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NASA NTRSDate not supplied

Open Data Integration (ODIN): A Concurrent, Distributed Message-Based Architecture and Framework for Disaster Response

The Runtime for Airspace Concept Evaluation (RACE) is an open-source software architecture and framework to build configurable, highly concurrent and distributed message-based systems that offer scalable, low-latency performance on commodity hardware. RACE was used in commercial aviation applications to rapidly build systems that span several machines (including synchronized displays), interface existing hardware simulators and other live data feeds, and incorporate sophisticated visualization components such as NASA WorldWind. These RACE applications validated elements of the FAA’s System Wide Information Management (SWIM) Program, handling up to 1000 messages/sec from diverse sources (SFDPS, TFM-DATA, TAIS, ASDE-X, ITWS and local ADS) for 4,500 simultaneous flights tracked in the next-generation air transportation system’s digital backbone. We have since generalized RACE to support Open Data Integration (ODIN) applications outside aviation. Systems built with RACE/ODIN can be deployed in the field, on commodity hardware, and operate with limited or intermittent connectivity to the outside world. Our primary use case is a web-server with local/persistent data storage that runs within and only serves the stakeholder network (e.g. an incident command post). We are tailoring the RACE/ODIN system to support wildland fire management for the upcoming NASA Wildland Fire Safety Demonstration Series. RACE-ODIN is under consideration for application in the Scalable Traffic Management for Emergency Response Operations project, or STEReO, which aims to create a system that can be deployed during emergencies, to coordinate multiple elements of disaster response. Such data sources predominantly come from existing services on the internet (e.g. weather and satellite data, imported from so called "edge servers") but can also include dynamic (real-time) data from computer simulations and within the stakeholder network (such as aircraft and personnel tracking information). We will present the architecture and ODIN system demonstration incorporating local data from instrumented power-line towers, interpolated weather data and geospatial data from space-based platforms.

Joseph C Coughlan↗

NASA NTRSDate not supplied

Open Data Integration (ODIN): A Concurrent, Distributed Message-Based Architecture and Framework for Disaster Response

Guillaume P Brat↗

NASA NTRS1994

The architecture of the High Performance Storage System (HPSS)

The rapid growth in the size of datasets has caused a serious imbalance in I/O and storage system performance and functionality relative to application requirements and the capabilities of other system components. The High Performance Storage System (HPSS) is a scalable, next-generation storage system that will meet the functionality and performance requirements or large-scale scientific and commercial computing environments. Our goal is to improve the performance and capacity of storage by two orders of magnitude or more over what is available in the general or mass marketplace today. We are also providing corresponding improvements in architecture and functionality. This paper describes the architecture and functionality of HPSS.

Teaff, Danny↗

NASA NTRS2014

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

crop modeling↗

NASA NTRSDate not supplied

A Partitioned -Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a “plug and play” software package that allows users to conduct massively multiscale modeling of hierarchical and nonlinear materials. This work extends the scalability and improves the High Performance Computing friendliness of NASMAT by adopting a Partitioned Task-Parallel approach. Interoperability of NASMAT with external software is enhanced through preCICE, a open source library for multiphysics coupling in a partitioned manner. Enhancement through preCICE allows for easy integration of NASMAT to other macro solvers and dissociates the parallelization strategy adopted within NASMAT from the macro solver. The task-parallel framework based on Master-Worker approach is implemented as the parallelization scheme. The scheme accounts for hierarchy of multiple scales (task-dependence) and heterogeneous nature (dynamic load balancing) of computations. The applicability and scalability of the framework will be evaluated by analyzing large scale engineering problems through massively multiscale methods.

NASMAT↗

NASA NTRS1990

Supercomputing systems - A projection to 2000

Advances in computer architecture, computer science, computational methods, and constituent technologies are expected to lead to significant advances in the performance of scientific supercomputing system capabilities over the next decade. By the year 2000, single 1-in-sq dies are projected to incorporate four processors, each of which would be operating faster than 750 million instructions per second (MIPS) for a total on-chip processing performance in excess of 2000 MIPS. Scalable parallel processors can be expected to contain thousands of such multiple processor chips. In general, semiconductor performance advances appear to change about one order of magnitude every five years. Rotating magnetic memory and communications technology are not advancing as rapidly, with the result that the allocation of functions within the system configurations fo future supercomputer systems will require important changes. Availability of massively parallel heterogeneous processing capabilities should be a catalyst leading to new approaches for applications.

Lundstrom, S. F.↗

NASA NTRS1998

Performance of a Bounce-Averaged Global Model of Super-Thermal Electron Transport in the Earth's Magnetic Field

In this paper, we report the results of our recent research on the application of a multiprocessor Cray T916 supercomputer in modeling super-thermal electron transport in the earth's magnetic field. In general, this mathematical model requires numerical solution of a system of partial differential equations. The code we use for this model is moderately vectorized. By using Amdahl's Law for vector processors, it can be verified that the code is about 60% vectorized on a Cray computer. Speedup factors on the order of 2.5 were obtained compared to the unvectorized code. In the following sections, we discuss the methodology of improving the code. In addition to our goal of optimizing the code for solution on the Cray computer, we had the goal of scalability in mind. Scalability combines the concepts of portabilty with near-linear speedup. Specifically, a scalable program is one whose performance is portable across many different architectures with differing numbers of processors for many different problem sizes. Though we have access to a Cray at this time, the goal was to also have code which would run well on a variety of architectures.

McGuire, Tim↗

NASA NTRS2016

Instrumentation for Examining Microbial Response to Changes In Environmental Pressures

The Automated Adaptive Directed Evolution Chamber (AADEC) is a device that allows operators to generate a micro-scale analog of real world systems that can be used to model the local-scale effects of climate change on microbial ecosystems. The AADEC uses an artificial environment to expose cultures of micro-organisms to environmental pressures, such as UV-C radiation, chemical toxins, and temperature. The AADEC autonomously exposes micro-organisms to selection pressures. This improves upon standard manual laboratory techniques: the process can take place over a longer period of time, involve more stressors, implement real-time adjustments based on the state of the population, and minimize the risk of contamination. We currently use UV-C radiation as the main selection pressure, UV-C is well studied both for its cell and DNA damaging effects as a type of selection pressure and for its related effectiveness as a mutagen; having these functions united makes it a good choice for a proof of concept. The AADEC roadmap includes expansion to different selection pressures, including heavy metal toxicity, temperature, and other forms of radiation.The AADEC uses closed-loop control to feedback the current state of the culture to the AADEC controller that modifies selection pressure intensity during experimentation, in this case culture density and growth rate. Culture density and growth rate are determined by measuring the optical density of the culture using 600 nm light. An array of 600 nm LEDs illuminate the culture and photodiodes are used to measure the shadow on the opposite side of the chamber.Previous experiments showed that we can produce a million fold increase to UV-C radiation over seven iterations. The most recent implements a microfluidic system that can expose cultures to multiple different selection pressures, perform non-survival based selection, and autonomously perform hundreds of exposure cycles. A scalable pump system gives the ability to pump in various different growth media to individual cultures and introduce chemical toxins during experimentation; AADEC can perform freeze and thaw cycles. We improved our baseline characterization by building a custom UV-C exposure hood, a shutter operates on a preset timer allowing the user to set exposure intensity consistently for multiple iterations.

Environment↗

NASA NTRSDate not supplied

Coupled Reactor Multiphysics and Mass Scalability Assessment for Crewed Megawatt-Class NEP System Architectures

Nuclear Electric Propulsion (NEP) is an in-space propulsion technology capable of enabling opposition and conjunction class crewed Mars missions. NEP subsystems include the reactor for heat generation, a power conversion system (PCS), power management and distribution, electric propulsion system, and heat rejection system. Specific mass, or α (kg/kWe), is a key performance parameter (KPP) of the propulsion system which is directly scalable with the performance and mass predictions for each individual component. To inform technology maturation planning activities, full system and component level parametric modeling is ongoing to explore the design trade space and illustrate the effect of subsystem design choices on the system KPPs. In this study, scaling of high-assay, low-enriched uranium reactor designs is assessed through coupled reactor physics and thermal hydraulics analyses. Scaling analyses evaluate the impact of system performance parameters (power level, interface temperatures) on mass for direct gas cooled, pumped liquid metal, and passively-cooled heat pipe reactor concepts. Each concept requires specific geometries, fluids, and power conversion interface conditions (temperature, pressure, flow rate) to meet desired performance and mass. The reactor assembly includes the active core (fuel, moderator, cladding, working fluid), axial and radial neutron reflectors, control drums, structural support / pressure vessel, and external radiation shielding. Each of these components are parametrically sized based on performance parameters for a megawatt-class power cycle. Results of this scaling analysis increase NEP propulsion system modeling fidelity and ultimately aim to support concept down-selection along with related technology development planning. The reactor and shield α are a function of several PCS and heat rejection system design choices, and reactor scaling with these parameters must be considered to enable an informed decision on an optimal reactor geometry and working fluid combination.

Nuclear Electric Propulsion↗

NASA NTRSDate not supplied

Coupled Reactor Multiphysics and Mass Scalability Assessment for Crewed Megawatt-Class NEP System Architectures

Nuclear Electric Propulsion (NEP) is an in-space propulsion technology capable of enabling opposition and conjunction class crewed Mars missions. NEP subsystems include the reactor for heat generation, a power conversion system (PCS), power management and distribution (PMAD), electric propulsion subsystem (EPS), and a primary heat rejection system. Specific mass, or αe (kg / kWe), is a key performance parameter (KPP) of the propulsion system which is directly scalable with the performance and mass estimates for individual components. To inform technology maturation planning, full system and component level parametric modeling is ongoing to explore the design trade space and illustrate the effect of subsystem design choices on the system KPPs. In this study, scaling of high-assay, low-enriched uranium (HALEU) reactor designs is assessed through coupled reactor physics and thermal hydraulics analyses. Scaling analyses evaluate the impact of system performance parameters (power level, interface temperatures) on mass for direct gas cooled, pumped liquid metal, and passively cooled heat pipe reactor concepts. Each concept requires specific geometries and working fluids to reach the performance goals of PCS interface conditions (temperature, pressure, flow rate) and system mass. The reactor assembly includes the active core (fuel, moderator, cladding, working fluid), axial and radial neutron reflectors, control drums, structural support / pressure vessel, and external radiation shielding. Each of these components are parametrically sized based on performance parameters for a megawatt-class power cycle. Results of this scaling analysis increase NEP propulsion system modeling fidelity and ultimately aim to support technology down-selection along with related technology development planning. The reactor and shield αe are a function of several PCS design choices, and reactor scaling with these parameters must be considered to enable an informed decision on reactor geometry and working fluid combination.

Nuclear Electric Propulsion↗

NASA NTRS1995

The relation of scalability and execution time

Scalability has been used extensively as a de facto performance criterion for evaluating parallel algorithms and architectures. However, for many, scalability has theoretical interests only since it does not reveal execution time. In this paper, the relation between scalability and execution time is carefully studied. Results show that the isospeed scalability well characterizes the variation of execution time: smaller scalability leads to larger execution time, the same scalability leads to the same execution time, etc. Three algorithms from scientific computing are implemented on an Intel Paragon and an IBM SP2 parallel computer. Experimental and theoretical results show that scalability is an important, distinct metric for parallel and distributed systems, and may be as important as execution time in a scalable parallel and distributed environment.

Sun, Xian-He↗

NASA NTRS1988

A case for Redundant Arrays of Inexpensive Disks (RAID)

Increasing performance of CPUs and memories will be squandered if not matched by a similar performance increase in I/O. While the capacity of Single Large Expensive Disks (SLED) has grown rapidly, the performance improvement of SLED has been modest. Redundant Arrays of Inexpensive Disks (RAID), based on the magnetic disk technology developed for personal computers, offers an attractive alternative to SLED, promising improvements of an order of magnitude in performance, reliability, power consumption, and scalability. This paper introduces five levels of RAIDs, giving their relative cost/performance, and compares RAID to an IBM 3380 and a Fujitsu Super Eagle.

Patterson, David A.↗

NASA NTRS1999

The SGI/CRAY T3E: Experiences and Insights

The focus of the HPCC Earth and Space Sciences (ESS) Project is capability computing - pushing highly scalable computing testbeds to their performance limits. The drivers of this focus are the Grand Challenge problems in Earth and space science: those that could not be addressed in a capacity computing environment where large jobs must continually compete for resources. These Grand Challenge codes require a high degree of communication, large memory, and very large I/O (throughout the duration of the processing, not just in loading initial conditions and saving final results). This set of parameters led to the selection of an SGI/Cray T3E as the current ESS Computing Testbed. The T3E at the Goddard Space Flight Center is a unique computational resource within NASA. As such, it must be managed to effectively support the diverse research efforts across the NASA research community yet still enable the ESS Grand Challenge Investigator teams to achieve their performance milestones, for which the system was intended. To date, all Grand Challenge Investigator teams have achieved the 10 GFLOPS milestone, eight of nine have achieved the 50 GFLOPS milestone, and three have achieved the 100 GFLOPS milestone. In addition, many technical papers have been published highlighting results achieved on the NASA T3E, including some at this Workshop. The successes enabled by the NASA T3E computing environment are best illustrated by the 512 PE upgrade funded by the NASA Earth Science Enterprise earlier this year. Never before has an HPCC computing testbed been so well received by the general NASA science community that it was deemed critical to the success of a core NASA science effort. NASA looks forward to many more success stories before the conclusion of the NASA-SGI/Cray cooperative agreement in June 1999.

Bernard, Lisa Hamet↗

NASA NTRS1999

A Solar Dynamic Power Option for Space Solar Power

A study was performed to determine the potential performance and related technology requirements of Solar Dynamic power systems for a Space Solar Power satellite. Space Solar Power is a concept where solar energy is collected in orbit and beamed to Earth receiving stations to supplement terrestrial electric power service. Solar Dynamic systems offer the benefits of high solar-to-electric efficiency, long life with minimal performance degradation, and high power scalability. System analyses indicate that with moderate component development, SD systems can exhibit excellent mass and deployed area characteristics. Using the analyses as a guide, a technology roadmap was -enerated which identifies the component advances necessary to make SD power generation a competitive option for the SSP mission.

Mason, Lee S.↗

NASA NTRS1998

Modeling, Simulation and Analysis of Public Key Infrastructure

Security is an essential part of network communication. The advances in cryptography have provided solutions to many of the network security requirements. Public Key Infrastructure (PKI) is the foundation of the cryptography applications. The main objective of this research is to design a model to simulate a reliable, scalable, manageable, and high-performance public key infrastructure. We build a model to simulate the NASA public key infrastructure by using SimProcess and MatLab Software. The simulation is from top level all the way down to the computation needed for encryption, decryption, digital signature, and secure web server. The application of secure web server could be utilized in wireless communications. The results of the simulation are analyzed and confirmed by using queueing theory.

Liu, Yuan-Kwei↗

NASA NTRS1998

Software-implemented Fault Tolerance for Supercomputing in Space

The NASA Jet Propulsion Laboratory Remote Exploration and Experimentaion (REE) Project is a large multi-year technology demonstration project which will develop low-power, scalable, fault-tolerant, high- performance computing for use in space and will demonstrate that significant onboard processing capability enables a new class of science missions.

software fault tolerance supercomputing space remo↗

NASA NTRS2008

Range Imaging without Moving Parts

Range-imaging instruments of a type now under development are intended to generate the equivalent of three-dimensional images from measurements of the round-trip times of flight of laser pulses along known directions. These instruments could also provide information on characteristics of targets, including roughnesses and reflectivities of surfaces and optical densities of such semi-solid objects as trees and clouds. Unlike in prior range-imaging instruments based on times of flight along known directions, there would be no moving parts; aiming of the laser beams along the known directions would not be accomplished by mechanical scanning of mirrors, prisms, or other optical components. Instead, aiming would be accomplished by using solid-state devices to switch input and output beams along different fiber-optic paths. Because of the lack of moving parts, these instruments could be extraordinarily reliable, rugged, and long-lasting. An instrument of this type would include an optical transmitter that would send out a laser pulse along a chosen direction to a target. An optical receiver coaligned with the transmitter would measure the temporally varying intensity of laser light reflected from the target to determine the distance and surface characteristics of the target. The transmitter would be a combination of devices for generating precise directional laser illumination. It would include a pulsed laser, the output of which would be coupled into a fiber-optic cable with a fan-out and solid-state optical switches that would enable switching of the laser beam onto one or more optical fibers terminated at known locations in an array on a face at the focal plane of a telescope. The array would be imaged by the telescope onto the target space. The receiver optical system could share the aforementioned telescope with the transmitter or could include a separate telescope aimed in the same direction as that of the transmitting telescope. In either case, light reflected from the target would be focused by the receiver optical system onto an array of optical fibers matching the array in the transmitter. These optical fibers would couple the received light to one or more photodetector( s). Optionally, the receiver could include solid-state optical switches for choosing which optical fiber(s) would couple light to the photodetector(s). This instrument architecture is flexible and can be optimized for a wide variety of applications and levels of performance. For example, it is scalable to any number of pixels and pixel resolutions and is compatible with a variety of ranging and photodetection methodologies, including, for example, ranging by use of modulated (including pulsed and encoded) light signals. The use of fixed arrays of optical fibers to generate controlled illumination patterns would eliminate the mechanical complexity and much of the bulk of optomechanical scanning assemblies. Furthermore, digital control of the selection of the fiber-optic pathways for the transmitted beams could afford capabilities not seen in previous three-dimensional range-imaging systems. Instruments of this type could be specialized for use as, for example, proximity detectors, three-dimensional robotic vision systems, airborne terrain-mapping systems, and inspection systems.

Blair, J. Bryan↗

NASA NTRS2014

MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science Through Cloud-enabled Climate Analytics-as-a-service

Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we it see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRAAS) is an example of cloud-enabled CAaaS built on this principle. MERRAAS enables MapReduce analytics over NASAs Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRAAS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRAAS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to organizational change, fosters innovation and experimentation, facilitates technology transfer, and provides the agility required to meet our customers' increasing and changing needs. Cloud Computing is providing a new tier in the data services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. For climate science, Cloud Computing's capacity to engage communities in the construction of new capabilies is perhaps the most important link between Cloud Computing and Big Data.

Data Analytics↗