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At least 1,009 records · Page 56

The performance evaluation of a new neural network based traffic management scheme for a satellite communication network

A neural-network-based traffic management scheme for a satellite communication network is described. The scheme consists of two levels of management. The front end of the scheme is a derivation of Kohonen's self-organization model to configure maps for the satellite communication network dynamically. The model consists of three stages. The first stage is the pattern recognition task, in which an exemplar map that best meets the current network requirements is selected. The second stage is the analysis of the discrepancy between the chosen exemplar map and the state of the network, and the adaptive modification of the chosen exemplar map to conform closely to the network requirement (input data pattern) by means of Kohonen's self-organization. On the basis of certain performance criteria, whether a new map is generated to replace the original chosen map is decided in the third stage. A state-dependent routing algorithm, which arranges the incoming call to some proper path, is used to make the network more efficient and to lower the call block rate. Simulation results demonstrate that the scheme, which combines self-organization and the state-dependent routing mechanism, provides better performance in terms of call block rate than schemes that only have either the self-organization mechanism or the routing mechanism.

Ansari, Nirwan↗

High resolution infrared astronomy satellite observations of a selected spiral galaxy

The H I, infrared, CO, H alpha and H beta band observations of M51, the prototypical grand-design spiral galaxy, are used to study the consequences of star formation for the distribution of H I and dust. Using the new Very Large Array (VLA) map of 21 cm emission, the Owens Valley Radio Observatory CO mosaic map, and an H alpha imate, new tests were performed with the idea of Tilanus and Allen that the H I is largely a photodissociation product in star-forming regions. It is confirmed that the H I spiral arms are generally coincident with the H II region arms, and offset downstream from the CO arms. The radial distributions of total gas, H alpha and H I surface density have a simple explanation in the dissociation picture. The distributions also demonstrate how the surface density of H I might be related to the star formation efficiency in molecule-rich galaxies. The large width of the H I regions along the arms compared to that of the giant H II regions can be understood in terms of a simple calculation of the expected size of an H I region associated with a typical giant H II region. The longer lifetime of the stars producing dissociating radiation vs. those producing ionizing radiation and the relatively long molecular formation timescale will also contribute to the greater width of the H I arms if stars are continuously forming on the arms. The lack of detailed coincidence of the H I and H II regions along the inner arms has a variety of possible explanations. Two simple tests were performed to probe the origins of the IRAS emission in M51. First, it was found that the infrared excess (IFE) of M51 is 24, suggesting that a substantial fraction of the infrared emission arises from dust heated by photons which do not originate in massive star-formaing regions. Second, radial cuts through the IRAS bands show that at 12, 25, and 60 microns, the arm-interarm contrast of the IRAS emission is substantially less than that of the H alpha emission, providing further evidence for the explanation and for the existence of a broadly distributed dust component. Deconvolved IRAS maps have improved resolution but do not change this finding.

Kulkarni, S. R.↗

Measuring Global Water Security Towards Sustainable Development Goals

Water plays an important role in underpinning equitable, stable and productive societies and ecosystems. Hence, United Nations recognized ensuring water security as one (Goal 6) of the seventeen sustainable development goals (SDGs). Many international river basins are likely to experience 'low water security' over the coming decades. Water security is rooted not only in the physical availability of freshwater resources relative to water demand, but also on social and economic factors (e.g. sound water planning and management approaches, institutional capacity to provide water services, sustainable economic policies). Until recently, advanced tools and methods are available for the assessment of water scarcity. However, quantitative and integrated-physical and socio-economic-approaches for spatial analysis of water security at global level are not available yet. In this study, we present a spatial multi-criteria analysis framework to provide a global assessment of water security. The selected indicators are based on Goal 6 of SDGs. The term 'security' is conceptualized as a function of 'availability', 'accessibility to services', 'safety and quality', and 'management'. The proposed global water security index (GWSI) is calculated by aggregating indicator values on a pixel-by-pixel basis, using the ordered weighted average method, which allows for the exploration of the sensitivity of final maps to different attitudes of hypothetical policy makers. Our assessment suggests that countries of Africa, South Asia and Middle East experience very low water security. Other areas of high water scarcity, such as some parts of United States, Australia and Southern Europe, show better GWSI values, due to good performance of management, safety and quality, and accessibility. The GWSI maps show the areas of the world in which integrated strategies are needed to achieve water related targets of the SDGs particularly in the African and Asian continents.

sustainable-development goals↗

Multi-Sensor Optimal Motion Planning for Radiological Contamination Surveys by Using Prediction-Difference Maps

Distributed and networked mobile sensor platforms using unmanned aerial and/or ground vehicles to survey areas of interest offer a safer and more efficient method for radiological contamination mapping; however, most applications rely on uniformly sweeping of the area in a raster-type motion without utilizing the information available in a dynamic sense. We have developed a fully autonomous optimal motion planning procedure for networks with two or more mobile sensors. The procedure utilizes well-established concepts of Gaussian processes in combination with control laws based on centroidal Voronoi tessellations to achieve optimal next-iteration sensor movements. A new method of informing optimal motion planning is proposed, whereby the absolute difference between the prior and current full-map prediction, referred to as the prediction-difference map, is used as the spatial density function within each Voronoi cell, providing immediate and iterative feedback for dynamic use of available information. The Gaussian process regression model used to estimate the contamination in unvisited locations also provides prediction uncertainties, and can be used as a quantitative metric to assess the confidence in the calculated contamination map; these estimates and prediction uncertainties are unavailable for standard uniform survey routines as they can only produce maps in the vicinity of observed locations. We present through simulation the achievable performance gains from using this new method by directly comparing to a uniform survey method. Results show that using the prediction-difference maps to inform motion planning procedures offers a faster rate of producing an accurate and convergent map relative to a uniform survey route.

47 OTHER INSTRUMENTATION↗

Mineral Mapping Using AVIRIS Data at Ray Mine, AZ

Imaging Spectroscopy enables the identification and mapping of surface mineralogy over large areas. This study focused on assessing the utility of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data for environmental impact analysis over the Environmental Protection Agency's (EPA) high priority Superfund site Ray Mine, AZ. Using the Spectral Angle Mapper (SAM) algorithm to analyze AVIRIS data makes it possible to map surface materials that are indicative of acid generating minerals. The improved performance of the AVIRIS sensor since 1996 provides data with sufficient signal to noise ratio to characterize up to 8 image endmembers. Specifically we employed SAM to map minerals associated with mine generated acid waste, namely jarositc, goethite, and hematite, in the presence of a complex mineralogical background.

McCubbin, Ian↗

Advances in Landslide Hazard Forecasting: Evaluation of Global and Regional Modeling Approach

A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that exhibit a high potential for landslide activity by combining a calculation of landslide susceptibility with satellite-derived rainfall estimates. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale landslide forecasting efforts, it requires several modifications before it can be fully realized as an operational tool. The evaluation finds that the landslide forecasting may be more feasible at a regional scale. This study draws upon a prior work's recommendations to develop a new approach for considering landslide susceptibility and forecasting at the regional scale. This case study uses a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America: Guatemala, Honduras, EI Salvador and Nicaragua. A regional susceptibility map is calculated from satellite and surface datasets using a statistical methodology. The susceptibility map is tested with a regional rainfall intensity-duration triggering relationship and results are compared to global algorithm framework for the Hurricane Mitch event. The statistical results suggest that this regional investigation provides one plausible way to approach some of the data and resolution issues identified in the global assessment, providing more realistic landslide forecasts for this case study. Evaluation of landslide hazards for this extreme event helps to identify several potential improvements of the algorithm framework, but also highlights several remaining challenges for the algorithm assessment, transferability and performance accuracy. Evaluation challenges include representation errors from comparing susceptibility maps of different spatial resolutions, biases in event-based landslide inventory data, and limited nonlandslide event data for more comprehensive evaluation. Additional factors that may improve algorithm performance accuracy include incorporating additional triggering factors such as tectonic activity, anthropogenic impacts and soil moisture into the algorithm calculation. Despite these limitations, the methodology presented in this regional evaluation is both straightforward to calculate and easy to interpret, making results transferable between regions and allowing findings to be placed within an inter-comparison framework. The regional algorithm scenario represents an important step in advancing regional and global-scale landslide hazard assessment and forecasting.

Kirschbaum, Dalia B.↗

High performance FORTRAN without templates: An alternative model for distribution and alignment

Language extensions of FORTRAN are being developed which permit the user to map data structures to the individual processors of distributed memory machines. These languages allow a programming style in which global data references are used. Current efforts are focussed on designing a common basis for such languages, the result of which is known as High Performance Fortran (HPF). One of the central debates in the HPF effort revolves around the concept of templates, introduced as an abstract index space to which data could be aligned. A model for the mapping of data which provides the functionality of High Performance Fortran distributions without the use of templates is presented.

Chapman, Barbara↗

Perpetual factors involved in performance of air traffic controllers using a microwave landing system

The task involved the control of two simulated aircraft targets per trial, in a 37.0 -km radius terminal area, by means of conventional radar vectoring and/or speed control. The goal was to insure that the two targets crossed the Missed Approach Point (MAP) at the runway threshold exactly 60 sec apart. The effects on controller performance of the MLS configuration under wind and no-wind conditions were examined. The data for mean separation time between targets at the MAP and the range about that mean were analyzed by appropriate analyses of variance. Significant effects were found for mean separation times as a result of the configuration of the MLS and for interaction between the configuration and wind conditions. The analysis of variance for range indicated significantly poorer performance under the wind condition. These findings are believed to be a result of certain perceptual factors involved in radar air traffic control (ATC) using the MLS with separation of targets in time.

Gershzohn, G.↗

Imaging the wakes of jets with energy-energy-energy correlators

As the partons in a high energy jet propagate through the droplet of quark-gluon plasma (QGP) produced in a heavy-ion collision they lose energy to, kick, and are kicked by the medium. The resulting modifications to the parton shower encode information about the microscopic nature of QGP. A direct consequence, however, is that the momentum and energy lost by the parton shower are gained by the medium and, since QGP is a strongly coupled liquid, this means that the jet excites a wake in the droplet of QGP. After freezeout, this wake becomes soft hadrons with net momentum in the jet direction meaning that what an experimentalist later reconstructs as a jet includes hadrons originating from both the modified parton shower and its wake. This has made it challenging to find experimental observables that provide an unambiguous view of the dynamical response of a droplet of QGP to a jet shooting through it. Recent years have seen significant substantial advances in the theoretical and experimental understanding of the substructure of jets, in particular, using correlation functions, $\langle$ ($\vec{n}$ 1 )•••$\mathcal{E}$($\vec{n}$ k ) $\rangle$, of the energy flux operator in proton-proton collisions and, recently, in heavy-ion collisions. So far, such studies have focused primarily on the two-point correlator, which allows for the identification of the angular scale of the underlying dynamics. Higher-point correlators hold the promise of mapping out the dynamics themselves. In this paper we perform the first study of the shape-dependent three-point energy-energy-energy correlator in heavy-ion collisions. Using the Hybrid Model to simulate the interactions of high energy jets with the QGP medium, we show that the three-point correlator presents us with a striking new opportunity. We find that hadrons originating from wakes are the dominant contribution to the three-point correlator in the kinematic regime in which the three points are well-separated in angle, forming a roughly equilateral triangle. This equilateral region of the correlator is far from the region populated by collinear vacuum emissions, making it a canvas on which jet wakes are laid out, where experimentalists can map their shapes. Our work provides a key step towards the systematic use of energy correlators to image and unravel the dynamical response of a droplet of QGP that has been probed by a passing jet, and motivates numerous experimental and theoretical studies.

Jets and Jet Substructure↗

GISMO

The 2 mm (1 50 GHz) atmospheric window enables unparalleled ground-based observations of the earliest active dusty galaxies in the universe. We have undertaken the development of a bolometer camera, GISMO (the Goddard-IRAM Superconducting 2-Millimeter Observer), which will obtain large and sensitive sky maps at this wavelength. The instrument will be used at the IRAM 30 m telescope, where we hope to have a trial observing run in Spring of 2007. The innovative element in this camera is its 8x1 6 fully sampled planar array of multiplexed superconducting transition edge sensor bolometers. This array is based on our recently demonstrated Backshort Under Grid architecture, designed to be scaled to kilopixel arrays with high sensitivity (of around 4 * 10 (exp -17)/ W* square root of Hz at T(sub c) approximates 450mK). A compact cryogenic optical system provides a wide field of view, (almost 2'x4') enabling GISMO to be very efficient at detecting sources serendipitously in large sky surveys, while retaining diffraction-limited imaging performance. GISMO will provide significantly greater imaging sensitivity and mapping speed at this wavelength than has previously been possible. The major scientific driver for the instrument is to detect dust emission from high-z Ultraluminous Infrared Galaxies (ULIRGs) and quasars. The instrument provides an important portion of the spectrum of high redshift galaxies at the Rayleigh-Jeans part of the dust emission spectrum, even at the highest redshifts. Models of galaxy evolution predict that GISMO will serendipitously detect one galaxy in every four hours of observing blank sky, and that one quarter of these galaxies will be at a redshift of z > 6.5.

Benford, Dominic↗

Influence Map Methodology for Evaluating Systemic Safety Issues

"Raising the bar" in safety performance is a critical challenge for many organizations, including Kennedy Space Center. Contributing-factor taxonomies organize information about the reasons accidents occur and therefore are essential elements of accident investigations and safety reporting systems. Organizations must balance efforts to identify causes of specific accidents with efforts to evaluate systemic safety issues in order to become more proactive about improving safety. This project successfully addressed the following two problems: (1) methods and metrics to support the design of effective taxonomies are limited and (2) influence relationships among contributing factors are not explicitly modeled within a taxonomy.

Source record↗

Machine learning simulation of finite element analysis in augmented reality

Media, method and system for approximating a finite element analysis texture map for an object. To accomplish this, the object is converted to a computer generated model and finite element analysis is performed for a plurality of different simulated inputs to generate a plurality of simulated mappings. Each simulated mapping is converted into a simulated texture map. A machine learning model is trained on the simulated inputs and simulated texture maps to generate a texture map which approximates a finite element analysis. The machine learning model receives a user input and generates the texture map therefrom. The texture map is then wrapped to the object and displayed.

Scherer, Derek Carl↗

Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado

Abstract. Deep learning (DL)-assisted inverse mapping has shown promise in hydrological model calibration by directly estimating parameters from observations. However, the increasing computational demand for running the state-of-the-art hydrological model limits sufficient ensemble runs for its calibration. In this work, we present a novel knowledge-informed deep learning method that can efficiently conduct the calibration using a few hundred realizations. The method involves two steps. First, we determine decisive model parameters from a complete parameter set based on the mutual information (MI) between model responses and each parameter computed by a limited number of realizations (∼50). Second, we perform more ensemble runs (e.g., several hundred) to generate the training sets for the inverse mapping, which selects informative model responses for estimating each parameter using MI-based parameter sensitivity. We applied this new DL-based method to calibrate a process-based integrated hydrological model, the Advanced Terrestrial Simulator (ATS), at Coal Creek Watershed, CO. The calibration is performed against observed stream discharge (Q) and remotely sensed evapotranspiration (ET) from the water year 2017 to 2019. Preliminary MI analysis on 50 realizations resulted in a down-selection of 7 out of 14 ATS model parameters. Then, we performed a complete MI analysis on 396 realizations and constructed the inverse mapping from informative responses to each of the selected parameters using a deep neural network. Compared with calibration using observations covering all time steps, the new inverse mapping improves parameter estimations, thus enhancing the performance of ATS forward model runs. The Nash–Sutcliffe efficiency (NSE) of streamflow predictions increases from 0.53 to 0.8 when calibrating against Q alone. Using ET observations, on the other hand, does not show much improvement on the performance of ATS modeling mainly due to both the uncertainty of the remotely sensed product and the insufficient coverage of the model ET ensemble in capturing the observation. By using observed Q only, we further performed a multiyear analysis and show that Q is best simulated (NSE > 0.8) by including in the calibration the dry-year flow dynamics that show more sensitivity to subsurface characteristics than the other wet years. Moreover, when continuing the forward runs till the end of 2021, the calibrated models show similar simulation performances during this evaluation period as the calibration period, demonstrating the ability of the estimated parameters in capturing climate sensitivity. Our success highlights the importance of leveraging data-driven knowledge in DL-assisted hydrological model calibration.

54 ENVIRONMENTAL SCIENCES↗

Object Based Numerical Zooming Between the NPSS Version 1 and a 1-Dimensional Meanline High Pressure Compressor Design Analysis Code

Within NASA's High Performance Computing and Communication (HPCC) program, NASA Glenn Research Center is developing an environment for the analysis/design of propulsion systems for aircraft and space vehicles called the Numerical Propulsion System Simulation (NPSS). The NPSS focuses on the integration of multiple disciplines such as aerodynamics, structures, and heat transfer, along with the concept of numerical zooming between 0- Dimensional to 1-, 2-, and 3-dimensional component engine codes. The vision for NPSS is to create a "numerical test cell" enabling full engine simulations overnight on cost-effective computing platforms. Current "state-of-the-art" engine simulations are 0-dimensional in that there is there is no axial, radial or circumferential resolution within a given component (e.g. a compressor or turbine has no internal station designations). In these 0-dimensional cycle simulations the individual component performance characteristics typically come from a table look-up (map) with adjustments for off-design effects such as variable geometry, Reynolds effects, and clearances. Zooming one or more of the engine components to a higher order, physics-based analysis means a higher order code is executed and the results from this analysis are used to adjust the 0-dimensional component performance characteristics within the system simulation. By drawing on the results from more predictive, physics based higher order analysis codes, "cycle" simulations are refined to closely model and predict the complex physical processes inherent to engines. As part of the overall development of the NPSS, NASA and industry began the process of defining and implementing an object class structure that enables Numerical Zooming between the NPSS Version I (0-dimension) and higher order 1-, 2- and 3-dimensional analysis codes. The NPSS Version I preserves the historical cycle engineering practices but also extends these classical practices into the area of numerical zooming for use within a companies' design system. What follows here is a description of successfully zooming I-dimensional (row-by-row) high pressure compressor results back to a NPSS engine 0-dimension simulation and a discussion of the results illustrated using an advanced data visualization tool. This type of high fidelity system-level analysis, made possible by the zooming capability of the NPSS, will greatly improve the fidelity of the engine system simulation and enable the engine system to be "pre-validated" prior to commitment to engine hardware.

Follen, G.↗

Real-time Terrain Relative Navigation Test Results from a Relevant Environment for Mars Landing

Terrain Relative Navigation (TRN) is an on-board GN&C function that generates a position estimate of a spacecraft relative to a map of a planetary surface. When coupled with a divert, the position estimate enables access to more challenging landing sites through pin-point landing or large hazard avoidance. The Lander Vision System (LVS) is a smart sensor system that performs terrain relative navigation by matching descent camera imagery to a map of the landing site and then fusing this with inertial measurements to obtain high rate map relative position, velocity and attitude estimates. A prototype of the LVS was recently tested in a helicopter field test over Mars analog terrain at altitudes representative of Mars Entry Descent and Landing conditions. TRN ran in real-time on the LVS during the flights without human intervention or tuning. The system was able to compute estimates accurate to 40m (3 sigma) in 10 seconds on a flight like processing system. This paper describes the Mars operational test space definition, how the field test was designed to cover that operational envelope, the resulting TRN performance across the envelope and an assessment of test space coverage.

Pin-point Landing↗

Lunar Node 1 and Beyond

Lunar Node 1 (LN-1) is an S-band Navigation beacon for lunar applications that was recently designed and built at MSFC. As part of NASA's Commercial Lunar Payload Services initiative, this beacon will be delivered to the moon's surface on Intuitive Machine's NOVA-C lunar lander in November 2021. During this mission, LN-1’s goal will be to demonstrate navigation technologies that can support local surface and orbital operations around the moon, enabling autonomy which would decrease dependency on heavily utilized Earth based assets like the Deep Space Network. To do this, LN-1’s design leverages Cubesat components as well as the Multi-spacecraft Autonomous Positioning System (MAPS) algorithms, which enable the autonomous spacecraft positioning through communication-integrated navigation measurements. In addition to demonstrating the MAPS payload, the radio will also be used in standard tone-based non-coherent ranging and Doppler tracking to provide an alternate approaches and comparisons for navigation performance. LN-1 will represent a single node in a potential greater MAPS network of assets. While LN-1 awaits launch to demonstrate this initial use of one-way navigation, designs are already under way for proposed subsequent missions like LN-2 to enable expanded capability. The next steps in these missions seek to include a receive capability to allow two-way ranging support with other operational spacecraft in the lunar vicinity, and to provide some component upgrades related to the radio, power, and thermal systems that will improve the longevity of the payload in the harsh lunar environment. The LN-1 design details, status, and potential forward work with mission like LN-2 will be outlined in this presentation.

Evan John Anzalone↗

Exploiting the IR: Solar and stellar spectroscopy in the IR

Recent instrumental advances have provided the capability to perform high resolution spectroscopy, in the thermal infrared region of the solar spectrum, with high sensitivity. The 8 to 12 micron region was extensively observed using Fourier transform (FTS) and laser heterodyne techniques. The continuous opacity of the solar atmosphere, due to H(-), increases with wavelength in the infrared region longward of 1.6 microns. Consequently thermal infrared observations probe the upper photosphere, and give an insight into the dynamics and structure of this region. The most notable spectral features in the 10 micron window include pure rotation lines of OH, and emission lines due to high-n states in MgI and AlI. The high-n lines due to MgI and AlI are important to solar and stellar physics because of their very large Zeeman sensitivity. The recent development of a cryogenic grating postdispenser for the FTS has allowed low-noise solar observations of these lines in 90 seconds. Limited mapping of the lines in a sunspot penumbra was performed, and gives information of the structure of the penumbral magnetic field. Although the MgI lines were detected in red giant spectra, instrumental sensitivity is not yet sufficient to see them in stars where significant magnetic fields are expected.

Deming, Drake↗

Cooperative Data Sharing: Simple Support for Clusters of SMP Nodes

Libraries like PVM and MPI send typed messages to allow for heterogeneous cluster computing. Lower-level libraries, such as GAM, provide more efficient access to communication by removing the need to copy messages between the interface and user space in some cases. still lower-level interfaces, such as UNET, get right down to the hardware level to provide maximum performance. However, these are all still interfaces for passing messages from one process to another, and have limited utility in a shared-memory environment, due primarily to the fact that message passing is just another term for copying. This drawback is made more pertinent by today's hybrid architectures (e.g. clusters of SMPs), where it is difficult to know beforehand whether two communicating processes will share memory. As a result, even portable language tools (like HPF compilers) must either map all interprocess communication, into message passing with the accompanying performance degradation in shared memory environments, or they must check each communication at run-time and implement the shared-memory case separately for efficiency. Cooperative Data Sharing (CDS) is a single user-level API which abstracts all communication between processes into the sharing and access coordination of memory regions, in a model which might be described as "distributed shared messages" or "large-grain distributed shared memory". As a result, the user programs to a simple latency-tolerant abstract communication specification which can be mapped efficiently to either a shared-memory or message-passing based run-time system, depending upon the available architecture. Unlike some distributed shared memory interfaces, the user still has complete control over the assignment of data to processors, the forwarding of data to its next likely destination, and the queuing of data until it is needed, so even the relatively high latency present in clusters can be accomodated. CDS does not require special use of an MMU, which can add overhead to some DSM systems, and does not require an SPMD programming model. unlike some message-passing interfaces, CDS allows the user to implement efficient demand-driven applications where processes must "fight" over data, and does not perform copying if processes share memory and do not attempt concurrent writes. CDS also supports heterogeneous computing, dynamic process creation, handlers, and a very simple thread-arbitration mechanism. Additional support for array subsections is currently being considered. The CDS1 API, which forms the kernel of CDS, is built primarily upon only 2 communication primitives, one process initiation primitive, and some data translation (and marshalling) routines, memory allocation routines, and priority control routines. The entire current collection of 28 routines provides enough functionality to implement most (or all) of MPI 1 and 2, which has a much larger interface consisting of hundreds of routines. still, the API is small enough to consider integrating into standard os interfaces for handling inter-process communication in a network-independent way. This approach would also help to solve many of the problems plaguing other higher-level standards such as MPI and PVM which must, in some cases, "play OS" to adequately address progress and process control issues. The CDS2 API, a higher level of interface roughly equivalent in functionality to MPI and to be built entirely upon CDS1, is still being designed. It is intended to add support for the equivalent of communicators, reduction and other collective operations, process topologies, additional support for process creation, and some automatic memory management. CDS2 will not exactly match MPI, because the copy-free semantics of communication from CDS1 will be supported. CDS2 application programs will be free to carefully also use CDS1. CDS1 has been implemented on networks of workstations running unmodified Unix-based operating systems, using UDP/IP and vendor-supplied high- performance locks. Although its inter-node performance is currently unimpressive due to rudimentary implementation technique, it even now outperforms highly-optimized MPI implementation on intra-node communication due to its support for non-copy communication. The similarity of the CDS1 architecture to that of other projects such as UNET and TRAP suggests that the inter-node performance can be increased significantly to surpass MPI or PVM, and it may be possible to migrate some of its functionality to communication controllers.

DiNucci, David C.↗