to previous results obtained by performing the parallel approach on deep convolutional conditional generative adversarial neural networks as well as an improvement of image quality of the new images created by the GANs approach. Weak scaling is attained on both datasets using up to 2000 NVIDIA V100 GPUs on the OLCF supercomputer Summit.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Computational Complexity of Neuromorphic Algorithms

Neuromorphic computing has several characteristics that make it an extremely compelling computing paradigm for post Moore computation. Some of these characteristics include intrinsic parallelism, inherent scalability, collocated processing and memory, and event-driven computation. While these characteristics impart energy efficiency to neuromorphic systems, they do come with their own set of challenges. One of the biggest challenges in neuromorphic computing is to establish the theoretical underpinnings of the computational complexity of neuromorphic algorithms. In this paper, we take the first steps towards defining the space and time complexity of neuromorphic algorithms. Specifically, we describe a model of neuromorphic computation and state the assumptions that govern the computational complexity of neuromorphic algorithms. Next, we present a theoretical framework to define the computational complexity of a neuromorphic algorithm. We explicitly define what space and time complexities mean in the context of neuromorphic algorithms based on our model of neuromorphic computation. Finally, we leverage our approach and define the computational complexities of six neuromorphic algorithms: constant function, successor function, predecessor function, projection function, neuromorphic sorting algorithm and neighborhood subgraph extraction algorithm.

Date, Prasanna↗

DOE OSTI2017

From Interfaces to Bulk: Experimental-Computational Studies Across Time and Length Scales of Multi-Functional Ionic Polymers

Neutron experiments coupled with computational components have resulted in unprecedented understanding of the factors that impact the behavior of ionic structured polymers. Additionally, new computational tools to study macromolecules, were developed. In parallel, this DOE funding have enabled the education of the next generation of material researchers who are able to take the advantage neutron tools offer to the understanding and design of advanced materials. Our research has provided unprecedented insight into one of the major factors that limits the use of ionizable polymers, combining the macroscopic view obtained from the experimental techniques with molecular insight extracted from computational studies leading to transformative knowledge that will impact the design of nano-structured, materials. With the focus on model systems, of broad interest to the scientific community and to industry, the research addressed challenges that cut across a large number of polymers, independent of the specific chemical structure or the transported species.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Low-synch Gram–Schmidt with delayed reorthogonalization for Krylov solvers

The parallel strong-scaling of iterative methods is often determined by the number of global reductions at each iteration. Low-synch Gram-Schmidt algorithms are applied here to the Arnoldi algorithm to reduce the number of global reductions and therefore to improve the parallel strong-scaling of iterative solvers for nonsymmetric matrices such as the GMRES and the Krylov-Schur iterative methods. In the Arnoldi context, the factorization is "left-looking" and processes one column at a time. Among the methods for generating an orthogonal basis for the Arnoldi algorithm, the classical Gram-Schmidt algorithm, with reorthogonalization (CGS2) requires three global reductions per iteration. A new variant of CGS2 that requires only one reduction per iteration is presented and applied to the Arnoldi algorithm. Delayed CGS2 (DCGS2) employs the minimum number of global reductions per iteration (one) for a one-column at-a-time algorithm. The main idea behind the new algorithm is to group global reductions by rearranging the order of operations. DCGS2 must be carefully integrated into an Arnoldi expansion or a GMRES solver. Numerical stability experiments assess robustness for Krylov-Schur eigenvalue computations. Performance experiments on the ORNL Summit supercomputer then establish the superiority of DCGS2 over CGS2.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Polarized fusion and potential in situ tests of fuel polarization survival in a tokamak plasma

Abstract The use of spin-polarized fusion fuels would provide a significant boost towards the ignition of a burning plasma. The cross section for D + T → α + n, would be increased by 1.5 if the fuels were injected with parallel polarization. Furthermore, our simulations demonstrate additional non-linear power gains in large-scale machines such as ITER, due to increased alpha heating. Such benefits require the survival of spin polarizations for periods comparable to the particle confinement time. During the 1980s, calculations predicted that polarizations could survive a plasma environment, although concerns persisted regarding the cumulative impacts of wall recycling. In that era, technical challenges prevented direct tests and left the large scale fueling of a power reactor beyond reach. Over the last decades, this situation has changed dramatically. Detailed simulations of ITER have predicted negligible wall recycling in a high-power reactor, and recent advances in laser-driven sources project the capability of producing large quantities of ∼100% polarized D and T. The remaining crucial step is an in-situ demonstration of polarization survival in a plasma. For this, we outline a measurement strategy using the isospin-mirror reaction, D + 3 He → α + p. Polarized 3 He avoids the complexities of handling tritium, while encompassing the same spin-physics. We evaluate two methods of delivering deuterium, using dynamically polarized Lithium-Deuteride (with vector polarization P V D of 70%) or frozen-spin Hydrogen-Deuteride (with P V D of 40%), together with a method of injecting optically-pumped 3 He (with 65% polarization). Pellets of these materials all have long polarization decay times (∼6 min for LiD at 2 K, ∼2 months for HD at 2 K, and ∼3 d for 3 He at 77 K), all far greater than a plasma shot in a research tokamak such as DIII-D (∼20 s). Both species can be propelled from a single cryogenic injection gun. We review plasma requirements and strategies for detecting polarization survival. Polarization alters both fusion yields and the angular distribution of fusion products, and each of these provides a potential signal. In this paper we simulate a selection of shots with similar characteristics in a future high-T ion H plasma, and find ratios of yields from shots with fuel spins parallel and antiparallel reaching 1.3 (HD + 3 He) to 1.6 (LiD + 3 He) over a wide range of poloidal angles. (A companion paper finds sensitivity to fusion product angular distributions as reflected in the pitch angles of protons and alphas reaching the plasma facing wall.)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

A Visual Analytics Framework for Reviewing Streaming Performance Data

Understanding and tuning the performance of extreme-scale parallel computing systems demands a streaming approach due to the computational cost of applying offline algorithms to vast amounts of performance log data. Analyzing large streaming data is challenging because the rate of receiving data and limited time to comprehend data make it difficult for the analysts to sufficiently examine the data without missing important changes or patterns. To support streaming data analysis, we introduce a visual analytic framework comprising of three modules: data management, analysis, and interactive visualization. The data management module collects various computing and communication performance metrics from the monitored system using streaming data processing techniques and feeds the data to the other two modules. The analysis module automatically identifies important changes and patterns at the required latency. In particular, we introduce a set of online and progressive analysis methods for not only controlling the computational costs but also helping analysts better follow the critical aspects of the analysis results. Finally, the interactive visualization module provides the analysts with a coherent view of the changes and patterns in the continuously captured performance data. Through a multi-faceted case study on performance analysis of parallel discrete-event simulation, we demonstrate the effectiveness of our framework for identifying bottlenecks and locating outliers.

Human-centered computing↗

DOE OSTI2026

Identification and mitigation of memory block timing issue in ITk ABCStar during ASIC production

The ABCStar is a mixed-signal front-end readout ASIC for the strips sensor portion of the ATLAS ITk detector being developed as part of the High-Luminosity LHC upgrade. In pre-production testing, a subtle design flaw was uncovered in the ABCStar that was reducing wafer yields in some manufactured lots from the expected 90% to as low as 2%. The root cause was determined to be a timing issue in the logic synthesized to control previously silicon proven memory blocks re-used for this ASIC. The solutions proposed included manufacturing process changes by the wafer foundry, changes to the operating parameters for the ABCStar in the detector, and the possibility that a redesign might be required. The two mitigation efforts were undertaken in parallel, with the process modification route a less desirable solution since already manufactured wafers would need to be scrapped in favour of the new ones. Based on a knowledge of the existing process, and testing done on the worst performing wafers, it was proposed that raising the core operating voltage of the ABCStar from 1.20V to 1.25V could address the timing issue by sufficiently speeding up its transistors. An extensive testing program that included the effects of temperature and radiation expected over the lifetime of the ITk detector was conducted to validate that approach. Those tests and studies proved that even the worst performing wafers would have yields over 80% with the 1.25V core voltage, and neither the modified process nor redesign would be required for ensuring reliable operation of the ITk. Based on testing, a further timing mitigation was implemented to provide an additional margin of reliability by increasing the duty cycle of the clock to the ABCStar. Testing of all ABCStar wafers has been completed and the production of the detector modules using these ASICs is now well underway as a result of the efforts detailed herein.

FOS: Physical sciences↗