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At least 973 records · Page 54

Aho-Corasick String Matching on Shared and Distributed Memory Parallel Architectures

String matching is at the core of many critical applications, including network intrusion detection systems, search engines, virus scanners, spam filters, DNA and protein sequencing, and data mining. For all of these applications string matching requires a combination of (sometimes all) the following characteristics: high and/or predictable performance, support for large data sets and flexibility of integration and customization. Many software based implementations targeting conventional cache-based microprocessors fail to achieve high and predictable performance requirements, while Field-Programmable Gate Array (FPGA) implementations and dedicated hardware solutions fail to support large data sets (dictionary sizes) and are difficult to integrate and customize. The advent of multicore, multithreaded, and GPU-based systems is opening the possibility for software based solutions to reach very high performance at a sustained rate. This paper compares several software-based implementations of the Aho-Corasick string searching algorithm for high performance systems. We discuss the implementation of the algorithm on several types of shared-memory high-performance architectures (Niagara 2, large x86 SMPs and Cray XMT), distributed memory with homogeneous processing elements (InfiniBand cluster of x86 multicores) and heterogeneous processing elements (InfiniBand cluster of x86 multicores with NVIDIA Tesla C10 GPUs). We describe in detail how each solution achieves the objectives of supporting large dictionaries, sustaining high performance, and enabling customization and flexibility using various data sets.

99 GENERAL AND MISCELLANEOUS↗

Securing Ground Data System Applications for Space Operations

The increasing prevalence and sophistication of cyber attacks has prompted the Multimission Ground Systems and Services (MGSS) Program Office at Jet Propulsion Laboratory (JPL) to initiate the Common Access Manager (CAM) effort to protect software applications used in Ground Data Systems (GDSs) at JPL and other NASA Centers. The CAM software provides centralized services and software components used by GDS subsystems to meet access control requirements and ensure data integrity, confidentiality, and availability. In this paper we describe the CAM software; examples of its integration with spacecraft commanding software applications and an information management service; and measurements of its performance and reliability.

Security↗

Hybrid learning techniques for scientific data reduction with performance guarantees

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗

Final report- UFL - RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗

The NASA Tetrahedral Unstructured Software System (TETRUSS)

The NASA Tetrahedral Unstructured Software System (TetrUSS) was developed during the 1990's to provide a rapid aerodynamic analysis and design capability to applied aerodynamicists. The system is comprised of loosely integrated, user-friendly software that enables the application of advanced Euler and Navier-Stokes tetrahedral finite volume technology to complex aerodynamic problems. TetrUSS has matured well because of the generous feedback from many willing users representing a broad cross-section of background and skill levels. This paper presents an overview of the current capabilities of the TetrUSS system along with some representative results from selected applications.

Frink, Neal T.↗

Evidence Arguments for Using Formal Methods in Software Certification

We describe a generic approach for automatically integrating the output generated from a formal method/tool into a software safety assurance case, as an evidence argument, by (a) encoding the underlying reasoning as a safety case pattern, and (b) instantiating it using the data produced from the method/tool. We believe this approach not only improves the trustworthiness of the evidence generated from a formal method/tool, by explicitly presenting the reasoning and mechanisms underlying its genesis, but also provides a way to gauge the suitability of the evidence in the context of the wider assurance case. We illustrate our work by application to a real example-an unmanned aircraft system- where we invoke a formal code analysis tool from its autopilot software safety case, automatically transform the verification output into an evidence argument, and then integrate it into the former.

Argumentation↗

Integrators

Many electromagnetic measurements detect signals that are the time derivative of the actual quantity of interest. Examples include so-called “B-dot” and “D-dot” detectors that are used for measuring transient magnetic and electric fields. Integration of these signals to recover the quantity of interest is performed either by hardware integrators in the signal line, or by software coding in the analysis programming. Hardware integration is usually done using a classic resistive-capacitive (RC) circuit, or internally in the detector by induction (L/R) or stray capacitance (RC). These hardware integration methods are only approximate, and must be corrected for distortion. This is usually called “droop correction.” In this note, we will examine this correction in some detail. Transient analysis via Laplace transforms will be used to simplify the mathematics. A rudimentary understanding of this method is assumed.

42 ENGINEERING↗

NASA's Software Bank (CLIPS)

C Language Integrated Production System (CLIPS) was used by Esse Systems to develop an expert system for clients who want to automate portions of their operations. The resulting program acts as a scheduling expert and automates routine, repetitive scheduling decisions, allowing employees to spend time on more creative projects.

Source record↗

Designing a configuration control mechanism for a flight software validation facility

Embedded computer systems and supporting operating systems have recently enabled the automation of many time-critical flight functions. This automation requires the integration of computer hardware and software, aircraft hardware, and the flight application. To properly integrate and control these critical functions requires a real-time environment that is provided by the onboard flight computer, a real-time operating system, and a real-time flight application that supplies the input commands to the aircraft and responds to the resulting actions. The increased complexity of developing and testing such real-time applications can best be supported by a separate test facility that provides the processing visibility and control which is virtually impossible in the actual real-time operating environment. Such a flight software validation facility has been developed at the NASA Langley Research Center to support applications using the Shuttle real-time language HAL/S. The development and control of this facility are described. Some of the management techniques used were project schedules, status monitoring, code walk-throughs, configuration control, phased releases, validation suites, and modern programming techniques.

Smith-Taylor, R.↗

Evolving software reengineering technology for the emerging innovative-competitive era

This paper reports on a multi-tool commercial/military environment combining software Domain Analysis techniques with Reusable Software and Reengineering of Legacy Software. It is based on the development of a military version for the Department of Defense (DOD). The integrated tools in the military version are: Software Specification Assistant (SSA) and Software Reengineering Environment (SRE), developed by Computer Command and Control Company (CCCC) for Naval Surface Warfare Center (NSWC) and Joint Logistics Commanders (JLC), and the Advanced Research Project Agency (ARPA) STARS Software Engineering Environment (SEE) developed by Boeing for NAVAIR PMA 205. The paper describes transitioning these integrated tools to commercial use. There is a critical need for the transition for the following reasons: First, to date, 70 percent of programmers' time is applied to software maintenance. The work of these users has not been facilitated by existing tools. The addition of Software Reengineering will also facilitate software maintenance and upgrading. In fact, the integrated tools will support the entire software life cycle. Second, the integrated tools are essential to Business Process Reengineering, which seeks radical process innovations to achieve breakthrough results. Done well, process reengineering delivers extraordinary gains in process speed, productivity and profitability. Most importantly, it discovers new opportunities for products and services in collaboration with other organizations. Legacy computer software must be changed rapidly to support innovative business processes. The integrated tools will provide commercial organizations important competitive advantages. This, in turn, will increase employment by creating new business opportunities. Third, the integrated system will produce much higher quality software than use of the tools separately. The reason for this is that producing or upgrading software requires keen understanding of extremely complex applications which is facilitated by the integrated tools. The radical savings in the time and cost associated with software, due to use of CASE tools that support combined Reuse of Software and Reengineering of Legacy Code, will add an important impetus to improving the automation of enterprises. This will be reflected in continuing operations, as well as in innovating new business processes. The proposed multi-tool software development is based on state of the art technology, which will be further advanced through the use of open systems for adding new tools and experience in their use.

Hwang, Phillip Q.↗

Design of Multivariable Controllers Using the Integrated Analysis Capability (IAC)

Dynamic analysis and controls design for flexible spacecraft involves high-order dynamic systems with multiple inputs and outputs. Computer tools are essential for such analysis. The controls/structures interaction analysis capability of an inter-disciplinary computer software system, called the Integrated Analysis Capability (IAC), is described. An overview of IAC components and procedures is presented, and an example of a preliminary space station controls design is shown.

Bossi, J. A.↗

A satellite data processing and analysis software system for earth's atmosphere and surface research

The OASIS (Oceanic and Atmospheric Satellite Imaging System) is a satellite data processing and analysis software system being developed by the California Space Institute (Cal Space) for support of interdisciplinary and integrated earth sciences research programs. The system's software applications are integrated under a common executive, NASA's Transportable Application Executive (TAE). In this paper, TAE and the system software and hardware are described, and specific techniques used for ingesting, processing, analyzing, and graphically displaying data from many of the sensors presently being flown are presented. Scientific uses of these capabilities that are, or will shortly be, running under TAE at Cal Space are described.

Dealy, B.↗

Automating the parallel processing of fluid and structural dynamics calculations

The NASA Lewis Research Center is actively involved in the development of expert system technology to assist users in applying parallel processing to computational fluid and structural dynamic analysis. The goal of this effort is to eliminate the necessity for the physical scientist to become a computer scientist in order to effectively use the computer as a research tool. Programming and operating software utilities have previously been developed to solve systems of ordinary nonlinear differential equations on parallel scalar processors. Current efforts are aimed at extending these capabilities to systems of partial differential equations, that describe the complex behavior of fluids and structures within aerospace propulsion systems. This paper presents some important considerations in the redesign, in particular, the need for algorithms and software utilities that can automatically identify data flow patterns in the application program and partition and allocate calculations to the parallel processors. A library-oriented multiprocessing concept for integrating the hardware and software functions is described.

Arpasi, Dale J.↗

Automating the parallel processing of fluid and structural dynamics calculations

The NASA Lewis Research Center is actively involved in the development of expert system technology to assist users in applying parallel processing to computational fluid and structural dynamic analysis. The goal of this effort is to eliminate the necessity for the physical scientist to become a computer scientist in order to effectively use the computer as a research tool. Programming and operating software utilities have previously been developed to solve systems of ordinary nonlinear differential equations on parallel scalar processors. Current efforts are aimed at extending these capabilties to systems of partial differential equations, that describe the complex behavior of fluids and structures within aerospace propulsion systems. This paper presents some important considerations in the redesign, in particular, the need for algorithms and software utilities that can automatically identify data flow patterns in the application program and partition and allocate calculations to the parallel processors. A library-oriented multiprocessing concept for integrating the hardware and software functions is described.

Arpasi, Dale J.↗

Understanding Bifacial PV Modeling: Raytracing and View Factor Models

As part of the PV Magazine Webinar 'View-factor vs. ray tracing - which bifacial modelling techniques should you use?,' the second part lead by NREL will explore the different rear-irradiance calculation software, which fall into two categories: view-factor and ray-tracing models. View factor models assume isotropic scattering of reflected rays, allowing for calculation of irradiance by integration. Due-diligence software such as PVSyst or SAM use the view-factor model. Ray-tracing models simulate multipath reflection and absorption of individual rays entering a scene. Raytracing software such as bifacial_radiance, which is the only available open-source toolkit, offers the possibility of reproducing complex scenes, including shading or finite-system edge effects. This can be useful to evaluate specific system geometries, shading and obstructions, areas of different albedo and electrical mismatch, all topics of interest to the prediction of bifacial performance. Model agreement for view factors and bifacial_radiance software is improving and has been shown to be between 2% (absolute) when compared with measured results.

14 SOLAR ENERGY↗

Cyber security best practices for the nuclear industry

When deploying software based systems, such as, digital instrumentation and controls for the nuclear industry, it is vital to include cyber security assessment as part of architecture and development process. When integrating and delivering software-intensive systems for the nuclear industry, engineering teams should make use of a secure, requirements driven, software development life cycle, ensuring security compliance and optimum return on investment. Reliability protections, data loss prevention, and privacy enforcement provide a strong case for installing strict cyber security policies. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

CESAR5.3: An Industrial Tool for Nuclear Fuel and Waste Characterization with Associated Qualification - 12067

CEA and AREVA-NC have developed and used a depletion code named CESAR for 30 years. This user-friendly industrial tool provides fast characterizations for all types of nuclear fuel (PWR / UOX or MOX or reprocess Uranium, BWR / UOX or MOX, MTR and SFR) and the wastes associated. CESAR can evaluate 100 heavy nuclides, 200 fission products and 150 activation products (with Helium and Tritium formation). It can also characterize the structural material of the fuel (Zircalloy, stainless steel, M5 alloy). CESAR provides depletion calculations for any reactor irradiation history and from 3 months to 1 million years of cooling time. CESAR5.3 is based on the latest calculation schemes recommended by the CEA and on an international nuclear data base (JEFF-3.1.1). It is constantly checked against the CEA referenced and qualified depletion code DARWIN. CESAR incorporates the CEA qualification based on the dissolution analyses of fuel rod samples and the 'La Hague' reprocessing plant feedback experience. AREVA-NC uses CESAR intensively at 'La Hague' plant, not only for prospective studies but also for characterizations at different industrial facilities all along the reprocessing process and waste conditioning (near 150 000 calculations per year). CESAR is the reference code for AREVA-NC. CESAR is used directly or indirectly with other software, data bank or special equipment in many parts of the La Hague plants. The great flexibility of CESAR has rapidly interested other projects. CESAR became a 'tool' directly integrated in some other softwares. Finally, coupled with a Graphical User Interface, it can be easily used independently, responding to many needs for prospective studies as a support for nuclear facilities or transport. An English version is available. For the principal isotopes of U and Pu, CESAR5 benefits from the CEA experimental validation for the PWR UOX fuels, up to a burnup of 60 GWd/t and for PWR MOX fuels, up to 45 GWd/t. CESAR version 5.3 uses the CEA reference calculation codes for neutron physics with the JEFF-3.1.1 nuclear data set. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

WeightedAFL

WeightedAFL (WAFL) is an improvement to open source fuzzer, American Fuzzy Lop (AFL). Fuzzers modify input to target programs in order to produce crashes and other unintended output in those target programs. WAFL integrates directly with AFL to determine offsets within a buffer that will improve performance metrics. WAFL uses various machine learning techniques to learn these offsets. WAFL also provides a novel software engineering solution to integrate with AFL and allows contributors to quickly write and test algorithms in python. SAND2020-12546 O Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Kincher-Winoto, Kina↗