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Computer software for ensembling all the space vehicle (SV) and ground clocks of the Global Positioning Systems (GPS) was implemented at the Master Control Station (MCS) on 17 June 1990. Improved GPS time stability and steering control are predicted. The perceptions of both Air Force and outside users are assessed. Current performance is compared with theoretical predictions.
Designers use computational fluid dynamics (CFD) to gain greater understanding of the fluid flow phenomena involved in components being designed. They also use finite element analysis (FEA) as a tool to help gain greater understanding of the structural response of components to loads, stresses and strains, and the prediction of failure modes. Automated CFD and FEA engineering design has centered on shape optimization, which has been hindered by two major problems: 1) inadequate shape parameterization algorithms, and 2) inadequate algorithms for CFD and FEA grid modification. Working with software engineers at Stennis Space Center, a NASA commercial partner, Optimal Solutions Software LLC, was able to utilize its revolutionary, one-of-a-kind arbitrary shape deformation (ASD) capability-a major advancement in solving these two aforementioned problems-to optimize the shapes of complex pipe components that transport highly sensitive fluids. The ASD technology solves the problem of inadequate shape parameterization algorithms by allowing the CFD designers to freely create their own shape parameters, therefore eliminating the restriction of only being able to use the computer-aided design (CAD) parameters. The problem of inadequate algorithms for CFD grid modification is solved by the fact that the new software performs a smooth volumetric deformation. This eliminates the extremely costly process of having to remesh the grid for every shape change desired. The program can perform a design change in a markedly reduced amount of time, a process that would traditionally involve the designer returning to the CAD model to reshape and then remesh the shapes, something that has been known to take hours, days-even weeks or months-depending upon the size of the model.
NASA’s Katherine Johnson Independent Verification and Validation (IV&V) Independent Test Capability (ITC) Team develops high fidelity software-only simulations (or “digital-twins”) of NASA’s most critical missions that are then used for software verification and validation (V&V). One such digital-twin simulator nearing maturity is the Psyche Hardware Abstraction Simulation Environment (PHASE). PHASE utilizes an instruction set simulator along with ITC-developed avionics models. PHASE includes a newly-developed model of the telecom hardware with a high-fidelity downlink interface, capable of supporting reconfigurable downlink data rates and transmission modes. The different downlink transmission modes allow more processing to be ceded from software onto the telecom hardware. Thus, we are able to monitor the performance of the downlink software module in the time-partitioned OS and perform more realistic dynamic testing based on software’s resource utilization. This presentation will cover PHASE, avionics modeling, the downlink model, and its usage for flight software performance testing.
Navigating the broad and rapidly evolving market landscape of software solutions is complex whether you are a sustainability leader, building owner, energy manager, or building engineer with energy and greenhouse gas (GHG) emissions reduction goals for a portfolio of buildings. The Department of Energy’s Better Buildings partners have noted this complexity and the associated lack of publicly available information. In response, this report reviews the ecosystem of environmental, social, and governance (ESG), energy management information systems (EMIS), and decarbonization software with the goal of orienting prospective users to current offerings. Organizations can utilize this guidance to determine the specific capabilities needed to support decarbonization efforts and procure appropriate software to streamline the GHG emissions reduction process. In this paper, we refer to “decarbonization software” as the category of software that meets an organization’s needs for decarbonization planning, implementation, and tracking. This software may have a heritage in ESG or EMIS, or it may be an entirely new product. This report offers a snapshot of today’s rapidly evolving decarbonization software capabilities, along with guidance for procuring and utilizing it that will remain relevant despite any future software changes. Exploratory research was conducted on over 100 software providers, and interviews were held with 28 of them. Note that inclusion in this report does not indicate an endorsement, nor does a product’s absence from this report indicate a lack of suitability
We describe a software emulator of the MIL-STD-1750A architecture that executes 1750A code at a rate of about 4 MIPS on a Sun 200MHz Ultra2 work-station, and effectively several times faster than that when application-specific optimizations are used.
The system performance test software is currently being modified to include additional capabilities and enhancements. Additional software programs are currently being developed for the Command Store and Forward System and the Automatic Total Recall System. The test executive is the main program. It controls the input and output of the individual test programs by routing data blocks and operator directives to those programs. It also processes data block dump requests from the operator.
The objective of this project was to improve upon the existing Watchr software that charts performance test metrics from the Trilinos project run on supercomputers at Sandia and elsewhere across the DOE complex. Software was iteratively designed and developed using Python Pandas and Dash data visualization to improve the extensibility and user experience of Watchr. Documentation is being maintained for future developers who want to extend the application.
ANSI/ASHRAE Standard 140 Method of Test for Evaluating Building Performance Simulation Software specifies the method to test the core competency of building performance simulation (BPS) software, a broad class of software which includes building energy modeling (BEM) software. Standard 140 has been widely used by BEM software vendors to help diagnose and compare the results from the program with other modeling programs. The Standard is also referenced by codes, standards, government programs, and other incentive programs as a part of minimum requirements for qualifying BEM software. The explanatory information, summary tables and figures in this 140 User’s Manual (referred to as “this Manual”) are provided to help users in implementing various suites of tests specified in Standard 140-2023 (referred to in this manual as “Standard 140” or “the Standard”).
The top down implementation plan used for the development of system performance test software during the Mark IV-A era is described. The plan is based upon the identification of the hierarchical relationship of the individual elements of the software design, the development of a sequence of functionally oriented demonstrable steps, the allocation of subroutines to the specific step where they are first required, and objective status reporting. The results are: determination of milestones, improved managerial visibility, better project control, and a successful software development.
This article describes the syntax editing concepts used by the Operations Sustaining Engineering Section in implementing System Performance Test software for the Mark 4-A era. The processing functions are discussed, as well as the necessary data structures and table generation macros used in implementing those functions. In addition, the procedural and software interfaces which have been developed for users of the syntax editor are described, including the forms required for establishing directive and parameter characteristics.
We address the problem of predicting future failures for a piece of software. The number of failures occurring during a finite future time interval is predicted from the number failures observed during an initial period of usage by using software reliability growth models. Two different methods for using the models are considered: straightforward use of individual models, and dynamic selection among models based on goodness-of-fit and quality-of-prediction criteria. Performance is judged by the relative error of the predicted number of failures over future finite time intervals relative to the number of failures eventually observed during the intervals. Six of the former models and eight of the latter are evaluated, based on their performance on twenty data sets. Many open questions remain regarding the use and the performance of software reliability growth models.
The software support group of the Deep Space Network support section is continuing the development of system performance test (SPT) software for the Deep Space Network. During the past two and one-half years, test software was developed for a new system, Radio Science, and many new features were added to existing software. Plans are underway for implementation of test software for the very long baseline interferometry system and the network data processing area. A description of the elements of the SPT software is provided.
A development status evaluation is presented for practical software performance measurement, or 'metrics', in which major innovations have recently occurred. Metrics address such aspects of software performance as whether a software project is on schedule, how many errors can be expected from it, whether the methodology being used is effective and the relative quality of the software employed. Metrics may be characterized as explicit, analytical, and subjective. Attention is given to the bases for standards and the conduct of metrics research.
The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) is currently developing an operational Tracking and Data Relay Satellite (TDRS) System (TDRSS) Onboard Navigation System (TONS) to provide realtime, autonomous, high-accuracy navigation products to users of TDRSS. A TONS experiment was implemented on the Explorer Platform/Extreme Ultraviolet Explorer (EP/EUVE) spacecraft, launched June 7, 1992, to flight qualify the TONS operational system using TDRSS forward-link communications services. This paper provides a detailed evaluation of the flight hardware, an ultrastable oscillator (USO) and Doppler extractor (DE) card in one of the TDRSS user transponders and the ground-based prototype flight software performance, based on the 1 year of TONS experiment operation. The TONS experiment results are used to project the expected performance of the TONS 1 operational system. TONS 1 processes Doppler data derived from scheduled forward-link S-band services using a sequential estimation algorithm enhanced by a sophisticated process noise model to provide onboard orbit and frequency determination and time maintenance. TONS 1 will be the prime navigation system on the Earth Observing System (EOS)-AM1 spacecraft, currently scheduled for launch in 1998. Inflight evaluation of the USO and DE short-term and long-term stability indicates that the performance is excellent. Analysis of the TONS prototype flight software performance indicates that realtime onboard position accuracies of better than 25 meters root-mean-square are achievable with one tracking contact every one to two orbits for the EP/EUVE 525-kilometer altitude, 28.5 degree inclination orbit. The success of the TONS experiment demonstrates the flight readiness of TONS to support the EOS-AM1 mission.
ScalES is a high performance software package for performing large scale electronic structure calculations on high performance supercomputers.
We apply AI-assisted large language model (LLM) capabilities of GPT-3 targeting high-performance computing (HPC) kernels for (i) code generation, and (ii) auto-parallelization of serial code in C ++, Fortran, Python and Julia. Our scope includes the following fundamental numerical kernels: AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG, and language/programming models: (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numpy, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). Kernel implementations are generated using GitHub Copilot capabilities powered by the GPT-based OpenAI Codex available in Visual Studio Code given simple + + prompt variants. To quantify and compare the generated results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. For auto-parallelization, we use ChatGPT interactively giving simple prompts as in a dialogue with another human including simple “prompt engineering” follow ups. Results suggest that correct outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general-purpose Python can benefit from adding language keywords, while Julia prompts perform acceptably well for its Threads and CUDA.jl programming models. Finally, we expect to provide an initial quantifiable point of reference for code generation in each programming model using a state-of-the-art LLM. Overall, understanding the convergence of LLMs, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.
As parallel systems expand in size and complexity, the absence of performance tools for these parallel systems exacerbates the already difficult problems of application program and system software performance tuning. Moreover, given the pace of technological change, we can no longer afford to develop ad hoc, one-of-a-kind performance instrumentation software; we need scalable, portable performance analysis tools. We describe an environment prototype based on the lessons learned from two previous generations of performance data analysis software. Our environment prototype contains a set of performance data transformation modules that can be interconnected in user-specified ways. It is the responsibility of the environment infrastructure to hide details of module interconnection and data sharing. The environment is written in C++ with the graphical displays based on X windows and the Motif toolkit. It allows users to interconnect and configure modules graphically to form an acyclic, directed data analysis graph. Performance trace data are represented in a self-documenting stream format that includes internal definitions of data types, sizes, and names. The environment prototype supports the use of head-mounted displays and sonic data presentation in addition to the traditional use of visual techniques.
The Radio Science Systems Group (RSSG) provides various support functions for several flight project radio-science teams. Among these support functions are uplink and sequence planning, real-time operations monitoring and support, data validation, archiving and distribution functions, and data processing and analysis. This article describes the support functions that encompass radio-science data performance analysis. The primary tool used by the RSSG to fulfill this support function is the STBLTY program set. STBLTY is used to reconstruct observable frequencies and calculate model frequencies, frequency residuals, frequency stability in terms of Allan deviation, reconstructed phase, frequency and phase power spectral density, and frequency drift rates. In the case of one-way data, using an ultrastable oscillator (USO) as a frequency reference, the program set computes the spacecraft transmitted frequency and maintains a database containing the in-flight history of the USO measurements. The program set also produces graphical displays. Some examples and discussions on operating the program set on Galileo and Ulysses data will be presented.