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At least 55 records · Page 3

MAX: A space station computer option

Information on Max, a space station computer option, is given in viewgraph form. The computer option is characterized by embedded, real-time applications; synchronous, cyclic operation and asynchronous, event driven operation; computationally intensive and data intensive processing; a wide range of throughput and memory requirements; a range of fault tolerant requirements from none to full; and maintainability, including capability for on-line substitution in critical systems.

Smith, D. B.

Observations of Particle Number Size Distributions and New Particle Formation in Six Indian Locations

Atmospheric new particle formation (NPF) is a crucial process driving aerosol number concentrations in the atmosphere; it can significantly impact the evolution of atmospheric aerosol and cloud processes. This study analyses at least 1 year of asynchronous particle number size distributions from six different locations in India. We also analyze the frequency of NPF and its contribution to cloud condensation nuclei (CCN) concentrations. We found that the NPF frequency has a considerable seasonal variability. At the measurement sites analyzed in this study, NPF frequently occurs in March–May (pre-monsoon, about 21 % of the days) and is the least common in October–November (post-monsoon, about 7 % of the days). Considering the NPF events in all locations, the particle formation rate (J_(SDS)) varied by more than 2 orders of magnitude (0.001–0.6 /cu.cm s) and the growth rate between the smallest detectable size and 25 nm (GR_(SDS-25 nm)) by about 3 orders of magnitude (0.2–17.2 nm/h). We found that JSDS was higher by nearly 1 order of magnitude during NPF events in urban areas than mountain sites. GRSDS did not show a systematic difference. Our results showed that NPF events could significantly modulate the shape of particle number size distributions and CCN concentrations in India. The contribution of a given NPF event to CCN concentrations was the highest in urban locations (4.3 × 10^(3) /cu.cm per event and 1.2 × 10^(3)/cu.cm per event for 50 and 100 nm, respectively) as compared to mountain background sites (2.7 × 10^(3)/cu.cm per event and 1.0 × 10^(3)/cu.cm per event, respectively). We emphasize that the physical and chemical pathways responsible for NPF and factors that control its contribution to CCN production require in situ field observations using recent advances in aerosol and its precursor gaseous measurement techniques.

particle number size distributions

Asynchronous multilevel adaptive methods for solving partial differential equations on multiprocessors - Performance results

The fast adaptive composite grid method (FAC) is an algorithm that uses various levels of uniform grids (global and local) to provide adaptive resolution and fast solution of PDEs. Like all such methods, it offers parallelism by using possibly many disconnected patches per level, but is hindered by the need to handle these levels sequentially. The finest levels must therefore wait for processing to be essentially completed on all the coarser ones. A recently developed asynchronous version of FAC, called AFAC, completely eliminates this bottleneck to parallelism. This paper describes timing results for AFAC, coupled with a simple load balancing scheme, applied to the solution of elliptic PDEs on an Intel iPSC hypercube. These tests include performance of certain processes necessary in adaptive methods, including moving grids and changing refinement. A companion paper reports on numerical and analytical results for estimating convergence factors of AFAC applied to very large scale examples.

Mccormick, S.

BULKI-Store v0.3.2

BULKI-Store is a distributed object storage system optimized for high-performance computing environments. Built with a Rust core and Python bindings, it efficiently manages scientific and machine learning datasets across HPC clusters. The system employs a client-server architecture with MPI integration, enabling seamless scaling on supercomputers like Perlmutter. BULKI-Store's object-oriented approach provides intuitive data organization with rich metadata support, contrasting with traditional file-based solutions. Key optimizations include selective checkpoint loading, unified checkpoint files, and object chunking for large data transfers. For machine learning workloads, BULKI-Store offers advantages through fine-grained access patterns, dynamic data sharing between training instances, and reduced memory pressure. Memory management features include strategic Python GC calls, minimized data copies, and batch processing capabilities. The system leverages Rayon's thread pool for asynchronous data prefetching and supports multiple CPU architectures (ARM64, x86, AMD, RISC-V). By combining performance optimizations with developer-friendly APIs, BULKI-Store addresses the complex data management challenges of modern HPC applications while maintaining compatibility across heterogeneous computing environments.

Zhang, Wei [Lawrence Berkeley National Laboratory

Redundant asynchronous microprocessor system for fault tolerant flight control and navigation

Unlike their synchronized counterparts, redundant channels in an asynchronous flight system can, under no-fault conditions, exhibit cross-channel data disparities. Sources of these errors are examined in terms of the general, individual functions of the flight control and navigation application in the asynchronous digital environment. The effects of asynchronism on trajectory programmers, dynamic control algorithms and data reconstruction processes are examined in terms of data skews, data latencies, and clock rate uncertainties. An example is presented in which time corrections are applied to reduce the data disparities. Practical limitations of the approach of the example are discussed.

Dunn, W. R.

Automated X-ray and Optical Analysis of the Virtual Observatory and Grid Computing

We are developing a system to combine the Web Enabled Source Identification with X-Matching (WESIX) web service, which emphasizes source detection on optical images,with the XAssist program that automates the analysis of X-ray data. XAssist is continuously processing archival X-ray data in several pipelines. We have established a workflow in which FITS images and/or (in the case of X ray data) an X-ray field can be input to WESIX. Intelligent services return available data (if requested fields have been processed) or submit job requests to a queue to be performed asynchronously. These services will be available via web services (for non-interactive use by Virtual Observatory portals and applications) and through web applications (written in the Django web application framework). We are adding web services for specific XAssist functionality such as determining .the exposure and limiting flux for a given position on the sky and extracting spectra and images for a given region. We are improving the queuing system in XAssist to allow for "watch lists" to be specified by users, and when X-ray fields in a user's watch list become publicly available they will be automatically added to the queue. XAssist is being expanded to be used as a survey planning 1001 when coupled with simulation software, including functionality for NuStar, eRosita, IXO, and the Wide Field Xray Telescope (WFXT), as part of an end to end simulation/analysis system. We are also investigating the possibility of a dedicated iPhone/iPad app for querying pipeline data, requesting processing, and administrative job control.

Ptak, A.

Monitoring real-time navigation processes using the automated reasoning tool (ART)

An expert system is described for monitoring and controlling navigation processes in real-time. The ART-based system features data-driven computation, accommodation of synchronous and asynchronous data, temporal modeling for individual time intervals and chains of time intervals, and hypothetical reasoning capabilities that consider alternative interpretations of the state of navigation processes. The concept is illustrated in terms of the NAVEX system for monitoring and controlling the high speed ground navigation console for Mission Control at Johnson Space Center. The reasoning processes are outlined, including techniques used to consider alternative data interpretations. Installation of the system has permitted using a single operator, instead of three, to monitor the ascent and entry phases of a Shuttle mission.

Maletz, M. C.

ON-OFF neuromorphic ISING machines using Fowler-Nordheim annealers

We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using a Fowler-Nordheim quantum mechanical tunneling based threshold-annealing process. The core component of NeuroSA consists of a pair of asynchronous ON-OFF neurons, which effectively map classical simulated annealing dynamics onto a network of integrate-and-fire neurons. The threshold of each ON-OFF neuron pair is adaptively adjusted by an FN annealer and the resulting spiking dynamics replicates the optimal escape mechanism and convergence of SA, particularly at low-temperatures. To validate the effectiveness of our neuromorphic Ising machine, we systematically solved benchmark combinatorial optimization problems such as MAX-CUT and Max Independent Set. Across multiple runs, NeuroSA consistently generates distribution of solutions that are concentrated around the state-of-the-art results (within 99%) or surpass the current state-of-the-art solutions for Max Independent Set benchmarks. Furthermore, NeuroSA is able to achieve these superior distributions without any graph-specific hyperparameter tuning. For practical illustration, we present results from an implementation of NeuroSA on the SpiNNaker2 platform, highlighting the feasibility of mapping our proposed architecture onto a standard neuromorphic accelerator platform.

42 ENGINEERING

AR/D image processing system

General Dynamics has developed advanced hardware, software, and algorithms for use with the Tomahawk cruise missile and other unmanned vehicles. We have applied this technology to the problem of locating and determining the orientation of the docking port of a target vehicle with respect to an approaching spacecraft. The system described in this presentation utilizes a multi-processor based computer to digitize and process television imagery and extract parameters such as range to the target vehicle, approach, velocity, and pitch and yaw angles. The processor is based on the Inmos T-800 Transputer and is configured as a loosely coupled array. Each processor operates asynchronously and has its own local memory. This allows additional processors to be easily added if additional processing power is required for more complex tasks. Total system throughput is approximately 100 MIPS (scalar) and 60 MFLOPS and can be expanded as desired. The algorithm implemented on the system uses a unique adaptive thresholding technique to locate the target vehicle and determine the approximate position of the docking port. A target pattern surrounding the port is than analyzed in the imagery to determine the range and orientation of the target. This information is passed to an autopilot which uses it to perform course and speed corrections. Future upgrades to the processor are described which will enhance its capabilities for a variety of missions.

Wookey, Cathy

Method and Apparatus for Automated Isolation of Nucleic Acids from Small Cell Samples

RNA isolation is a ubiquitous need, driven by current emphasis on microarrays and miniaturization. With commercial systems requiring 100,000 to 1,000,000 cells for successful isolation, there is a growing need for a small-footprint, easy-to-use device that can harvest nucleic acids from much smaller cell samples (1,000 to 10,000 cells). The process of extraction of RNA from cell cultures is a complex, multi-step one, and requires timed, asynchronous operations with multiple reagents/buffers. An added complexity is the fragility of RNA (subject to degradation) and its reactivity to surface. A novel, microfluidics-based, integrated cartridge has been developed that can fully automate the complex process of RNA isolation (lyse, capture, and elute RNA) from small cell culture samples. On-cartridge cell lysis is achieved using either reagents or high-strength electric fields made possible by the miniaturized format. Traditionally, silica-based, porous-membrane formats have been used for RNA capture, requiring slow perfusion for effective capture. In this design, high efficiency capture/elution are achieved using a microsphere-based "microfluidized" format. Electrokinetic phenomena are harnessed to actively mix microspheres with the cell lysate and capture/elution buffer, providing important advantages in extraction efficiency, processing time, and operational flexibility. Successful RNA isolation was demonstrated using both suspension (HL-60) and adherent (BHK-21) cells. Novel features associated with this development are twofold. First, novel designs that execute needed processes with improved speed and efficiency were developed. These primarily encompass electric-field-driven lysis of cells. The configurations include electrode-containing constructs, or an "electrode-less" chip design, which is easy to fabricate and mitigates fouling at the electrode surface; and the "fluidized" extraction format based on electrokinetically assisted mixing and contacting of microbeads in a shape-optimized chamber. A secondary proprietary feature is in the particular layout integrating these components to perform the desired operation of RNA isolation. Apart from a novel functional capability, advantages of the innovation include reduced or eliminated use of toxic reagents, and operator-independent extraction of RNA.

Sundaram, Shivshankar

Adaptive parallel logic networks

Adaptive, self-organizing concurrent systems (ASOCS) that combine self-organization with massive parallelism for such applications as adaptive logic devices, robotics, process control, and system malfunction management, are presently discussed. In ASOCS, an adaptive network composed of many simple computing elements operating in combinational and asynchronous fashion is used and problems are specified by presenting if-then rules to the system in the form of Boolean conjunctions. During data processing, which is a different operational phase from adaptation, the network acts as a parallel hardware circuit.

Martinez, Tony R.

Asynchronous GPU-based DEM solver embedded in commercial CFD software with polyhedral mesh support

A novel graphical processing unit-based discrete element method solver is introduced to improve stability, performance, and provide seamless integration into commercial or open-source computational fluid dynamics software. A key innovation is eliminating a need for network communication between solvers, which was previously required for cross-platform coupling. This is accomplished by a direct coupling method that employs dynamic-linked libraries. Furthermore, the solver optimizes memory usage by streamlining the particle-cell search algorithm by eliminating the cells' searching grid. This ensures the solver is compatible with a wide range of mesh types, providing high geometric flexibility. The approach simplifies the simulation process by directly incorporating computational fluid dynamics mesh information into the discrete element method solver. The performance analysis indicates about sixteen times boost in computational speed compared to benchmark central processing unit-based solvers. Finally, the solver's compatibility with polyhedral meshes, a vital advantage for complex geometries, is tested against a referenced study regarding the simulation of an immersed-tube fluidized bed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Real-Time Considerations for A Source-Time Dominant Auralization Scheme

A well-designed recording system can capture a moving source without risk of distortions, knowledge of the source or path, or transmission of information back to the source (i.e., a smartphone can reasonably record a plane flying overhead). This necessarily happens in real time. It would be good if signal processing schemes for auralization possessed these properties. Recent work on the NoTAP method of auralization proposed an asynchronous sample rate conversion scheme that keeps track of the (nonuniform) rate of incoming samples to formulate an effective incoming sampling frequency. This value allows the method to predict what frequency regions at the receiver are vulnerable to aliasing or imaging artifacts. Strategies of oversampling and filtering can be used to eliminate these problem regions while preserving as much of the original content as possible given the desired receiver sampling frequency. This approach creates a situation where the receiver processing can run independently of the source/path processing making it attractive for real-time implementation. This presentation discusses the challenges associated with producing a truly real-time scheme. A three-way tradeoff emerges between an interpolation mechanism that generates decorrelated noise, the computational burden, and the nearness to absolute real-time with which one wants the scheme to run.

Auralization

Advanced systems for shuttle launch processing

Four advanced technologies that could be used in a new shuttle launch processing center are described. The latest methods for high capacity data storage technology, disk arrays and magneto optical disks, are described and their advantages and disadvantages compared. A 3-D protein based optical memory, now being researched, is also described as a possible future technology for data storage. An overview of neural network technology is presented together with several commercial software development options now available for neural network applications. The feasibility of Asynchronous Data Transfer technology as the networking technology to integrate video, voice, and data in a new launch processing center is also considered. Different applications of expert system technology at KSC are enumerated together with a number of commercial expert systems development packages presently available.

Perez, Rafael A.

Approach for energy efficient building design during early phase of design process

Energy consumption in the building sector is about 40% of total energy consumed globally and is trending upwards, along with its contribution to greenhouse gas (GHG) emissions. Given the adverse impacts of GHG emissions, it is crucial to integrate energy efficiency into building designs. The most significant opportunities for enhancing energy performance are present during the initial phases of building design, when there is less impact of other design constraints. Various tools exist for simulating different design options and providing feedback in terms of energy consumption and comfort parameters. These simulation outputs must then be analyzed to derive design solutions. This paper presents an innovative approach that utilizes user input parameters, processes them through cloud computing, and outputs easily understandable strategies for energy-efficient building design. The methodology employs Asynchronous Distributed Task Queues (DTQ) - a more scalable and reliable alternative to conventional speedup techniques-for conducting parametric energy simulations in the cloud. The goal of this approach is to assist design teams in identifying, visualizing, and prioritizing energy-saving design strategies from a range of possible solutions for each project. Furthermore, a tool ‘eDOT’ has been developed utilizing the discussed methodology. Unlike existing tools, eDOT leverages artificial intelligence to dynamically generate and provide design strategies during the early phases of design process. By simplifying the simulation process, eDOT enables design teams to make informed, data-driven decisions without needing to interpret complex simulation outputs. A case study simulated for two locations is provided in this paper to demonstrate the effectiveness of eDOT, further underscoring its practical impact on energy-efficient building design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

A multiprocessing architecture for real-time monitoring

A multiprocessing architecture for performing real time monitoring and analysis using knowledge-based problem solving techniques is discussed. To handle asynchronous inputs and perform in real time, the system consists of three or more separate processes which run concurrently on one or more processors and communicate via a message passing scheme. The Data Management Process gathers, compresses, scales and sends the incoming telemetry data to other tasks. The Inference Process consists of a proprietary high performance inference engine that runs at 1000 rules per second using telemetry data to perform real time analysis on the state and health of the Space Telescope. The multiprocessing architecture has been interfaced to a simulator and is able to process the incoming telemetry in real time.

Laffey, Thomas J.

A multiprocessing architecture for real-time monitoring

A multitasking architecture for performing real-time monitoring and analysis using knowledge-based problem solving techniques is described. To handle asynchronous inputs and perform in real time, the system consists of three or more distributed processes which run concurrently and communicate via a message passing scheme. The Data Management Process acquires, compresses, and routes the incoming sensor data to other processes. The Inference Process consists of a high performance inference engine that performs a real-time analysis on the state and health of the physical system. The I/O Process receives sensor data from the Data Management Process and status messages and recommendations from the Inference Process, updates its graphical displays in real time, and acts as the interface to the console operator. The distributed architecture has been interfaced to an actual spacecraft (NASA's Hubble Space Telescope) and is able to process the incoming telemetry in real-time (i.e., several hundred data changes per second). The system is being used in two locations for different purposes: (1) in Sunnyville, California at the Space Telescope Test Control Center it is used in the preflight testing of the vehicle; and (2) in Greenbelt, Maryland at NASA/Goddard it is being used on an experimental basis in flight operations for health and safety monitoring.

Schmidt, James L.

Real-time analysis of telemetry data

This paper descibes a knowledge-based system for performing real-time monitoring and analysis of telemetry data from the NASA Hubble Space Telescope (HST). In order to handle asynchronous inputs and perform in real time the system consists of three or more separate processes, which run concurrently and communicate via a message passing scheme. The data management process gathers, compresses, and scales the incoming telemetry data befoe sending it to the other tasks. The inferencing process uses the incoming data to perform a real-time analysis of the state and health of the Space Telescope. The I/O process receives telemetry monitors from the data management process, updates its graphical displays in real time, and acts as the interface to the console operator. The three processes may run on the same or different computers. This system is currently under development and is being used to monitor testcases produced by the Bass Telemetry System in the Hardware/Software Integration Facility at Lockheed Missile and Space Co. in Sunnyvale, California.

Kao, Simon A.