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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

ScalaBLAST 2.0: Rapid and robust BLAST calculations on multiprocessor systems

BLAST remains one of the most widely used tools in computational biology. The rate at which new sequence data is available continues to grow exponentially, driving the emergence of new fields of biological research. At the same time multicore systems and conventional clusters are more accessible. ScalaBLAST has been designed to run on conventional multiprocessor systems with an eye to extreme parallelism, enabling parallel BLAST calculations using over 16,000 processing cores with a portable, robust, fault-resilient design. ScalaBLAST 2.0 source code can be freely downloaded from http://omics.pnl.gov/software/ScalaBLAST.php.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2017

Scalable Static and Dynamic Community Detection Using Grappolo

Graph clustering, popularly known as community detection, is a fundamental kernel for several applications of relevance to the Defense Advanced Research Projects Agency’s (DARPA) Hierarchical Identify Verify Exploit (HIVE) Pro- gram. Clusters or communities represent natural divisions within a network that are densely connected within a cluster and sparsely connected to the rest of the network. The need to compute clustering on large scale data necessitates the development of efficient algorithms that can exploit modern architectures that are fundamentally parallel in nature. How- ever, due to their irregular and inherently sequential nature, many of the current algorithms for community detection are challenging to parallelize. In response to the HIVE Graph Challenge, we present several parallelization heuristics for fast community detection using the Louvain method as the serial template. We implement all the heuristics in a software library called Grappolo. Using the inputs from the HIVE Challenge, we demonstrate superior performance and high quality solutions based on four parallelization heuristics. We use Grappolo on static graphs as the first step towards community detection on streaming graphs.

Community Detection↗
DOE OSTI2019

Introducing Nonstructural Ligands to Zirconia-like Metal–Organic Framework Nodes To Tune the Activity of Node-Supported Nickel Catalysts for Ethylene Hydrogenation [Introducing Nonstructural Ligands to Zirconia-like MOF Nodes To Tune the Activity of Node-Supported Nickel Catalysts for Ethylene Hydrogenation]

Previous work has shown that introduction of hexafluoroacetylacetone (Facac) units as nonstructural ligands for the zirconia-like nodes of the eight-connected metal-organic framework (MOF), NU-1000, greatly alters the selectivity of node-supported oxy-nickel clusters for ethylene dimerization vs oligomerization. Here we i explore a related concept: tuning of support/catalyst interactions, and therefore, catalyst activity, via parallel installation of organic modifiers on the support itself. As modifiers we focused on para-substituted benzoates (R-BA – ; R = -NH 2 , -OCH 3 , -CH 3 , -H, -F, and -NO 2 ) where the substituents were chosen to present similar steric demand, but varying electron-donating or electron-withdrawing properties. R-benzoate-engendered shifts in the node-based aqua O-H stretching frequency for NU-1000, as measured by DRIFTS (diffuse-reflectance infrared Fourier-transform spectroscopy), together with systematic shifts in Ni 2p peak energies, as measured by X-ray photoelectron spectroscopy, show that the electronic properties of the support can be modulated. The vibrational and electronic peak shifts correlate with the putative electron-withdrawing vs electron-donating strength of the para-substituted benzoate modifiers. Subsequent installation of node-supported, oxy-Ni(II) clusters for ethylene hydrogenation yield a compelling correlation between log (catalyst turnover frequency) and the electron donating or withdrawing character of the substituent of the benzoate units. Single crystal X-ray diffraction measurements reveal that each organic modifier makes use of only one of two available carboxylate oxygens to accomplish grafting. The remaining oxygen atom is, in principle, well positioned to coordinate directly to an installed Ni(II) ion. We postulate that the unanticipated direct coordination of the catalyst by the node-modifier (rather than indirect modifier-based tuning of support(node)/catalyst electronic interactions) is the primary source of the observed systematic tuning of hydrogenation activity. Here we suggest, however, that regardless of mechanism for communication with active-sites of MOF-supported catalysts, intentional elaboration of nodes via grafted, nonstructural organic species could prove to be a valuable general strategy for fine-tuning supported-catalyst activity and/or selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

MixSim : An R Package for Simulating Data to Study Performance of Clustering Algorithms

The R package MixSim is a new tool that allows simulating mixtures of Gaussian distributions with different levels of overlap between mixture components. Pairwise overlap, defined as a sum of two misclassification probabilities, measures the degree of interaction between components and can be readily employed to control the clustering complexity of datasets simulated from mixtures. These datasets can then be used for systematic performance investigation of clustering and finite mixture modeling algorithms. Among other capabilities of MixSim, there are computing the exact overlap for Gaussian mixtures, simulating Gaussian and non-Gaussian data, simulating outliers and noise variables, calculating various measures of agreement between two partitionings, and constructing parallel distribution plots for the graphical display of finite mixture models. All features of the package are illustrated in great detail. The utility of the package is highlighted through a small comparison study of several popular clustering algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Secure Storage Architectures

The purpose of this report is to clarify the challenges associated with storage for secure enclaves. The major focus areas for the report are: - review of relevant parallel filesystem technologies to identify assets and gaps; - review of filesystem isolation/protection mechanisms, to include native filesystem capabilities and auxiliary/layered techniques; - definition of storage architectures that can be used for customizable compute enclaves (i.e., clarification of use-cases that must be supported for shared storage scenarios); - investigate vendor products related to secure storage. This study provides technical details on the storage and filesystem used for HPC with particular attention on elements that contribute to creating secure storage. We outline the pieces for a a shared storage architecture that balances protection and performance by leveraging the isolation capabilities available in filesystems and virtualization technologies to maintain the integrity of the data. Key Points: There are a few existing and in-progress protection features in Lustre related to secure storage, which are discussed in (Chapter 3.1). These include authentication capabilities like GSSAPI/Kerberos and the in-progress work for GSSAPI/Host-keys. The GPFS filesystem provides native support for encryption, which is not directly available in Lustre. Additionally, GPFS includes authentication/authorization mechanisms for inter-cluster sharing of filesystems (Chapter 3.2). The limitations of key importance for secure storage/filesystems are: (i) restricting sub-tree mounts for parallel filesystem (which is not directly supported in Lustre or GPFS), and (ii) segregation of hosts on the storage network and practical complications with dynamic additions to the storage network, e.g., LNET. A challenge for VM based use cases will be to provide efficient IO forwarding of the parallel filessytem from the host to the guest (VM). There are promising options like para-virtualized filesystems to help with this issue, which are a particular instances of the more general challenge of efficient host/guest IO that is the focus of interfaces like virtio. A collection of bridging technologies have been identified in Chapter 4, which can be helpful to overcome the limitations and challenges of supporting efficient storage for secure enclaves. The synthesis of native filesystem security mechanisms and bridging technologies led to an isolation-centric storage architecture that is proposed in Chapter 5, which leverages isolation mechanisms from different layers to facilitate secure storage for an enclave. Recommendations: The following highlights recommendations from the investigations done thus far. - The Lustre filesystem offers excellent performance but does not support some security related features, e.g., encryption, that are included in GPFS. If encryption is of paramount importance, then GPFS may be a more suitable choice. - There are several possible Lustre related enhancements that may provide functionality of use for secure-enclaves. However, since these features are not currently integrated, the use of Lustre as a secure storage system may require more direct involvement (support). (*The network that connects the storage subsystem and users, e.g., Lustre s LNET.) - The use of OpenStack with GPFS will be more streamlined than with Lustre, as there are available drivers for GPFS. - The Manilla project offers Filesystem as a Service for OpenStack and is worth further investigation. Manilla has some support for GPFS. - The proposed Lustre enhancement of Dynamic-LNET should be further investigated to provide more dynamic changes to the storage network which could be used to isolate hosts and their tenants. - The Linux namespaces offer a good solution for creating efficient restrictions to shared HPC filesystems. However, we still need to conduct a thorough round of storage/filesystem benchmarks. - Vendor products should be more closely reviewed, possibly to include evaluation of performance/protection of select products. (Note, we are investigation the option of evaluating equipment from Seagate/Xyratex.) Outline: The remainder of this report is structured as follows: - Section 1: Describes the growing importance of secure storage architectures and highlights some challenges for HPC. - Section 2: Provides background information on HPC storage architectures, relevant supporting technologies for secure storage and details on OpenStack components related to storage. Note, that background material on HPC storage architectures in this chapter can be skipped if the reader is already familiar with Lustre and GPFS. - Section 3: A review of protection mechanisms in two HPC filesystems; details about available isolation, authentication/authorization and performance capabilities are discussed. - Section 4: Describe technologies that can be used to bridge gaps in HPC storage and filesystems to facilitate...

Aderholdt, Ferrol↗
DOE OSTI2020

On the Efficient Evaluation of the Exchange Correlation Potential on Graphics Processing Unit Clusters

The predominance of Kohn–Sham density functional theory (KS-DFT) for the theoretical treatment of large experimentally relevant systems in molecular chemistry and materials science relies primarily on the existence of efficient software implementations which are capable of leveraging the latest advances in modern high-performance computing (HPC). With recent trends in HPC leading toward increasing reliance on heterogeneous accelerator-based architectures such as graphics processing units (GPU), existing code bases must embrace these architectural advances to maintain the high levels of performance that have come to be expected for these methods. In this work, we purpose a three-level parallelism scheme for the distributed numerical integration of the exchange-correlation (XC) potential in the Gaussian basis set discretization of the Kohn–Sham equations on large computing clusters consisting of multiple GPUs per compute node. In addition, we purpose and demonstrate the efficacy of the use of batched kernels, including batched level-3 BLAS operations, in achieving high levels of performance on the GPU. We demonstrate the performance and scalability of the implementation of the purposed method in the NWChemEx software package by comparing to the existing scalable CPU XC integration in NWChem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A network approach for multiscale catchment classification using traits

Abstract. The classification of river catchments into groups with similar biophysical characteristics is useful to understand and predict their hydrological behavior. The increasing availability of remote sensing and other large-scale geospatial datasets has enabled the use of advanced data-driven approaches to classify catchments using traits such as topography, geology, climate, land cover, land use, and human influence. Unsupervised clustering algorithms based on the Euclidean distance are commonly used for trait-based classification but are not suitable for highly dimensional data. In this study we present a new network-based method for multi-scale catchment classification, which can be applied to large datasets and used to determine the traits associated with different catchment groups. In this framework, two networks are analyzed in parallel: the first being where the nodes are traits and the second being where the nodes are catchments. In both cases, edges represent pairwise similarity, and a network cluster detection algorithm is used for the classification. The trait network is used to investigate redundancy in the trait data and to condense this information into a small number of interpretable categories. The catchments network is used to classify the catchments into clusters and to identify representative catchments for the different groups using the degree centrality metric. We apply this method to classify 9067 river catchments across the contiguous United States at both regional and continental scales using 274 non-categorical traits. At the continental scale, we identify 25 interpretable trait categories and 34 catchment clusters of sizes greater than 50. We find that catchments with similar trait categories are typically located in the same region, with different spatial patterns emerging among clusters dominated by natural and anthropogenic traits. We also find that the catchment clusters exhibit distinct hydrological behavior based on an analysis of streamflow indices. This network approach provides several advantages over traditional means of classification, including better separation of clusters, the use of alternate similarity metrics that are more suitable for highly dimensional data, and reducing redundancy in the trait information. The paired catchment–trait networks enable analysis of hydrological behavior using the dominant trait categories for each catchment cluster. The approach can be used at multiple spatial scales since the network topologies adjust automatically to reflect the trait patterns at the scale of investigation. Finally, the representative catchments identified as hub nodes in the network can be used to guide transferable observational and modeling strategies. The method is broadly applicable beyond hydrology for classification of other complex systems that utilize different types of trait datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Results from the CBC3 readout ASIC for CMS 2S-modules

The CBC3 is the latest version of the CMS Binary Chip for readout of the outer radial region of the upgraded CMS Tracker at the High Luminosity LHC. This 254-channel, 130 nm CMOS ASIC is designed to be bump-bonded to a substrate to which sensors will be wire-bonded. It will instrument double-layer 2S-modules, containing two overlaid silicon microstrip sensors, aligned with a parallel orientation. On-chip logic identifies Level-1 trigger primitives from high transverse-momentum tracks by selecting correlated clusters in the two sensors. The CBC3 was delivered in late 2016; wafer probing and performance tests have been carried out. Several prototype modules using the CBC3 have been produced and tested in the lab and in different beams. The results show that the CBC3 satisfies CMS requirements and only small corrections are needed for the final version of the chip for production.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Mechanistic Details and Reactivity Descriptors in Oxidation and Acid Catalysis of Methanol

Acid and redox reaction rates of CH₃OH-O₂ mixtures on polyoxometalate (POM) clusters, together with isotopic, spectroscopic, and theoretical assessments of catalyst properties and reaction pathways, were used to define rigorous descriptors of reactivity and to probe the compositional effects for oxidative dehydrogenation (ODH) and dehydration reactions. ³¹P-MAS NMR, transmission electron microscopy and titrations of protons with di-tert-butylpyridine during catalysis showed that POM clusters retained their Keggin structure upon dispersion on SiO₂ and after use in CH₃OH reactions. The effects of CH₃OH and O₂ pressures and of D-substitution on ODH rates show that C-H activation in molecularly adsorbed CH₃OH is the sole kinetically relevant step and leads to reduced centers as intermediates present at low coverages; their concentrations, measured from UV-vis spectra obtained during catalysis, are consistent with the effects of CH₃OH/O₂ ratios predicted from the elementary steps proposed. First-order ODH rate constants depend strongly on the addenda atoms (Mo vs W) but weakly on the central atom (P vs Si) in POM clusters, because C-H activation steps inject electrons into the lowest unoccupied molecular orbitals (LUMO) of the clusters, which are the d-orbitals at Mo⁶⁺ and W⁶⁺ centers. H-atom addition energies (HAE) at O-atoms in POM clusters represent the relevant theoretical probe of the LUMO energies and of ODH reactivity. The calculated energies of ODH transition states at each O-atom depend linearly on their HAE values with slopes near unity, as predicted for late transition states in which electron transfer and C-H cleavage are essentially complete. HAE values averaged over all accessible O-atoms in POM clusters provide the appropriate reactivity descriptor for oxides whose known structures allow accurate HAE calculations. CH₃OH dehydration proceeds via parallel pathways mediated by late carbenium-ion transition states; effects of composition on dehydration reactivity reflect changes in charge reorganizations and electrostatic forces that stabilize protons at Brønsted acid sites.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2011

The microstructure of dislocation clusters in industrial directionally solidified multicrystalline silicon

The microstructure of commonly occurring dislocation patterns in industrial directionally solidified multicrystalline silicon has been systematically studied by light microscopy, electron backscatter diffraction, and transmission electron microscopy. The work has been focused on dislocation clusters on wafers near the top of cast blocks. In near {l_brace}111{r_brace} grain surface, dislocation arrays parallel to {l_brace}110{r_brace} plane traces are lying in parallel rows of {l_brace}111{r_brace} planes inclined to the surface, in mainly <112>30 deg. orientation. The dislocation configuration suggests that the microstructure may result from a recovery process. The dislocations formed during crystal growth and cooling have undergone transformations at high temperature in order to achieve low energy configurations for minimization of dislocation and crystal energy.

36 MATERIALS SCIENCE↗
DOE OSTI2012

SNP Discovery with EST and NextGen Sequencing in Switchgrass ( Panicum virgatum L. )

Although yield trials for switchgrass (Panicum virgatum L.), a potentially high value biofuel feedstock crop, are currently underway throughout North America, the genetic tools for crop improvement in this species are still in the early stages of development. Identification of high-density molecular markers, such as single nucleotide polymorphisms (SNPs), that are amenable to high-throughput genotyping approaches, is the first step in a quantitative genetics study of this model biofuel crop species. We generated and sequenced expressed sequence tag (EST) libraries from thirteen diverse switchgrass cultivars representing both upland and lowland ecotypes, as well as tetraploid and octoploid genomes. We followed this with reduced genomic library preparation and massively parallel sequencing of the same samples using the Illumina Genome Analyzer technology platform. EST libraries were used to generate unigene clusters and establish a gene-space reference sequence, thus providing a framework for assembly of the short sequence reads. SNPs were identified utilizing these scaffolds. We used a custom software program for alignment and SNP detection and identified over 149,000 SNPs across the 13 short-read sequencing libraries (SRSLs). Approximately 25,000 additional SNPs were identified from the entire EST collection available for the species. This sequencing effort generated data that are suitable for marker development and for estimation of population genetic parameters, such as nucleotide diversity and linkage disequilibrium. Based on these data, we assessed the feasibility of genome wide association mapping and genomic selection applications in switchgrass. Overall, the SNP markers discovered in this study will help facilitate quantitative genetics experiments and greatly enhance breeding efforts that target improvement of key biofuel traits and development of new switchgrass cultivars.

09 BIOMASS FUELS↗
DOE OSTI2020

Scalable All-pairs Shortest Paths for Huge Graphs on Multi-GPU Clusters

We present an optimized Floyd-Warshall (Floyd-Warshall) algorithm that computes the All-pairs shortest path (APSP) for GPU accelerated clusters. The Floyd-Warshall algorithm due to its structural similarities to matrix-multiplication is well suited for highly parallel GPU architectures. To achieve high parallel efficiency, we address two key algorithmic challenges: reducing high communication overhead and addressing limited GPU memory. To reduce high communication costs, we redesign the parallel (a) to expose more parallelism, (b) aggressively overlap communication and computation with pipelined and asynchronous scheduling of operations, and (c) tailored MPI-collective. To cope with limited GPU memory, we employ an offload model, where the data resides on the host and is transferred to GPU on-demand. The proposed optimizations are supported with detailed performance models for tuning. Our optimized parallel Floyd-Warshall implementation is up to 5x faster than a strong baseline and achieves 8.1 PetaFLOPS/sec on 256~nodes of the Summit supercomputer at Oak Ridge National Laboratory. This performance represents 70% of the theoretical peak and 80% parallel efficiency. The offload algorithm can handle 2.5x larger graphs with a 20% increase in overall running time.

Sao, Piyush↗
DOE OSTI2020

Unidirectional growth of graphene nano-islands from carbon cluster seeds on Ge(1 1 0)

The anisotropic twofold symmetry of Ge(1 1 0) makes it a unique substrate for the growth of single-crystalline graphene. However, the underlying mechanism during the initial stage of growth of graphene on Ge(1 1 0) surface is not well understood. Here, we use in-situ cryogenic scanning tunneling microscopy (STM) and spectroscopy (STS), to study the initial growth properties of graphene synthesized on Ge(1 1 0) surface with ethylene precursor gases. The STM results reveal that the unidirectional growth of the graphene nanoribbons (GNRs) initiates from carbon cluster seeds on terraces during the early stage of the growth. The orientations of the GNRs show the same directions which are nearly parallel to the direction of the Ge(1 1 0) surface. This orientation is the same as that of the wafer-scale graphene grown on Ge(1 1 0). Subsequent growth, transformed the GNRs to graphene nanoislands (GNIs), which eventually coalesced to form single crystalline monolayer graphene. STS measurements demonstrated that the GNRs have small bandgaps induced by the confinement effect of graphene. Furthermore, this study provides an in-depth understanding of the growth mechanism of graphene on Ge(1 1 0) surface in various synthesis conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Structure sensitivity in the nonscalable regime explored via catalysed ethylene hydrogenation on supported platinum nanoclusters

The sensitivity, or insensitivity, of catalysed reactions to catalyst structure is a commonly employed fundamental concept. Here we report on the nature of nano-catalysed ethylene hydrogenation, investigated through experiments on size-selected Pt n (n=8-15) clusters soft-landed on magnesia and first-principles simulations, yielding benchmark information about the validity of structure sensitivity/insensitivity at the bottom of the catalyst size range. Both ethylene-hydrogenation-to-ethane and the parallel hydrogenation–dehydrogenation ethylidyne-producing route are considered, uncovering that at the <1 nm size-scale the reaction exhibits characteristics consistent with structure sensitivity, in contrast to structure insensitivity found for larger particles. The onset of catalysed hydrogenation occurs for Pt n (n≥10) clusters at T>150 K, with maximum room temperature reactivity observed for Pt 13 . Structure insensitivity, inherent for specific cluster sizes, is induced in the more active Pt 13 by a temperature increase up to 400 K leading to ethylidyne formation. As a result, control of sub-nanometre particle size may be used for tuning catalysed hydrogenation activity and selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Assessing the concept of structure sensitivity or insensitivity for sub-nanometer catalyst materials

In this report the nature of the nano-catalyzed hydrogenation of ethylene, yielding benchmark information pertaining to the concept of structure sensitivity/insensitivity and its applicability at the bottom of the catalyst particle size-range, is explored with experiments on size-selected Ptn (n = 7–40) clusters soft-landed on MgO, in conjunction with first-principles simulations. As in the case of larger particles both the direct ethylene hydrogenation channel and the parallel hydrogenation–dehydrogenation ethylidyne-producing route must be considered, with the fundamental uncovering that at the < 1 nm size-scale the reaction exhibits characteristics consistent with structure sensitivity, in contrast to the structure insensitivity found for larger particles. In this size-regime, the chemical properties can be modulated and tuned by a single atom, reflected by the onset of low temperature hydrogenation at T > 150 K catalyzed by Pt n (n ≥ 10) clusters, with maximum room temperature reactivity observed for Pt 13 using a pulsed molecular beam technique. Structure insensitive behavior, inherent for specific cluster sizes at ambient temperatures, can be induced in the more active sizes, e.g. Pt 13 , by a temperature increase, up to 400 K, which opens dehydrogenation channels leading to ethylidyne formation. This reaction channel was, however found to be attenuated on Pt 20 , as catalyst activity remained elevated after the 400 K step. Pt 30 displayed behavior which can be understood from extrapolating bulk properties to this size range; in particular the calculated d-band center. In the non-scalable sub-nanometer size regime, however, precise control of particle size may be used for atom-by-atom tuning and manipulation of catalyzed hydrogenation activity and selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Symmetry and Topology Code of the Cluster Self-Assembly of Intermetallic Compounds A{sub 2}{sup [16]}B{sub 4}{sup [12]} of the Friauf Families Mg{sub 2}Cu{sub 4} and Mg{sub 2}Zn{sub 4}

A geometrical and topological analysis of intermetallic compounds A{sub 2}{sup [16]}B{sub 4}{sup [12]} of the Friauf families Mg{sub 2}Cu{sub 4} (formed in 273 binary and 775 ternary systems) and Mg{sub 2}Zn{sub 4} (formed in 67 binary and 121 ternary systems) has been performed. Basic 3D nets are determined in the form of a graph, whose sites correspond to the centers of tetrahedral cluster precursors В{sub 4}: Cu-type net with a coordination number (CN) of 12 for Mg{sub 2}Cu{sub 4} and a BN-type net with a CN of 8 for Mg{sub 2}Zn{sub 4}. The symmetry and topology code is determined for the crystal structure self-assembly in the following form: primary chain S{sub 3}{sup 1} → microlayer S{sub 3}{sup 2} → microframework S{sub 3}{sup 3}. An identical mechanism of primary chain S{sub 3}{sup 1} self-assembly from B{sub 4} clusters with participation of large template atoms A{sup [16]} for both families and a mechanism of S{sub 3}{sup 2} microlayer self-assembly from parallel S{sub 3}{sup 1} chains in Mg{sub 2}Cu{sub 4} (basic 2D net 4{sup 4}) and shifted chains in Mg{sub 2}Zn{sub 4} (basic 2D net 3{sup 6}) have been determined for the first time. The constant chemical composition of intermetallic compounds A{sub 2}{sup [16]}B{sub 4}{sup [12]} is related to the functional difference between the B atoms forming 3D frameworks and template atoms А. The numbers of chemically different В{sub 4} clusters for the Mg{sub 2}Cu{sub 4} and Mg{sub 2}Zn{sub 4} families are found to be 25 and 19, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Transitioning NWChem to the Next Generation of Manycore Machines

The NorthWest Chemistry (NWChem) modeling software is a popular molecular chemistry simulation software that was designed from the start to work on massively parallel processing supercomputers[6, 28, 49]. It contains an umbrella of modules that today includes Self Consistent Field (SCF), second order Mller-Plesset perturbation theory (MP2), Coupled Cluster, multi-conguration selfconsistent eld (MCSCF), selected conguration interaction (CI), tensor contraction engine (TCE) many body methods, density functional theory (DFT), time-dependent density functional theory (TDDFT), real time time-dependent density functional theory, pseudopotential plane-wave density functional theory (PSPW), band structure (BAND), ab initio molecular dynamics, Car-Parrinello molecular dynamics, classical molecular dynamics (MD), QM/MM, AIMD/MM, GIAO NMR, COSMO, COSMO-SMD, and RISM solvation models, free energy simulations, reaction path optimization, parallel in time, among other capabilities[ 22]. Moreover new capabilities continue to be added with each new release.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2017

Divide and Conquer (DC) BLAST: fast and easy BLAST execution within HPC environments

Bioinformatics is currently faced with very large-scale data sets that lead to computational jobs, especially sequence similarity searches, that can take absurdly long times to run. For example, the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST and BLAST+) suite, which is by far the most widely used tool for rapid similarity searching among nucleic acid or amino acid sequences, is highly central processing unit (CPU) intensive. While the BLAST suite of programs perform searches very rapidly, they have the potential to be accelerated. In recent years, distributed computing environments have become more widely accessible and used due to the increasing availability of high-performance computing (HPC) systems. Therefore, simple solutions for data parallelization are needed to expedite BLAST and other sequence analysis tools. However, existing software for parallel sequence similarity searches often requires extensive computational experience and skill on the part of the user. In order to accelerate BLAST and other sequence analysis tools, Divide and Conquer BLAST (DCBLAST) was developed to perform NCBI BLAST searches within a cluster, grid, or HPC environment by using a query sequence distribution approach. Scaling from one (1) to 256 CPU cores resulted in significant improvements in processing speed. Thus, DCBLAST dramatically accelerates the execution of BLAST searches using a simple, accessible, robust, and parallel approach. DCBLAST works across multiple nodes automatically and it overcomes the speed limitation of single-node BLAST programs. DCBLAST can be used on any HPC system, can take advantage of hundreds of nodes, and has no output limitations. Thus, this freely available tool simplifies distributed computation pipelines to facilitate the rapid discovery of sequence similarities between very large data sets.

59 BASIC BIOLOGICAL SCIENCES↗