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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

Comparative Performance Analysis of Coarse Solvers for Algebraic Multigrid on Multicore and Manycore Architectures

In this paper, we study the performance of a two-level algebraic-multigrid algorithm, with a focus on the impact of the coarse-grid solver on performance. We consider two algorithms for solving the coarse-space systems: the preconditioned conjugate gradient method and a new robust HSS-embedded low-rank sparse-factorization algorithm. Our test data comes from the SPE Comparative Solution Project for oil-reservoir simulations. We contrast the performance of our code on one 12-core socket of a Cray XC30 machine with performance on a 60-core Intel Xeon Phi coprocessor. To obtain top performance, we optimized the code to take full advantage of fine-grained parallelism and made it thread-friendly for high thread count. We also developed a bounds-and-bottlenecks performance model of the solver which we used to guide us through the optimization effort, and also carried out performance tuning in the solver’s large parameter space. Finally, as a result, significant speedups were obtained on both machines.

97 MATHEMATICS AND COMPUTING↗

Performance Evaluation of NWChem Ab-Initio Molecular Dynamics (AIMD) Simulations on the Intel® Xeon Phi™ Processor

Ab-initio Molecular Dynamics (AIMD) methods are an important class of algorithms, as they enable scientists to understand the chemistry and dynamics of molecular and condensed phase systems while retaining a first-principles-based description of their interactions. Many-core architectures such as the Intel® Xeon Phi™ processor are an interesting and promising target for these algorithms, as they can provide the computational power that is needed to solve interesting problems in chemistry. In this paper, we describe the efforts of refactoring the existing AIMD plane-wave method of NWChem from an MPI-only implementation to a scalable, hybrid code that employs MPI and OpenMP to exploit the capabilities of current and future many-core architectures. We describe the optimizations required to get close to optimal performance for the multiplication of the tall-and-skinny matrices that form the core of the computational algorithm. We present strong scaling results on the complete AIMD simulation for a test case that simulates 256 water molecules and that strong-scales well on a cluster of 1024 nodes of Intel Xeon Phi processors. We compare the performance obtained with a cluster of dual-socket Intel® Xeon® E5–2698v3 processors.

Environmental Molecular Sciences Laboratory↗

Effect of proteoglycans at interfaces as related to location, architecture, and mechanical cues

Covalently bound functional GAGs orchestrate tissue mechanics through time-dependent characteristics. The role of specific glycosaminoglycans (GAGs) at the ligament-cementum and cementum-dentin interfaces within a human periodontal complex were examined. Matrix swelling and resistance to compression under health and modeled diseased states was investigated. The presence of keratin sulfate (KS) and chondroitin sulfate (CS) GAGs at the ligament-cementum and cementum-dentin interfaces in human molars (N = 5) was illustrated by using enzymes, atomic force microscopy (AFM), and AFM-based nanoindentation. Furthermore, the change in physical characteristics of modeled diseased states through sequential digestion of keratin sulfate (KS) and chondroitin sulfate (CS) GAGs was investigated. One-way ANOVA tests with P < 0.05 were performed to determine significant differences between groups. Additionally, the presence of mineral within the seemingly hygroscopic interfaces was investigated using transmission electron microscopy. Immunohistochemistry (N = 3) indicated presence of biglycan and fibromodulin small leucine rich proteoglycans at the interfaces. Digestion of matrices with enzymes confirmed the presence of KS and CS GAGs at the interfaces by illustrating a change in ti ssue architecture and mechanics. A significant increase in height (nm), decrease in elastic modulus (GPa), and tissue deformation rate (nm/s) of the PDL-C attachment site (215 ± 63-424 ± 94 nm; 1.5 ± 0.7-0.4 ± 0.2 GPa; 21 ± 7-48 ± 22 nm/s), and cementum-dentin interface (122 ± 69-360 ± 159 nm; 2.9 ± 1.3-0.7 ± 0.3 GPa; 18 ± 4-30 ± 6 nm/s) was observed. The sequential removal of GAGs indicated loss in intricate structural hierarchy of hygroscopic interfaces. From a mechanics perspective, GAGs provide tissue recovery/resilience. Our results provide insights into the role of GAGs toward conserved tooth movement in the socket in response to mechanical loads, and modulation of potentially deleterious strain at tissue interfaces.

59 BASIC BIOLOGICAL SCIENCES↗

Separable projection integrals for higher-order correlators of the cosmic microwave sky: Acceleration by factors exceeding 100

We present a case study describing efforts to optimise and modernise “Modal”, the simulation and analysis pipeline used by the Planck satellite experiment for constraining general non-Gaussian models of the early universe via the bispectrum (or three-point correlator) of the cosmic microwave background radiation. We focus on one particular element of the code: the projection of bispectra from the end of inflation to the spherical shell at decoupling, which defines the CMB we observe today. This code involves a three-dimensional inner product between two functions, one of which requires an integral, on a non-rectangular domain containing a sparse grid. We show that by employing separable methods this calculation can be reduced to a one-dimensional summation plus two integrations, reducing the overall dimensionality from four to three. The introduction of separable functions also solves the issue of the non-rectangular sparse grid. This separable method can become unstable in certain scenarios and so the slower non-separable integral must be calculated instead. We present a discussion of the optimisation of both approaches. We demonstrate significant speed-ups of ≈100×, arising from a combination of algorithmic improvements and architecture-aware optimisations targeted at improving thread and vectorisation behaviour. The resulting MPI/OpenMP hybrid code is capable of executing on clusters containing processors and/or coprocessors, with strong-scaling efficiency of 98.6% on up to 16 nodes. We find that a single coprocessor outperforms two processor sockets by a factor of 1.3× and that running the same code across a combination of both microarchitectures improves performance-per-node by a factor of 3.38×. By making bispectrum calculations competitive with those for the power spectrum (or two-point correlator) we are now able to consider joint analysis for cosmological science exploitation of new data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Characterizing, Modeling, and Accurately Simulating Power and Energy Consumption of I/O-intensive Scientific Workflows

While distributed computing infrastructures can provide infrastructure-level techniques for managing energy consumption, application-level energy consumption models have also been developed to support energy-efficient scheduling and resource provisioning algorithms. In this work, we analyze the accuracy of a widely-used application-level model that has been developed and used in the context of scientific workflow executions. To this end, we profile two production scientific workflows on a distributed platform instrumented with power meters. We then conduct an analysis of power and energy consumption measurements. This analysis shows that power consumption is not linearly related to CPU utilization and that I/O operations significantly impact power, and thus energy, consumption. We then propose a power consumption model that accounts for I/O operations, including the impact of waiting for these operations to complete, and for concurrent task executions on multi-socket, multi-core compute nodes. We implement our proposed model as part of a simulator that allows us to draw direct comparisons between real-world and modeled power and energy consumption. Here, we find that our model has high accuracy when compared to real-world executions. Furthermore, our model improves accuracy by about two orders of magnitude when compared to the traditional models used in the energy-efficient workflow scheduling literature.

97 MATHEMATICS AND COMPUTING↗

An all-oxide electrolysis cells for syngas production with tunable H 2 /CO yield via co-electrolysis of H 2 O and CO 2

High-rate production of syngas with tunable H 2 /CO and coke-free operation is achieved in a solid-oxide electrolysis cell (SOEC). Prior to operation, controlled pre-reduction of La 0.7 Sr 0.3 Fe 0.9 Ni 0.1 O 3-δ (LSFNi) cathode is used to trigger the in-situ exsolution of Ni-Fe alloy nanoparticles with an average size of ~45 nm uniformly distributed and socketed on LSFNi backbone, enabling efficient co-electrolysis of H 2 O and CO 2 to H 2 and CO. At 1.5 V, the current density reaches ~1.0 A cm-2 at 750 °C and ~2.4 A cm -2 at 850 °C with near 100% Faradaic Efficiency. We demonstrate the feasibility of tuning the output H 2 /CO ratio by nearly two orders of magnitude (from ~0.1 to ~7) by manipulating H 2 O/CO 2 ratio of feed gas, operating temperature, and current density. Finally, stable operation for >100 h is obtained without evidence of carbon deposition, although high current density operation leads to observable deterioration of anode/electrolyte interface due to the rapid oxygen evolution.

25 ENERGY STORAGE↗

On Parallel Push-Relabel based Algorithms for Bipartite Maximum Matching

We study multithreaded push-relabel based algorithms for computing maximum cardinality matching in bipartite graphs. Matching is a fundamental combinatorial (graph) problem with applications in a wide variety of problems in science and engineering. We are motivated by its use in the context of sparse linear solvers for computing maximum transversal of a matrix. We implement and test our algorithms on several multi-socket multicore systems and compare their performance to state-of-the-art augmenting path-based serial and parallel algorithms using a testset comprised of a wide range of real-world instances. Building on several heuristics for enhancing performance, we demonstrate good scaling for the parallel push-relabel algorithm. We show that it is comparable to the best augmenting path-based algorithms for bipartite matching. To the best of our knowledge, this is the first extensive study of multithreaded push-relabel based algorithms. In addition to a direct impact on the applications using matching, the proposed algorithmic techniques can be extended to preflow-push based algorithms for computing maximum flow in graphs.

Push-relabel, matching, bipartite↗

Friction behavior of a multi-interface system and improved performance by AlMgB 14 –TiB 2 –C and diamond-like-carbon coatings

We investigated friction behavior of a bearing system with two interfaces involved: a roller component experiencing rolling–sliding interaction against twin cylinders under point contacts while simultaneously undergoing pure sliding interaction against a socket under a conformal contact. Lubrication modeling predicted a strong correlation between the roller's rolling condition and the system's friction behavior. Experimental observations first validated the analytical predictions using steel and iron components. Diamond-like-carbon (DLC) coating and AlMgB 14 –TiB 2 coating with a carbon topcoat (BAMC) were then applied to the roller and twin cylinders, respectively. In conclusion, testing and analysis results suggest that the coatings effectively decreased the slip ratio for the roller–cylinder contact and the sliding friction at both bearing interfaces and, as a result, significantly reduced the system frictional torque.

42 ENGINEERING↗

Structural insights into inhibition of lipid I production in bacterial cell wall synthesis

Antibiotic-resistant bacterial infection is a serious threat to public health. Peptidoglycan biosynthesis is a well-established target for antibiotic development. MraY (phospho-MurNAc-pentapeptide translocase) catalyses the first and an essential membrane step of peptidoglycan biosynthesis. It is considered a very promising target for the development of new antibiotics, as many naturally occurring nucleoside inhibitors with antibacterial activity target this enzyme. However, antibiotics targeting MraY have not been developed for clinical use, mainly owing to a lack of structural insight into inhibition of this enzyme. Here we present the crystal structure of MraY from Aquifex aeolicus (MraY AA ) in complex with its naturally occurring inhibitor, muraymycin D2 (MD2). We show that after binding MD2, MraY AA undergoes remarkably large conformational rearrangements near the active site, which lead to the formation of a nucleoside-binding pocket and a peptide-binding site. MD2 binds the nucleoside-binding pocket like a two-pronged plug inserting into a socket. Further interactions it makes in the adjacent peptide-binding site anchor MD2 to and enhance its affinity for MraY AA . Surprisingly, MD2 does not interact with three acidic residues or the Mg 2+ cofactor required for catalysis, suggesting that MD2 binds to MraY AA in a manner that overlaps with, but is distinct from, its natural substrate, UDP-MurNAc-pentapeptide. We have determined the principles of MD2 binding to MraY AA , including how it avoids the need for pyrophosphate and sugar moieties, which are essential features for substrate binding. The conformational plasticity of MraY could be the reason that it is the target of many structurally distinct inhibitors. Furthermore, these findings can inform the design of new inhibitors targeting MraY as well as its paralogues, WecA and TarO.

59 BASIC BIOLOGICAL SCIENCES↗

DFTB+, a software package for efficient approximate density functional theory based atomistic simulations

DFTB+ is a versatile community developed open source software package offering fast and efficient methods for carrying out atomistic quantum mechanical simulations. By implementing various methods approximating density functional theory (DFT), such as the density functional based tight binding (DFTB) and the extended tight binding method, it enables simulations of large systems and long timescales with reasonable accuracy while being considerably faster for typical simulations than the respective ab initio methods. Based on the DFTB framework, it additionally offers approximated versions of various DFT extensions including hybrid functionals, time dependent formalism for treating excited systems, electron transport using non-equilibrium Green’s functions, and many more. DFTB+ can be used as a user-friendly standalone application in addition to being embedded into other software packages as a library or acting as a calculation-server accessed by socket communication. We give an overview of the recently developed capabilities of the DFTB+ code, demonstrating with a few use case examples, discuss the strengths and weaknesses of the various features, and also discuss on-going developments and possible future perspectives.

74 ATOMIC AND MOLECULAR PHYSICS↗

Quick-connect scanning tunneling microscope head with nested piezoelectric coarse walkers

To meet changing research demands, new scanning tunneling microscope (STM) features must constantly evolve. We describe the design, development, and performance of a modular plug-in STM, which is compact and stable. The STM head is equipped with a quick-connect socket that is matched to a universal connector plug, enabling it to be transferred between systems. This head can be introduced into a vacuum system via a load-lock and transferred to various sites equipped with the connector plug, permitting multi-site STM operation. Its design allows for reliable operation in a variety of experimental conditions, including a broad temperature range, ultra-high vacuum, high magnetic fields, and closed-cycle pulse-tube cooling. The STM’s compact size is achieved by a novel nested piezoelectric coarse walker design, which allows for large orthogonal travel in the X, Y, and Z directions, ideal for studying both bulk and thin film samples ranging in size from mm to μm. Its stability and noise tolerance are demonstrated by achieving atomic resolution under ambient conditions on a laboratory desktop with no vibrational or acoustic isolation. The operation of the nested coarse walkers is demonstrated by successful navigation to a μm-sized 2D sample.

Instruments & Instrumentation↗

Errant Beam Detection Using the AMD Versal ACAP and Vitis AI

The prevalence of ML and AI-powered solutions along with the slowing of Moore's Law has given rise to novel hardware platforms aimed at accelerating ML and AI. While programming these hardware platforms can be difficult, particularly for non-hardware experts, hardware vendors provide high-level tooling in an effort to address this difficulty. The Versal ACAP is an SoC designed by AMD that combines CPU cores, FPGA fabric, and a tiled, vector architecture called an AI engine all on the same socket. In an effort to more easily program this heterogeneous system, AMD has provided the Vitis AI development stack. In this work, we leverage Vitis AI to program a Versal ACAP to perform errant beam detection in the Spallation Neutron Source at Oak Ridge National Laboratory. Our initial work shows that after quantization and compilation of the model for the Versal ACAP, the classification accuracy, as measured by the AUC metric, is over 95% accurate while achieving this accuracy in 46 microseconds on average.

Cabrera, Anthony↗

Urban-Scale Control of School Bus Fleet Charging and Discharging Strategies Using Single and Multi-Stage Optimization

This paper presents a dual-strategy approach to optimizing charging and discharging schedules for school bus fleets, using the limited charging infrastructure effectively. We aim to ensure that each bus is fully charged for daily operations and aids in grid stability during peak demand. The first strategy utilizes linear programming to schedule overnight charging at available station sockets and strategic discharging during peak periods, efficiently coordinating limited resources. The second strategy employs metaheuristic techniques for continuous optimization, focusing on precise power requirements and offering greater flexibility than the linear model.

Selim, Alaa↗

Invited Paper: Benchmarking and Optimizing Data Movement on Emerging Heterogeneous Architectures

As supercomputers evolve, nodes are continually increasing in complexity. As a result, each generation of parallel systems brings new performance challenges. For instance, on recent systems inter-node communication has outperformed inter-socket, resulting in poor performance of many node-aware communication optimizations. Communication optimizations are critical for the performance and scalability of parallel applications, but are dependent on the parallel architecture, which varies significantly among recent generations of supercomputers. Furthermore, this paper investigates the performance of various paths of data movement on recent generations of systems, and analyzes the increased complexity of communication, particularly on recent heterogeneous systems. The paper also introduces MPI Advance, a communication library that enables optimizations to be created based on benchmark analysis of each emerging system.

benchmarking↗

Assessing Advanced Technology in CENATE

PNNL's Center for Advanced Technology Evaluation (CENATE) is a new U.S. Department of Energy center whose mission is to assess and facilitate access to emerging computing technology. CENATE is assessing a range of advanced technologies, from evolutionary to disruptive. Technologies of interest include the processor socket (homogeneous and accelerated systems), memories (dynamic, static, memory cubes), motherboards, networks (network interface cards and switches), and input/output and storage devices. CENATE is developing a multi-perspective evaluation process based on integrating advanced system instrumentation, performance measurements, and modeling and simulation. We show evaluations of two emerging network technologies: silicon photonics interconnects and the Data Vortex network. CENATE's evaluation also addresses the question of which machine is best for a given workload under certain constraints. We show a performance-power tradeoff analysis of a well-known machine learning application on two systems.

Tallent, Nathan R.↗

Optimizing End-to-End Big Data Transfers over Terabits Network Infrastructure

While future terabit networks hold the promise of significantly improving big-data motion among geographically distributed data centers, significant challenges must be overcome even on today's 100 gigabit networks to realize end-to-end performance. Multiple bottlenecks exist along the end-to-end path from source to sink, for instance, the data storage infrastructure at both the source and sink and its interplay with the wide-area network are increasingly the bottleneck to achieving high performance. In this study, we identify the issues that lead to congestion on the path of an end-to-end data transfer in the terabit network environment, and we present a new bulk data movement framework for terabit networks, called LADS. LADS exploits the underlying storage layout at each endpoint to maximize throughput without negatively impacting the performance of shared storage resources for other users. LADS also uses the Common Communication Interface (CCI) in lieu of the sockets interface to benefit from hardware-level zero-copy, and operating system bypass capabilities when available. It can further improve data transfer performance under congestion on the end systems using buffering at the source using flash storage. With our evaluations, we show that LADS can avoid congested storage elements within the shared storage resource, improving input/output bandwidth, and data transfer rates across the high speed networks. We also investigate the performance degradation problems of LADS due to I/O contention on the parallel file system (PFS), when multiple LADS tools share the PFS. We design and evaluate a meta-scheduler to coordinate multiple I/O streams while sharing the PFS, to minimize the I/O contention on the PFS. Finally, with our evaluations, we observe that LADS with meta-scheduling can further improve the performance by up to 14 percent relative to LADS without meta-scheduling.

97 MATHEMATICS AND COMPUTING↗

A Block-Based Triangle Counting Algorithm on Heterogeneous Environments

Triangle counting is a fundamental building block in graph algorithms. In this article, we propose a block-based triangle counting algorithm to reduce data movement during both sequential and parallel execution. Our block-based formulation makes the algorithm naturally suitable for heterogeneous architectures. The problem of partitioning the adjacency matrix of a graph is well-studied. Our task decomposition goes one step further: it partitions the set of triangles in the graph. By streaming these small tasks to compute resources, we can solve problems that do not fit on a device. We demonstrate the effectiveness of our approach by providing an implementation on a compute node with multiple sockets, cores and GPUs. The current state-of-the-art in triangle enumeration processes the Friendster graph in 2.1 seconds, not including data copy time between CPU and GPU. Using that metric, our approach is 20 percent faster. When copy times are included, our algorithm takes 3.2 seconds. This is 5.6 times faster than the fastest published CPU-only time.

97 MATHEMATICS AND COMPUTING↗