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At least 1,567 records · Page 87

GPU Lossless Hyperspectral Data Compression System

Hyperspectral imaging systems onboard aircraft or spacecraft can acquire large amounts of data, putting a strain on limited downlink and storage resources. Onboard data compression can mitigate this problem but may require a system capable of a high throughput. In order to achieve a high throughput with a software compressor, a graphics processing unit (GPU) implementation of a compressor was developed targeting the current state-of-the-art GPUs from NVIDIA(R). The implementation is based on the fast lossless (FL) compression algorithm reported in "Fast Lossless Compression of Multispectral-Image Data" (NPO- 42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which operates on hyperspectral data and achieves excellent compression performance while having low complexity. The FL compressor uses an adaptive filtering method and achieves state-of-the-art performance in both compression effectiveness and low complexity. The new Consultative Committee for Space Data Systems (CCSDS) Standard for Lossless Multispectral & Hyperspectral image compression (CCSDS 123) is based on the FL compressor. The software makes use of the highly-parallel processing capability of GPUs to achieve a throughput at least six times higher than that of a software implementation running on a single-core CPU. This implementation provides a practical real-time solution for compression of data from airborne hyperspectral instruments.

Aranki, Nazeeh I.↗

Task 28: Web Accessible APIs in the Cloud Trade Study

This study explored three candidate architectures for serving NASA Earth Science Hierarchical Data Format Version 5 (HDF5) data via Hyrax running on Amazon Web Services (AWS). We studied the cost and performance for each architecture using several representative Use-Cases. The objectives of the project are: Conduct a trade study to identify one or more high performance integrated solutions for storing and retrieving NASA HDF5 and Network Common Data Format Version 4 (netCDF4) data in a cloud (web object store) environment. The target environment is Amazon Web Services (AWS) Simple Storage Service (S3).Conduct needed level of software development to properly evaluate solutions in the trade study and to obtain required benchmarking metrics for input into government decision of potential follow-on prototyping. Develop a cloud cost model for the preferred data storage solution (or solutions) that accounts for different granulation and aggregation schemes as well as cost and performance trades.

cost model↗

Injection data analysis using material balance time for CO 2 storage capacity estimation in deep closed saline aquifers

Estimating the ultimate storage capacity of deep saline aquifers is important to address the formation potential to store the envisioned large volumes of CO 2 . Injection data (i.e. injection rate, bottomhole pressure, and cumulative injected volume of CO 2 ) are routinely recorded during storage operations. These data contain valuable information on the subsurface (e.g. the reservoir pore volume and the formation storage capacity) that can be extracted. In this paper, we present a two-step graphical technique to infer the pore volume and the ultimate storage capacity of closed saline aquifers by analyzing the available injection data. First, the pore volume is inferred through adapting the concept of the material balance time. Material balance time is an approximate superposition time function developed to interpret production data from oil and gas wells operating at variable pressure/rate conditions during the boundary-dominated flow period. Using material balance techniques, the ultimate storage capacity is then estimated through linear extrapolation of the average pressure trend to the maximum allowable pressure the formation can withstand. The average pressure is not available in practice, but is can be obtained from the injection data. Two approaches are presented in this study to calculate the average pressure; namely the rigorous and the approximate approaches. Unlike the rigorous approach, the approximate approach does not require a prior knowledge of some reservoir properties (e.g. relative permeability, absolute permeability, formation porosity and thickness) to calculate the average pressure. To investigate its potential and reliability in analyzing CO 2 injection data, the proposed technique is applied to four synthetic cases representing different well operating conditions. Results indicate that the approximate approach consistently overestimates the actual (simulated) storage capacity as compared to the rigorous approach. The agreement - between the inferred and the simulated reservoir pore volume, and between the analytical and numerical estimates of storage capacity - validates the potential application of the technique to CO 2 storage in closed saline aquifers. The technique is further substantiated through application to a field data set utilized from a commercial-scale geological storage (CGS) project. Finally, field data interpretation shows that the proposed technique can be utilized to identify the degree of hydraulic continuity and reservoir compartmentalization within a target formation by interpreting the corresponding pressure and rate responses.

02 PETROLEUM↗

Satellite-based remote sensing data set of global surface water storage change from 1992 to 2018

The recent availability of freely and openly available satellite remote sensing products has enabled the implementation of global surface water monitoring at a level not previously possible. Here we present a global set of satellite-derived time series of surface water storage variations for lakes and reservoirs for a period that covers the satellite altimetry era. Our goals are to promote the use of satellite-derived products for the study of large inland water bodies and to set the stage for the expected availability of products from the Surface Water and Ocean Topography (SWOT) mission, which will vastly expand the spatial coverage of such products,expected from 2021 on. Our general strategy is to estimate global surface water storage changes (1V) in large lakes and reservoirs using a combination of paired water surface elevation (WSE) and water surface area (WSA)extent products. Specifically, we use data produced by multiple satellite altimetry missions (TOPEX/Poseidon,Jason-1, Jason-2, Jason-3, and Envisat) from 1992 on, with surface extent estimated from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000 on. We leverage relationships between elevation and surface area (i.e., hypsometry) to produce estimates of 1 Veven during periods when either of the variables was not available. This approach is successful provided that there are strong relationships between the two variables during an overlapping period. Our target is to produce time series of1Vas well as of WSE and WSA fora set of 347 lakes and reservoirs globally for the 1992–2018 period. The data sets presented and their respective algorithm theoretical basis documents are publicly available and distributed via the Physical Oceanography Dis-tributed Active Archive Center (PO DAAC; https://podaac.jpl.nasa.gov/, last access: 13 May 2020) of NASA’sJet Propulsion Laboratory. Specifically, the WSE data set is available at https://doi.org/10.5067/UCLRS-GREV2(Birkett et al., 2019), the WSA data set is available at https://doi.org/10.5067/UCLRS-AREV2 (Khandelwal and Kumar, 2019), and the 1V data set is available at https://doi.org/10.5067/UCLRS-STOV2 (Tortini et al., 2019).The records we describe represent the most complete global surface water time series available from the launch of TOPEX/Poseidon in 1992 (beginning of the satellite altimetry era) to the near present. The production of long-term, consistent, and calibrated records of surface water cycle variables such as in the data set presented here is of fundamental importance to baseline future SWOT products

Riccardo Tortini↗

Applications and safety data

A general overview of activities involving lithium batteries, which shows the various applications and data that were performed for numerous industry and government sponsors is presented. Brief discussions on electrochemical criteria selection, and typical storage and performance data obtained from three systems being developed are presented. Current safety work being done on high-rate, D, SO2 cells is also discussed. Three chemistries were developed and are discussed: lithium vanadium pentoxide, lithium sulfur dioxide, and lithium thionyl chloride. Storage, performance and safety data are graphically presented.

Berlangieri, N. J.↗

A NWB-based dataset and processing pipeline of human single-neuron activity during a declarative memory task

A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory.

Science & Technology - Other Topics↗

dCache: Inter-disciplinary storage system

The dCache project provides open-source software deployed internationally to satisfy ever more demanding storage requirements. Its multifaceted approach provides an integrated way of supporting different use-cases with the same storage, from high throughput data ingest, data sharing over wide area networks, efficient access from HPC clusters and long term data persistence on a tertiary storage. Though it was originally developed for the HEP experiments, today it is used by various scientific communities, including astrophysics, biomed, life science, which have their specific requirements. In this paper we describe some of the new requirements as well as demonstrate how dCache developers are addressing them.

Mkrtchyan, Tigran↗

Pervasive Restart In MOOSE-based Applications

Multiphysics applications are inherently complicated. Solving for multiple, interacting physical phenomena involves the solution of multiple equations, and each equation has its own data dependencies. Feeding the correct data to these equations at exactly the right time requires extensive effort in software design. In an ideal world, multiphysics applications always run to completion and produce correct answers. Unfortunately, in reality, there can be many reasons why a simulation might fail: power outage, system failure, exceeding a runtime allotment on a supercomputer, failure of the solver to converge, etc. A failure after many hours spent computing can be a significant setback for a project. Therefore, the ability to “continue” a solve from the point of failure, rather than starting again from scratch, is an essential component of any high-quality simulation tool. This process of “continuation” is commonly termed “restart” in the computational community. While the concept of restarting an application sounds ideal, the aforementioned complexities and data dependencies present in multiphysics applications make its implementation decidedly non-trivial. A running multiphysics calculation accumulates an enormous amount of “state”: current time, solution history, material properties, status of mechanical contact, etc. This “state” data comes in many different forms, including scalar, tensor, vector, and arbitrary, application-specific data types. To be able to restart an application, you must be able to both store and retrieve this data, effectively recreating the state of the application before the failure. When utilizing the Multiphysics Object Oriented Simulation Environment (MOOSE) framework developed at Idaho National Laboratory, this state data is stored both internally within the framework itself (such as solution vectors and the current time) and within the applications that use the framework. In order to implement restart in MOOSE-based applications, the total state of the system (both within the framework and without) must be stored and retrieved. To this end, the MOOSE team has implemented a “pervasive” restart capability which allows any object within MOOSE (or within a MOOSE-based application) to be declared as “state” data, and handles the storage and retrieval of said data.

97 MATHEMATICS AND COMPUTING↗

An interactive, discipline-independent data visualization system

The data visualization techniques used by National Space Science Data Center Graphics System are discussed. The system includes a self-describing data abstraction for the storage and manipulation of multidimensional data for discipline-independent scientific applications. The system's data format and graphics display are described. Consideration is given to techniques developed for the rapid display and manipulation of large, complex data sets and for manipulating algorithms with portable implementations which can operate on any data object or geometry. The processes of operating the system are given and examples are presented from applying the system to various types of data, including TOMS data, data from the International Satellite Cloud Climatology Project, and IRAS data.

Treinish, Lloyd A.↗

Network accessible multi-terabyte archive

The viewgraphs of a discussion on Network Accessible Multi-terabyte Archive presented at the National Space Science Data Center (NSSDC) Mass Storage Workshop is included. Topics covered in the presentation include the rotary storage system (RSS) including RSS data access, data management, administration, and hardware and software architecture.

Rybczynski, Fred↗

Array processor architecture

A high speed parallel array data processing architecture fashioned under a computational envelope approach includes a data base memory for secondary storage of programs and data, and a plurality of memory modules interconnected to a plurality of processing modules by a connection network of the Omega gender. Programs and data are fed from the data base memory to the plurality of memory modules and from hence the programs are fed through the connection network to the array of processors (one copy of each program for each processor). Execution of the programs occur with the processors operating normally quite independently of each other in a multiprocessing fashion. For data dependent operations and other suitable operations, all processors are instructed to finish one given task or program branch before all are instructed to proceed in parallel processing fashion on the next instruction. Even when functioning in the parallel processing mode however, the processors are not locked-step but execute their own copy of the program individually unless or until another overall processor array synchronization instruction is issued.

Barnes, George H.↗

Programmable data communications controller requirements

The design requirements for a Programmable Data Communications Controller (PDCC) that reduces the difficulties in attaching data terminal equipment to a computer are presented. The PDCC is an interface between the computer I/O channel and the bit serial communication lines. Each communication line is supported by a communication port that handles all line control functions and performs most terminal control functions. The port is fabricated on a printed circuit board that plugs into a card chassis, mating with a connector that is joined to all other card stations by a data bus. Ports are individually programmable; each includes a microprocessor, a programmable read-only memory for instruction storage, and a random access memory for data storage.

Source record↗

Progress in Monitoring Strategies for Risk Reduction in Geologic CO2 Storage

Abstract: This geophysical monitoring review is intended to lay the ground work for an approach to integrating monitoring strategies with risk assessment and risk reduction and to summarize work conducted by U.S. Department of Energy's National Risk Assessment Partnership (NRAP) participants that addresses key questions related to monitoring strategies. Commercial, demonstration and pilot geologic CO2 storage (GCS) projects have provided a wealth of practical experience in monitoring technologies. In this manuscript we review a few key projects, specific geophysical methods, well-based methods, geophysical workflows and some suggested best practices. These practices are often driven and governed by regulatory requirements (e.g. U.S. Environmental Protection Agency [US-EPA] Class VI underground injection regulation) and the need for effective reservoir management of pressures and volumes as well as the site-specific risks to containment, plume migration, and underground sources of drinking water. Reducing uncertainty in monitoring is likely to lead to reducing uncertainty in risk. One of our conclusions is the need for field experiment testing that is risk-driven. It is notable that GCS pilot projects have been designed for safe storage, and to date they have been successful. Technical challenges at all geologic CO2 storage sites include assuring injectivity and capacity predictions are reliable, the fate and subsurface topology of the CO2 plume is acceptable, regulatory permitting and compliance are accomplished in a timely manner, needed business assurances are supported by quantitative technical data, and the storage operation is acceptable to stakeholders. There is risk associated with all of these challenges necessitating a monitoring program utilizing both direct and indirect monitoring methods. Because of the direct association of risk and monitoring in GCS, geophysical monitoring is viewed as a key component in approaching risk assessment. To address monitoring in the context of risk assessment the U.S. Department of Energy's National Risk Assessment Partnership (NRAP) has undertaken a review of work related to monitoring storage sites. In this review we provide a framework for monitoring and then present some specific monitoring tools that may be useful for regulatory compliance, as well as technologies that are applicable to leakage detection.

Harbert, William↗

Parallel checksumming of data chunks of a shared data object using a log-structured file system

Checksum values are generated and used to verify the data integrity. A client executing in a parallel computing system stores a data chunk to a shared data object on a storage node in the parallel computing system. The client determines a checksum value for the data chunk; and provides the checksum value with the data chunk to the storage node that stores the shared object. The data chunk can be stored on the storage node with the corresponding checksum value as part of the shared object. The storage node may be part of a Parallel Log-Structured File System (PLFS), and the client may comprise, for example, a Log-Structured File System client on a compute node or burst buffer. The checksum value can be evaluated when the data chunk is read from the storage node to verify the integrity of the data that is read.

97 MATHEMATICS AND COMPUTING↗

NCDC mass storage systems and technologies

National Climatic Data Center (NCDC) data management issues are discussed, such as nature of holdings, history of the site, popularity of data sets, media/technology used for storage, volume distributed per month, mode of distribution, most frequently encountered problems, type of media requested/used, and evolution of media. Current holdings at NCDC are 107.8 terabytes of digital data and about 0.3 terabytes of manuscript data. The nexrad radar system is expected to generate approximately 88 terabytes per year by 1996.

Davis, Dick↗

Graphics processing unit management system for computed tomography

A method and apparatus for managing operation of graphics processing units in a computer system. A processing thread in the computer system controls processing of a set of sinogram data by a graphics processing unit to form a set of graphics data. An output thread in the computer system controls writing of the set of graphics data to a storage system. The graphics processing unit is available to perform processing of another set of sonogram data while the set of graphics data is written to the storage system such that the increased availability of a plurality of graphics processing units is present.

97 MATHEMATICS AND COMPUTING↗

The UCLA Cosmochemistry Database

Abstract The UCLA Cosmochemistry Database was initiated as part of a data-rescue and -storage project aimed at archiving a variety of cosmochemical data acquired at University of California, Los Angeles (UCLA). The data collection includes elemental compositions of extraterrestrial materials analyzed by UCLA cosmochemists over the last five decades. The analytical techniques include atomic absorption spectrometry (AAS) and neutron activation analysis (NAA) at UCLA. The data collection is stored on the Astromaterials Data System (Astromat). We provide both interactive tables and downloadable datasheets for users to access all data. The UCLA Cosmochemistry Database archives cosmochemical data that are essential tools for increasing our understanding of the nature and origin of extraterrestrial materials. Future studies can reference the data collection in the examination, analysis, and classification of newly acquired extraterrestrial samples.

Science & Technology - Other Topics↗