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All sourcesNASA NTRSDOE OSTI
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↗
NASA NTRS2007

Fault Injection Campaign for a Fault Tolerant Duplex Framework

Fault tolerance is an efficient approach adopted to avoid or reduce the damage of a system failure. In this work we present the results of a fault injection campaign we conducted on the Duplex Framework (DF). The DF is a software developed by the UCLA group [1, 2] that uses a fault tolerant approach and allows to run two replicas of the same process on two different nodes of a commercial off-the-shelf (COTS) computer cluster. A third process running on a different node, constantly monitors the results computed by the two replicas, and eventually restarts the two replica processes if an inconsistency in their computation is detected. This approach is very cost efficient and can be adopted to control processes on spacecrafts where the fault rate produced by cosmic rays is not very high.

fault injector↗
DOE OSTI2018

Reinterpreting the infrared spectrum of H + HCN: Methylene amidogen radical and its coproducts

The methylene amidogen radical (H 2 CN) plays a role in high-energy material combustion and extraterresterial atmospheres. Recent theoretical work has struggled to match experimental assignments for its CN and antisymmetric CH 2 stretching frequencies (ν 2 and ν 5 ), which were reported to occur at 1725 and 3103 cm –1 . Herein, we compute the vibrational energy levels of this molecule by extrapolating quadruples-level coupled- cluster theory to the complete basis limit and adding corrections for vibrational anharmonicity. This level of theory predicts that ν 2 and ν 5 should occur at 1646 and 2892 cm –1 , at odds with the experimental assignments. To investigate the possibility of defects in our theoretical treatment, we analyze the sensitivity of our approach to each of its contributing approximations. Our analysis suggests that the observed deviation from experiment is too large to be explained as an accumulation of errors, leading us to conclude that these transitions were misassigned. To help resolve this discrepancy, we investigate possible byproducts of the H + HCN reaction, which was the source of H 2 CN in the original experiment. In particular, we predict vibrational spectra for cis -HCNH, trans -HCNH, and H 2 CNH using high-level coupled-cluster computations. Based on these results, we reassign the transition at 1725 cm –1 to ν 3 of trans-HCNH, yielding excellent agreement. Supporting this identification, we assign a known contaminant peak at 886 cm –1 to ν 5 of the same conformer. Our computations suggest that the peak observed at 3103 cm –1 , however, does not belong to any of the aforementioned species. To facilitate further investigation, we use structure and bonding arguments to narrow the range of possible candidates. Furthermore, these arguments lead us to tentatively put forth formaldazine [(H 2 CN) 2 ] as a suggestion for further study, which we support with additional computations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
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 OSTI2016

Further Automate Planned Cluster Maintenance to Minimize System Downtime during Maintenance Windows

This report documents the integration and testing of the automated update process of compute clusters in LC to minimize impact to user productivity. Description: A set of scripts will be written and deployed to further standardize cluster maintenance activities and minimize downtime during planned maintenance windows. Completion Criteria: When the scripts have been deployed and used during planned maintenance windows and a timing comparison is completed between the existing process and the new more automated process, this milestone is complete. This milestone was completed on Aug 23, 2016 on the new CTS1 cluster called Jade when a request to upgrade the version of TOSS 3 was initiated while SWL jobs and normal user jobs were running. Jobs that were running when the update to the system began continued to run to completion. New jobs on the cluster started on the new release of TOSS 3. No system administrator action was required. Current update procedures in TOSS 2 begin by killing all users jobs. Then all diskfull nodes are updated, which can take a few hours. Only after the updates are applied are all nodes are rebooted, and then finally put back into service. A system administrator is required for all steps. In terms of human time spent during a cluster OS update, the TOSS 3 automated procedure on Jade took 0 FTE hours. Doing the same update without the Toss Update Tool would have required 4 FTE hours.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Scalable deep text comprehension for Cancer surveillance on high-performance computing

Background: Deep Learning (DL) has advanced the state-of-the-art capabilities in bioinformatics applications which has resulted in trends of increasingly sophisticated and computationally demanding models trained by larger and larger data sets. This vastly increased computational demand challenges the feasibility of conducting cutting-edge research. One solution is to distribute the vast computational workload across multiple computing cluster nodes with data parallelism algorithms. In this study, we used a High-Performance Computing environment and implemented the Downpour Stochastic Gradient Descent algorithm for data parallelism to train a Convolutional Neural Network (CNN) for the natural language processing task of information extraction from a massive dataset of cancer pathology reports. We evaluated the scalability improvements using data parallelism training and the Titan supercomputer at Oak Ridge Leadership Computing Facility. To evaluate scalability, we used different numbers of worker nodes and performed a set of experiments comparing the effects of different training batch sizes and optimizer functions.Results: We found that Adadelta would consistently converge at a lower validation loss, though requiring over twice as many training epochs as the fastest converging optimizer, RMSProp. The Adam optimizer consistently achieved a close 2nd place minimum validation loss significantly faster; using a batch size of 16 and 32 allowed the network to converge in only 4.5 training epochs.Conclusions: We demonstrated that the networked training process is scalable across multiple compute nodes communicating with message passing interface while achieving higher classification accuracy compared to a traditional machine learning algorithm.

Qiu, John X.↗
DOE OSTI2025

A Versatile Simulated Data Transport Layer for in Situ Workflows Performance Evaluation

In situ processing does not only allow scientific applications to face the explosion in data volume and velocity but also to address the time constraints of many simulation-analysis workflows by providing scientists with early insights about their applications at runtime. Multiple frameworks implement the concept of a data transport layer (DTL) to enable such in situ workflows. These tools are very versatile, directly or indirectly access the data generated on the same node, another node of the same compute cluster, or a completely distinct node, and allow data publishers and subscribers to run on the same computing resources or not. This versatility puts on researchers the onus of taking key decisions related to resource allocation and how to transport data to ensure the most efficient execution of their in situ workflows. However, domain scientists and workflow practitioners lack the appropriate tools to assess the respective performance of particular design and deployment options. In this paper we introduce a versatile simulated DTL designed to provide researchers with insights on the respective performance of different execution scenarios of in situ workflows. This open-source, standalone library builds on the SimGrid toolkit and can be linked to any SimGrid-based simulator. It facilitates the evaluation of the performance behavior, at scale, of different data transport configurations and the study of the effects of resource allocation strategies. We demonstrate the scalability, versatility, and accuracy of this simulated DTL by reproducing the execution of two synthetic benchmarks and of a real-world in situ workflow composed of an MPI application and a parallel data analysis. Results of simulations run on a single core show that the proposed library can simulate the interactions of tens of thousands of simulated processes deployed on two interconnected commodity clusters in a few seconds, and the execution by a thousand simulated processes of an in situ workflow in less than three minutes.

Suter, Fred [ORNL] (ORCID:0000000319021955)↗
DOE OSTI2020

Energetics and Structure of Ag–Water Clusters Formed in Mordenite

Zeolite-supported Ag 0 clusters have broad applications from catalysis to medicine, necessitating a mechanistic understanding of the formation of Ag 0 clusters in situ. Density functional theory (DFT) simulations have been performed on silver, water, and silver–water clusters in silica mordenite (Si-MOR), to identify the role of the confinement on the structure and energetics of Ag 0 cluster formation. The most favorable binding energy in the 12-membered ring (MR) pore of the Si-MOR is a 10–15-atom Ag 0 cluster. Computational pair distribution function (PDF) data indicates that the Ag 0 and Ag 0 –H 2 O clusters formed in vacuum versus in Si-MOR exhibit structural differences. Additionally, when the Ag 0 cluster is confined, the density decreases and the surface area increases, hypothesized to be due to the limiting geometry of the 12-MR main channel. An energetic drive toward formation of larger Ag 0 clusters was also identified, with hydrated silver atoms generating higher energy structures. In conclusion, this work identifies mechanistic and structural insight into the role of nanoconfinement on formation of Ag 0 clusters in mordenite.

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

PROTEUS-SN User Manual

PROTEUS-SN is a three-dimensional, highly scalable, high-fidelity neutron transport code developed at Argonne National Laboratory. The code is applicable to all spectrum reactor transport calculations, particularly those in which a high degree of fidelity is needed either to represent spatial detail or to resolve solution gradients. PROTEUS-SN solves the second order formulation of the transport equation using the continuous Galerkin finite element method in space, the discrete ordinates approximation in angle, and the multigroup approximation in energy. PROTEUS-SN’s parallel methodology permits the efficient decomposition of the problem by both space and angle, permitting large problems to run efficiently on hundreds of thousands of cores. PROTEUS-SN can also be used in serial or on smaller compute clusters (10’s to 100’s of cores) for smaller homogenized problems, although it is generally more computationally expensive than traditional homogenized methodology codes. PROTEUS-SN has been used to model partially homogenized systems, where regions of interest are represented explicitly and other regions are homogenized to reduce the problem size and required computational resources. PROTEUS-SN solves forward and adjoint eigenvalue problems and permits both neutron upscattering and downscattering. An adiabatic kinetics option has recently been included for performing simple time-dependent calculations in addition to standard steady state calculations. PROTEUS-SN handles void and reflective boundary conditions. Multigroup cross sections can be generated externally using the MC2-3 fast reactor multigroup cross section generation code or internally using the cross section application programming interface (API) which can treat the subgroup or resonance table libraries. PROTEUS-SN is written in Fortran 90 and also includes C preprocessor definitions. The code links against the PETSc, METIS, HDF5, and MPICH libraries. It optionally links against the MOAB library and is a part of the SHARP multi-physics suite for coupled multi-physics analysis of nuclear reactors. This user manual describes how to set up a neutron transport simulation with the PROTEUS-SN code. A companion methodology manual describes the theory and algorithms within PROTEUS-SN.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

Evolutionary Computational Methods for Identifying Emergent Behavior in Autonomous Systems

A technique based on Evolutionary Computational Methods (ECMs) was developed that allows for the automated optimization of complex computationally modeled systems, such as autonomous systems. The primary technology, which enables the ECM to find optimal solutions in complex search spaces, derives from evolutionary algorithms such as the genetic algorithm and differential evolution. These methods are based on biological processes, particularly genetics, and define an iterative process that evolves parameter sets into an optimum. Evolutionary computation is a method that operates on a population of existing computational-based engineering models (or simulators) and competes them using biologically inspired genetic operators on large parallel cluster computers. The result is the ability to automatically find design optimizations and trades, and thereby greatly amplify the role of the system engineer.

Terrile, Richard J.↗
NASA NTRS2005

Parallel Rendering of Large Time-Varying Volume Data

Interactive visualization of large time-varying 3D volume datasets has been and still is a great challenge to the modem computational world. It stretches the limits of the memory capacity, the disk space, the network bandwidth and the CPU speed of a conventional computer. In this SURF project, we propose to develop a parallel volume rendering program on SGI's Prism, a cluster computer equipped with state-of-the-art graphic hardware. The proposed program combines both parallel computing and hardware rendering in order to achieve an interactive rendering rate. We use 3D texture mapping and a hardware shader to implement 3D volume rendering on each workstation. We use SGI's VisServer to enable remote rendering using Prism's graphic hardware. And last, we will integrate this new program with ParVox, a parallel distributed visualization system developed at JPL. At the end of the project, we Will demonstrate remote interactive visualization using this new hardware volume renderer on JPL's Prism System using a time-varying dataset from selected JPL applications.

Garbutt, Alexander E.↗
DOE OSTI2021

SMC 2021 : Analyzing Resource Utilization and User Behavior on Titan Supercomputer

Resource utilization statistics of submitted jobs on a supercomputer can help us understand how users from various scientific domains use HPC platforms and better design a job scheduler. We explore to generate insight regarding workload distribution and usage pattern domains from job scheduler trace, GPU failure information, and project-specific information collected from Titan supercomputer. Furthermore, we want to know how the scheduler performance varies over time and how the users' scheduling behavior changes following a system failure. These observations have the potential to provide valuable insight, which is helpful to prepare for system failures. These practices will help us develop and apply novel machine learning algorithms in understanding system behavior, requirement, and better scheduling of HPC systems. There are two datasets, RUR and GPU. RUR: This dataset is the job scheduler traces collected from the Titan supercomputerfrom 01/01/2015 to 07/31/2019 (2015.csv - 2019.csv). These were collected usingResource Utilization Report (RUR), a Cray-developed resource-usage data collectionand reporting system. It contains the usage information of its critical resources (CPU,Memory, GPU, and I/O) of each running job on Titan during that period [2]. ProjectAreas: Every job is associated with a project ID. TheProjectAreas.csvdatasetprovides a mapping of the project ID to its domain science. GPU: There have been some hardware-related issues in the GPUs in Titan that caused some GPUs to fail, sometimes irrecoverably during some job runs. This dataset provides information regarding these failures during the execution of the submitted jobs. GPUs on Titan are uniquely identified by a serial number (SN), and they are installed in a location. A GPU can be installed in a location, then removed from that location following a failure, and then re-installed in a different location after fixing the problem. If the failure can't be recovered, the GPU might be removed entirely from Titan. There are two prominent types of failures that resulted in the removal of GPUs from Titan: Double Bit Error (DBE) and Out of the Bus (OTB). The dataset (gc_full.csv) has the following fields: 1. SN : Serial number of a GPU 2. location : The location where it is installed 3. insert : The time when it was inserted into that location 4. remove : The time when it was removed from that location 5. duration : Amount of time the GPU spent in this location 6. out : If the device was taken out entirely w/o a re-installment into a new location. 7. event : If the GPU was taken out entirely, the reason for its removal. To learn more about this dataset, please refer to the git repositoryhttps://github.com/olcf/TitanGPULifeand the related publication [1]. References [1] George Ostrouchov, Don Maxwell, Rizwan A Ashraf, Christian Engelmann, MallikarjunShankar, and James H Rogers. Gpu lifetimes on titan supercomputer: Survival analysisand reliability. InSC20: International Conference for High Performance Computing,Networking, Storage and Analysis, pages 1-14. IEEE, 2020. [2] Feiyi Wang, Sarp Oral, Satyabrata Sen, and Neena Imam. Learning from five-yearresource-utilization data of titan system. In2019 IEEE International Conference onCluster Computing (CLUSTER), pages 1-6. IEEE, 2019.

42 ENGINEERING↗
DOE OSTI2021

Sierra/SolidMechanics for Target Pulse Analysis

Sierra is a Multiphysics engineering simulation software suite developed and maintained by Sandia National Laboratories. Created for nuclear weapon needs, it is available to national laboratories with a foreign national restriction. The STS Target Systems analysis team is interested in using Sierra to perform explicit dynamics simulations of the tantalum clad tungsten target blocks as a response to sudden temperature changes induced by proton beam pulses. The capability already exists with Abaqus|Explicit, however, there are time and cost limitations due to licensing. The following document serves as a “quick-start” guide to the successful setup, simulation, and post-processing of a target model in Sierra on the OZ3 computing cluster at the Spallation Neutron Source.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Fast tree-based algorithms for DBSCAN for low-dimensional data on GPUs

DBSCAN is a well-known density-based clustering algorithm to discover arbitrary shape clusters. While conceptually simple in serial, the algorithm is challenging to efficiently parallelize on manycore GPU architectures. Common pitfalls, such as asynchronous range query calls, result in high thread execution divergence in many implementations. In this paper, we propose a new framework for GPU-accelerated DBSCAN, and describe two tree-based algorithms within that framework. Both algorithms fuse the search for neighbors with updating cluster information, but differ in their treatment of dense regions of the data. We show that the time taken to compute clusters is at most twice that of determination of the neighbors. We compare the proposed algorithms with existing CPU and GPU implementations, and demonstrate their competitiveness and performance using a fast traversal structure (bounding volume hierarchy) for low dimensional data. We also show that the memory usage can be reduced by processing object neighbors dynamically without storing them.

Prokopenko, Andrey↗
NASA NTRS2005

Performance Comparison of Mainframe, Workstations, Clusters, and Desktop Computers

A performance evaluation of a variety of computers frequently found in a scientific or engineering research environment was conducted using a synthetic and application program benchmarks. From a performance perspective, emerging commodity processors have superior performance relative to legacy mainframe computers. In many cases, the PC clusters exhibited comparable performance with traditional mainframe hardware when 8-12 processors were used. The main advantage of the PC clusters was related to their cost. Regardless of whether the clusters were built from new computers or whether they were created from retired computers their performance to cost ratio was superior to the legacy mainframe computers. Finally, the typical annual maintenance cost of legacy mainframe computers is several times the cost of new equipment such as multiprocessor PC workstations. The savings from eliminating the annual maintenance fee on legacy hardware can result in a yearly increase in total computational capability for an organization.

Farley, Douglas L.↗
NASA NTRSDate not supplied

Medical Resource Set Bulky Item Trade Space Analysis for Spaceflight Medical Risk

The NASA engineering community utilizes event-driven and fault-tree probabilistic techniques to classify risks in the space environment by taking advantage of the inherent knowledge of complex spaceflight system design and testing to quantify failure risk. In harmonizing the risk of human space flight, answering the question of ‘How do we balance health, performance and resource risks with other engineering risks on long duration space missions?’ remains a deeply challenging and largely qualitative practice. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is one aspect of the efforts by NASA’s Human Research Program (HRP) to quantitatively assess the impact of health and performance risk. One of MEDPRAT’s key features is its high degree of computational efficiency. Coupled with the HRP High Performance Compute cluster located at NASA’s Glenn Research Center, MEDPRAT runs millions of simulated missions in a matter of minutes. This degree of computational efficiency provides the novel opportunity to explore the relationship between medical set mass, volume, and medical resource size. Of particular interest for future human spaceflight missions are ‘bulky’ items, medical resources like devices, which occupy a large portion of the small, allocated mass and volume for the medical set leaving less room for other resources. This talk will present results showing the quantitative impact of forced inclusion of several bulky items across a variety of medical kit constraints, and the effect that a potential research investment into reducing the bulky item mass and volume may have on risk.

Lauren Mcintyre↗
DOE OSTI2017

Data Structures for Extreme Scale Computing

As computing problems of national importance grow, the government meets the increased demand by funding the development of ever larger systems. The overarching goal of the work supported in part by this grant is to increase efficiency of programming and performing computations on these large computing systems. In past work, we have demonstrated that some of these computations once thought to require expensive hardware designs and/or complex, special-purpose programming may be executed efficiently on low-cost commodity cluster computing systems using a general-purpose “latency-tolerant” programming framework. One important developed application of the ideas underlying this framework is graph database technology supporting social network pattern matching used by US intelligence agencies to more quickly identify potential terrorist threats. This database application has been spun out by the Pacific Northwest National Laboratory, a Department of Energy Laboratory, into a commercial start-up, Trovares Inc. We explore an alternative application of the same underlying ideas to a well-studied challenge arising in engineering: solving unstructured sparse linear equations. Solving these equations is key to predicting the behavior of large electronic circuits before they are fabricated. Predicting that behavior ahead of fabrication means that designs can optimized and errors corrected ahead of the expense of manufacture.

42 ENGINEERING↗
DOE OSTI2024

Ab initio computations of strongly deformed nuclei near Zr 80

Nuclei around N ≈ Z ≈ 40 are strongly deformed and exhibit coexistence of shapes. These phenomena have challenged nuclear models. Here, we perform ab initio coupled-cluster computations of low-lying collective states and electromagnetic quadrupole transitions of the even-even nuclei 72 Kr, 76,78 Sr, 78,80 Zr, and 84 Mo starting from chiral nucleon-nucleon and three-nucleon forces. Our calculations reproduce the coexistence of oblate and prolate shapes in these nuclei, yield rotational bands and strong electromagnetic transitions, but are not accurate for some observables and nuclei. Finally, these results highlight the advances and challenges of ab initio computations of heavy deformed nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗