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At least 109 records · Page 6

The NEEDS Data Base Management and Archival Mass Memory System

A Data Base Management System and an Archival Mass Memory System are being developed that will have a 10 to the 12th bit on-line and a 10 to the 13th off-line storage capacity. The integrated system will accept packetized data from the data staging area at 50 Mbps, create a comprehensive directory, provide for file management, record the data, perform error detection and correction, accept user requests, retrieve the requested data files and provide the data to multiple users at a combined rate of 50 Mbps. Stored and replicated data files will have a bit error rate of less than 10 to the -9th even after ten years of storage. The integrated system will be demonstrated to prove the technology late in 1981.

Bailey, G. A.↗

The ASC Data Archive for the AXAF Ground Calibration

A data archive is near completion at the AXAF Science Center (ASC) to store and provide access to AXAF data. The archive is a distributed client/server system. It consists of a number of different servers which handle flat data files, relational data, replication across multiple sites, and the interface to the WWW. There is a 4GL client interface for each type of data server, C++ and Java APIs, and a number of standard clients to archive and retrieve data. The architecture is scalable and configurable in order to accommodate future data types and increasing data volumes. The first release of the system became available in August 1996 and has been successfully operated since then in support of the AXAF calibration at the George C. Marshall Space Flight Center, Huntsville, AL. This paper will present the overall archive architecture and the design of client and server components. It will also review the ground calibration data contents, the plan for flight data, and the access to the data by ASC internal users and processing pipelines.

Zografou, Panagoula↗

Part A: Cirrus ice crystal nucleation and growth. Part B: Automated analysis of aircraft ice particle data

Specific measurement of cirrus crystals by aircraft and temperature modified CN are used to specify measurements necessary to provide a basis for a conceptual model of cirrus particle formation. Key to this is the ability to measure the complete spectrum of particles at cirrus levels. The most difficult regions for such measurement is from a few to 100 microns, and uses a replicator. The details of the system to automate replicator data analysis are given, together with an example case study of the system provided from a cirrus cloud in FIRE 2, with particles detectable by replicator and FSSP, but not 2DC.

Arnott, William P.↗

Distributed Operations Planning

Maestro software provides a secure and distributed mission planning system for long-term missions in general, and the Mars Exploration Rover Mission (MER) specifically. Maestro, the successor to the Science Activity Planner, has a heavy emphasis on portability and distributed operations, and requires no data replication or expensive hardware, instead relying on a set of services functioning on JPL institutional servers. Maestro works on most current computers with network connections, including laptops. When browsing down-link data from a spacecraft, Maestro functions similarly to being on a Web browser. After authenticating the user, it connects to a database server to query an index of data products. It then contacts a Web server to download and display the actual data products. The software also includes collaboration support based upon a highly reliable messaging system. Modifications made to targets in one instance are quickly and securely transmitted to other instances of Maestro. The back end that has been developed for Maestro could benefit many future missions by reducing the cost of centralized operations system architecture.

Fox, Jason↗

Visual Systems Mapping to Define and Compare Woody Biomass LCAs for Sustainable Systems

The challenge addressed in this research centres on the need to choose between several biomass sources and energy production processes, while supporting rural economies and resilience of forest systems. A key barrier to effective decision-making for strategies using biomass is the lack of standardized and transparent life cycle assessment (LCA) baselines. These baselines are critical for assessing the impacts of biomass strategies but often vary due to regional factors and chosen simplifying assumptions of the LCAs. However, omitting key variables can mean the LCA omits key feedback and balancing loops relevant to fully assessing impacts of the change or test scenario. To address these complexities, this project employs a systems engineering approach: visual systems mapping. This technique is used to define the boundaries and dynamic behaviours of LCA baselines, enhancing transparency. By examining five literature sources and their documented baseline scenarios, the systems mapping case-studies demonstrates an approach to documenting and archiving these baselines. Recommendations are that visual systems mapping should be used to document key assumptions, such as baselines, of LCAs. Further, where possible open data repositories should hold key information about LCA baselines and reproducible workflows (e.g., using open-source tools) should be used to improve transparency and comparability in LCAs. Given the consensus within the broader scientific community on the importance of replicable data practices, this research reinforces the need for standardized frameworks and systems engineering tools in LCAs. This research demonstrates a pathway to more transparent, standardized, and comparable LCAs, that may bolster decisions for biomass systems.

Davis, Maggie [ORNL] (ORCID:0000000181319328)↗

An experiment in software reliability: Additional analyses using data from automated replications

A study undertaken to collect software error data of laboratory quality for use in the development of credible methods for predicting the reliability of software used in life-critical applications is summarized. The software error data reported were acquired through automated repetitive run testing of three independent implementations of a launch interceptor condition module of a radar tracking problem. The results are based on 100 test applications to accumulate a sufficient sample size for error rate estimation. The data collected is used to confirm the results of two Boeing studies reported in NASA-CR-165836 Software Reliability: Repetitive Run Experimentation and Modeling, and NASA-CR-172378 Software Reliability: Additional Investigations into Modeling With Replicated Experiments, respectively. That is, the results confirm the log-linear pattern of software error rates and reject the hypothesis of equal error rates per individual fault. This rejection casts doubt on the assumption that the program's failure rate is a constant multiple of the number of residual bugs; an assumption which underlies some of the current models of software reliability. data raises new questions concerning the phenomenon of interacting faults.

Dunham, Janet R.↗

Development and Characterization of Lightweight Durable Composite Conductor for Cables

Sustainable aviation in the form of electrified propulsion is likely to lead to an increase in the electrical assets contained within a single aircraft. As a result, it is desirable to design light weight conductor materials, thus reducing the payload of components like motor windings, low voltage signal cables, and transmission cables for data and power. One approach involves replacing pure Cu wiring with metalized CNT composites. This paper evaluates a framework for modeling overall conductivity and current sharing within such composites. Processing methods and parameters were refined. Select electroplated samples outperformed pure Cu in conductivity and had comparable ultimate tensile strengths. Tensile strengths are expected to improve with an additional densification step during processing. Acoustic emission data was used to predict the failure mechanism of the composite. Theories explaining improved intrinsic conductivity are discussed, with a focus on chemical and mechanical interactions at the Cu-CNT interface. These include Cu infiltration of CNT crevices, CNT oxidation, activity at defects in CNT walls, and the release of carbide-forming metals from CNT walls. Validating any or all these theories will require further work replicating data, collecting electron micrographs and conducting chemical analyses.

Metalized CNT↗

From Science to e-Science to Semantic e-Science: A Heliosphysics Case Study

The past few years have witnessed unparalleled efforts to make scientific data web accessible. The Semantic Web has proven invaluable in this effort; however, much of the literature is devoted to system design, ontology creation, and trials and tribulations of current technologies. In order to fully develop the nascent field of Semantic e-Science we must also evaluate systems in real-world settings. We describe a case study within the field of Heliophysics and provide a comparison of the evolutionary stages of data discovery, from manual to semantically enable. We describe the socio-technical implications of moving toward automated and intelligent data discovery. In doing so, we highlight how this process enhances what is currently being done manually in various scientific disciplines. Our case study illustrates that Semantic e-Science is more than just semantic search. The integration of search with web services, relational databases, and other cyberinfrastructure is a central tenet of our case study and one that we believe has applicability as a generalized research area within Semantic e-Science. This case study illustrates a specific example of the benefits, and limitations, of semantically replicating data discovery. We show examples of significant reductions in time and effort enable by Semantic e-Science; yet, we argue that a "complete" solution requires integrating semantic search with other research areas such as data provenance and web services.

Narock, Thomas↗

Structures of SARS-CoV-2 N7-methyltransferase with DOT1L and PRMT7 inhibitors provide a platform for new antivirals

The RNA N7-methyltransferase (MTase) activity of SARS-CoV-2’s nsp14 protein is essential for viral replication and is a target for the development of new antivirals. Nsp14 uses S-adenosyl methionine (SAM) as the methyl donor to cap the 5’ end of the SARS-CoV-2 mRNA and generates S-adenosyl homocysteine (SAH) as the reaction byproduct. Due to the central role of histone MTases in cancer, many SAM/SAH analogs with properties of cell permeability have recently been developed for the inhibition of these MTases. We have succeeded in identifying two such compounds (SGC0946 and SGC8158) that display significant antiviral activity and bind to the SARS-CoV-2 nsp14 N7-MTase core. Unexpectedly, crystal structures of SGC0946 and SGC8158 with the SARS-CoV-2 nsp14 N7-MTase core identify them as bi-substrate inhibitors of the viral MTase, co-occupying both the SAM and RNA binding sites; positing novel features that can be derivatized for increased potency and selectivity for SARS-CoV-2 nsp14. Taken together, the high-resolution structures and the accompanying biophysical and viral replication data provide a new avenue for developing analogs of SGC0946 and SGC8158 as antivirals.

60 APPLIED LIFE SCIENCES↗

Scalable Parallel Methods for Analyzing Metagenomics Data at Extreme Scale

The field of bioinformatics and computational biology is currently experiencing a data revolution. The exciting prospect of making fundamental biological discoveries is fueling the rapid development and deployment of numerous cost-effective, high-throughput next-generation sequencing technologies. The result is that the DNA and protein sequence repositories are being bombarded with new sequence information. Databases are continuing to report a Moore’s law-like growth trajectory in their database sizes, roughly doubling every 18 months. In what seems to be a paradigm-shift, individual projects are now capable of generating billions of raw sequence data that need to be analyzed in the presence of already annotated sequence information. While it is clear that data-driven methods, such as sequencing homology detection, are becoming the mainstay in the field of computational life sciences, the algorithmic advancements essential for implementing complex data analytics at scale have mostly lagged behind. Sequence homology detection is central to a number of bioinformatics applications including genome sequencing and protein family characterization. Given millions of sequences, the goal is to identify all pairs of sequences that are highly similar (or “homologous”) on the basis of alignment criteria. While there are optimal alignment algorithms to compute pairwise homology, their deployment for large-scale is currently not feasible; instead, heuristic methods are used at the expense of quality. In this dissertation, we present the design and evaluation of a parallel implementation for conducting optimal homology detection on distributed memory supercomputers. Our approach uses a combination of techniques from asynchronous load balancing (viz. work stealing, dynamic task counters), data replication, and exact-matching filters to achieve homology detection at scale. Results for a collection of 2.56M sequences show parallel efficiencies of ~75-100% on up to 8K cores, representing a time-to-solution of 33 seconds. We extend this work with a detailed analysis of single-node sequence alignment performance using the latest CPU vector instruction set extensions. Preliminary results reveal that current sequence alignment algorithms are unable to fully utilize widening vector registers.

59 BASIC BIOLOGICAL SCIENCES↗

Gradient Coding With Iterative Block Leverage Score Sampling

Gradient coding is a method for mitigating straggling servers in a centralized computing network that uses erasure-coding techniques to distributively carry out first-order optimization methods. Randomized numerical linear algebra uses randomization to develop improved algorithms for large-scale linear algebra computations. In this study, we propose a method for distributed optimization that combines gradient coding and randomized numerical linear algebra. The proposed method uses a randomized ℓ 2 -subspace embedding and a gradient coding technique to distribute blocks of data to the computational nodes of a centralized network, and at each iteration the central server only requires a small number of computations to obtain the steepest descent update. The novelty of our approach is that the data is replicated according to importance scores, called block leverage scores, in contrast to most gradient coding approaches that uniformly replicate the data blocks. Furthermore, we do not require a decoding step at each iteration, avoiding a bottleneck in previous gradient coding schemes. We show that our approach results in a valid ℓ 2 -subspace embedding, and that our resulting approximation converges to the optimal solution.

97 MATHEMATICS AND COMPUTING↗

dCache on Steroids - Delegated Storage Solutions

For over a decade, dCache.org has delivered a robust software used at more than 80 Universities and research institutes around the world, allowing these sites to provide reliable storage services for the WLCG experiments as well as many other scientific communities. The flexible architecture of dCache allows running it in a wide variety of configurations and platforms - from a SoC based all-in-one Raspberry-Pi up to hundreds of nodes in a multipetabyte installation. Due to lack of managed storage at the time, dCache implemented data placement, replication and data integrity directly. Today, many alternatives are available: S3, GlusterFS, CEPH and others. While such solutions position themselves as scalable storage systems, they cannot be used by many scientific communities out of the box. The absence of community-accepted authentication and authorization mechanisms, the use of product specific protocols and the lack of namespace are some of the reasons that prevent wide-scale adoption of these alternatives. Most of these limitations are already solved by dCache. By delegating low-level storage management functionality to the above-mentioned new systems and providing the missing layer through dCache, we provide a solution which combines the benefits of both worlds - industry standard storage building blocks with the access protocols and authentication required by scientific communities. In this paper, we focus on CEPH, a popular software for clustered storage that supports file, block and object interfaces. CEPH is often used in modern computing centers, for example as a backend to OpenStack services. We will show prototypes of dCache running with a CEPH backend and discuss the benefits and limitations of such an approach. As a result, we will also outline the roadmap for supporting ‘delegated storage’ within the dCache releases.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

A communication-avoiding 3D sparse triangular solver

We present a novel distributed memory algorithm to improve the strong scalability of the solution of a sparse triangular system. This operation appears in the solve phase of direct methods for solving general sparse linear systems, Ax = b. Our 3D sparse triangular solver employs several techniques, including a 3D MPI process grid, elimination tree parallelism, and data replication, all of which reduce the per-process communication when combined. We present analytical models to understand the communication cost of our algorithm and show that our 3D sparse triangular solver can reduce the per-process communication volume asymptotically by a factor of O(n1/4) and O(n1/6) for problems arising from the finite element discretizations of 2D "planar" and 3D "non-planar" PDEs, respectively. We implement our algorithm for use in SuperLU_DIST3D, using a hybrid MPI+OpenMP programming model. Our 3D triangular solve algorithm, when run on 12k cores of Cray XC30, outperforms the current state-of-the-art 2D algorithm by 7.2x for planar and 2.7x for the non-planar sparse matrices, respectively.

Sao, Piyush↗

New Results on Communication- and Memory-Aware Load Balancing Model and Algorithms

While load balancing in distributed-memory computing has been well-studied, we present an innovative approach to this problem: a unified, reduced-order model that combines three key components to describe “work” in a distributed system: computation, communication, and memory. Our model enables an optimizer to explore complex tradeoffs in task placement, such as augmented parallelism, at the expense of data replication increasing memory usage. We propose a fully distributed, heuristic-based load balancing optimization algorithm, and demonstrate that it quickly finds close-to-optimal solutions. We formalize the complex optimization problem as a mixed-integer linear program, and compare it to our strategy. Finally, we show that when applied to an electromagnetics code, our approach obtains up to 2.3x speedups for the imbalanced execution.

97 MATHEMATICS AND COMPUTING↗

Software reliability studies

The longterm goal of this research is to identify or create a model for use in analyzing the reliability of flight control software. The immediate tasks addressed are the creation of data useful to the study of software reliability and production of results pertinent to software reliability through the analysis of existing reliability models and data. The completed data creation portion of this research consists of a Generic Checkout System (GCS) design document created in cooperation with NASA and Research Triangle Institute (RTI) experimenters. This will lead to design and code reviews with the resulting product being one of the versions used in the Terminal Descent Experiment being conducted by the Systems Validations Methods Branch (SVMB) of NASA/Langley. An appended paper details an investigation of the Jelinski-Moranda and Geometric models for software reliability. The models were given data from a process that they have correctly simulated and asked to make predictions about the reliability of that process. It was found that either model will usually fail to make good predictions. These problems were attributed to randomness in the data and replication of data was recommended.

Wilson, Larry W.↗

The Use of Efficient Broadcast Protocols in Asynchronous Distributed Systems

Reliable broadcast protocols are important tools in distributed and fault-tolerant programming. They are useful for sharing information and for maintaining replicated data in a distributed system. However, a wide range of such protocols has been proposed. These protocols differ in their fault tolerance and delivery ordering characteristics. There is a tradeoff between the cost of a broadcast protocol and how much ordering it provides. It is, therefore, desirable to employ protocols that support only a low degree of ordering whenever possible. This dissertation presents techniques for deciding how strongly ordered a protocol is necessary to solve a given application problem. It is shown that there are two distinct classes of application problems: problems that can be solved with efficient, asynchronous protocols, and problems that require global ordering. The concept of a linearization function that maps partially ordered sets of events to totally ordered histories is introduced. How to construct an asynchronous implementation that solves a given problem if a linearization function for it can be found is shown. It is proved that in general the question of whether a problem has an asynchronous solution is undecidable. Hence there exists no general algorithm that would automatically construct a suitable linearization function for a given problem. Therefore, an important subclass of problems that have certain commutativity properties are considered. Techniques for constructing asynchronous implementations for this class are presented. These techniques are useful for constructing efficient asynchronous implementations for a broad range of practical problems.

Schmuck, Frank Bernhard↗

Log-Based Recovery in Asynchronous Distributed Systems

A log-based mechanism is described for restoring consistent states to replicated data objects after failures. Preserving a causal form of consistency based on the notion of virtual time is focused upon in this report. Causal consistency has been shown to apply to a variety of applications, including distributed simulation, task decomposition, and mail delivery systems. Several mechanisms have been proposed for implementing causally consistent recovery, most notably those of Strom and Yemini, and Johnson and Zwaenepoel. The mechanism proposed here differs from these in two major respects. First, a roll-forward style of recovery is implemented. A functioning process is never required to roll-back its state in order to achieve consistency with a recovering process. Second, the mechanism does not require any explicit information about the causal dependencies between updates. Instead, all necessary dependency information is inferred from the orders in which updates are logged by the object servers. This basic recovery technique appears to be applicable to forms of consistency other than causal consistency. In particular, it is shown how the recovery technique can be modified to support an atomic form of consistency (grouping consistency). By combining grouping consistency with casual consistency, it may even be possible to implement serializable consistency within this mechanism.

Kane, Kenneth Paul↗