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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Evolving impact of Ada on a production software environment

Many aspects of software development with Ada have evolved as our Ada development environment has matured and personnel have become more experienced in the use of Ada. The Software Engineering Laboratory (SEL) has seen differences in the areas of cost, reliability, reuse, size, and use of Ada features. A first Ada project can be expected to cost about 30 percent more than an equivalent FORTRAN project. However, the SEL has observed significant improvements over time as a development environment progresses to second and third uses of Ada. The reliability of Ada projects is initially similar to what is expected in a mature FORTRAN environment. However, with time, one can expect to gain improvements as experience with the language increases. Reuse is one of the most promising aspects of Ada. The proportion of reusable Ada software on our Ada projects exceeds the proportion of reusable FORTRAN software on our FORTRAN projects. This result was noted fairly early in our Ada projects, and experience shows an increasing trend over time.

Mcgarry, F.↗
NASA NTRS1994

Performance analysis of three dimensional integral equation computations on a massively parallel computer

The purpose of this study is to investigate the performance of the integral equation computations using numerical source field-panel method in a massively parallel processing (MPP) environment. A comparative study of computational performance of the MPP CM-5 computer and conventional Cray-YMP supercomputer for a three-dimensional flow problem is made. A serial FORTRAN code is converted into a parallel CM-FORTRAN code. Some performance results are obtained on CM-5 with 32, 62, 128 nodes along with those on Cray-YMP with a single processor. The comparison of the performance indicates that the parallel CM-FORTRAN code near or out-performs the equivalent serial FORTRAN code for some cases.

Logan, Terry G.↗
NASA NTRS2004

Certification of CFD heat transfer software for turbine blade analysis

Accurate modeling of heat transfer effects is a critical component of the Turbine Branch of the Turbomachinery and Propulsion Systems Division. Being able to adequately predict and model heat flux, coolant flows, and peak temperatures are necessary for the analysis of high pressure turbine blades. To that end, the primary goal of my internship this summer will be to certify the reliability of the CFD program GlennHT for the purpose of turbine blade heat transfer analysis. GlennHT is currently in use by the engineers in the Turbine Branch who use the FORTRAN 77 version of the code for analysis. The program, however, has been updated to a FORTRAN 90 version which is more robust than the older code. In order for the new code to be distributed for use, its reliability must first be certified. Over the course of my internship I will create and run test cases using the FORTRAN 90 version of GlennHT and compare the results to older cases which are known to be accurate, If the results of the new code match those of the sample cases then the newer version will be one step closer to certification for distribution. In order to complete these it will first be necessary to become familiar with operating a number of other programs. Among them are GridPro, which is used to create a grid mesh around a blade geometry, and FieldView, whose purpose is to graphically display the results from the GlennHT program. Once enough familiarity is established with these programs to render them useful, then the work of creating and running test scenarios will begin. The work is additionally complicated by a transition in computer hardware. Most of the working computers in the Turbine Branch are Silicon Graphics machines, which will soon be replaced by LINUX PC's. My project is one of the first to make use the new PC's. The change in system architecture however, has created several software related issues which have greatly increased the time and effort investments required by the project.Although complications with the project continue to arise, it is expected that the goal of my internship can still be achieved within the remaining time period. Critical steps have been achieved and test scenarios can now be designed and run. At the completion of my internship, the FORTRAN 90 version of GlennHT should be well on its way to certification.

Jordan, William A.↗
NASA NTRS2022

pyCRTM: A Python Interface for the Community Radiative Transfer Model

The Community Radiative Transfer Model (CRTM) is a powerful and versatile scalar radiative transfer model for satellite data assimilation and remote sensing applications. It is implemented as an object-oriented Fortran library, enabling flexible code development and optimal runtime performance on clusters. The downsides of the Fortran interface are a steep learning curve for students and the reduced productivity of users that is typical for static compiled languages, in contrast to dynamic interpreted languages like Python. pyCRTM is a new software framework that directly interfaces the CRTM Fortran data structures and procedures in Python, leveraging both the simplicity and ease of use of Python syntax as well as the flexibility arising from the vast contemporary Python ecosystem. The goal of pyCRTM is to lower the barrier of entry for university students to learn and use the CRTM and to boost the productivity of researchers seeking to create new methods in radiative transfer and data assimilation, or seeking to apply the CRTM to study atmospheric phenomena without having to go through the pre-existing complexity of the CRTM Fortran interface.

Python↗
NASA NTRS2011

Coarrars for Parallel Processing

The design of the Coarray feature of Fortran 2008 was guided by answering the question "What is the smallest change required to convert Fortran to a robust and efficient parallel language." Two fundamental issues that any parallel programming model must address are work distribution and data distribution. In order to coordinate work distribution and data distribution, methods for communication and synchronization must be provided. Although originally designed for Fortran, the Coarray paradigm has stimulated development in other languages. X10, Chapel, UPC, Titanium, and class libraries being developed for C++ have the same conceptual framework.

Fortran↗
DOE OSTI2024

Large language model evaluation for high–performance computing software development

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.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Using a Large Language Model as a Building Block to Generate Usable Validation and Verification Suite for OpenMP

In the HPC area, both hardware and software move quickly. Often new hardware is developed and deployed, the corresponding software stack, including compilers and other tools, are under active development while leading edge software developers are working to port and tune their applications, all at the same time. While the software ecosystem is in flux, one of the key challenges for users is obtaining insight into the state of implementation of key features in the programming languages and models their applications are using – whether they have been implemented, and whether the implementation conforms to the specification, especially for newly implemented features (less tested by widespread use). OpenMP is one of the most prominent shared memory programming models used for on-node programming in HPC. With the shift towards accelerators (such as GPUs and FPGAs) and heterogeneous programming OpenMP features are getting more complex. It is natural to ask whether generative AI approaches, and large language models (LLMs) in particular, can help in producing validation and verification test suites to allow users better and faster insights into the availability and correctness of OpenMP features of interest. In this work, we explore the use of ChatGPT-4 to generate a suite of tests for OpenMP features. We have chosen a set of directives and clauses, a total of 78 combinations, which first appeared in OpenMP 3.0 (released in May 2008) but are also relevant for accelerators. We prompted ChatGPT to generate tests in the C and Fortran languages, for both host (CPU) and device (accelerator). On the Summit super-computer using the GNU implementation, we found that, of the 78 generated tests 67 C tests and 43 Fortran tests compiled successfully and fewer than those executed to completion. On further analysis we show that not all generated tests are valid. We document the process, results, and provide detailed analysis regarding the quality of tests generated. With the aim of providing input to a production quality validation and verification suite, we manually implement the corrections required to make the tests valid according to the current OpenMP specification. We quantify this effort as small, medium, or large, and record the lines of code changed to correct the invalid tests. With the corrected tests we validate recent implementations from HPE, AMD, and GNU on the Frontier supercomputer. Our experiment and subsequent analysis show that although LLMs are capable of producing HPC specific codes, they are limited by their understanding of the deeper semantics and restrictions of programming models such as OpenMP. Unsurprisingly more commonly used features have better support, while some OpenMP 3.0 directives such as sections and tasking are not universally supported on accelerators. We demonstrate that successful compilation and execution to completion are inadequate metrics for evaluating generated code and that, at this time, commodity LLMs require expert intervention for code verification. This points to gaps in the training data that is currently available for HPC. We demonstrate that with "small" effort 37% of generated invalid C tests and 63% of generated invalid Fortran tests could be corrected. This improves productivity of test generation as we circumvent writing from scratch and the common programming errors associated with it.

Pophale, Swaroop [ORNL] (ORCID:0000000185446367)↗
DOE OSTI2024

Julienne v1.0.0

Julienne is a compiler-portable unit-testing framework for Fortran software projects, including those that use the parallel/accelerator-programming features of Fortran 2023. Julienne achieves portability across compilers through minimalism and isolation. The minimal design ensures that Julienne uses only features supported by the majority of Fortran compilers. The isolation through zero dependencies ensures that no other projects block Julienne from building with a particular compiler. Julienne also contains with additional services that support its unit-testing code. These include functions for manipulating strings, command lines and input/output format strings; and a user-defined collective subroutine for verifying that all processes pass a test in parallel testing. Julienne's name derives from the term for vegetables sliced into thin strings: julienne vegetables. Julienne captures the authors' most frequently used thin slice of the Veggies and Sourcery software repositories while avoiding certain compiler limitations of the those two packages.

Rouson, Damian↗
DOE OSTI2026

CodeScribe Agent

SF-26-086 CodeScribe introduces a structured, multi-stage pipeline that combines deterministic program analysis with LLM-powered translation to enable incremental, testable Fortran-to-C++ migration. First, `code-scribe index` traverses the project directory tree and produces `scribe.yaml` metadata files recording all modules, subroutines, and functions at each level, giving the LLM accurate structural context instead of a hallucinated codebase model. Second, `code-scribe draft` performs the deterministic portion of translation — converting Fortran types to C++ equivalents, replacing `use` statements with `#include` and `using namespace` directives, and detecting constructs requiring special handling — while embedding`scribe-prompt` annotations that guide the LLM through non-trivial cases such as statement-function-to-lambda conversions and `extern "C"` wrapper generation. Third, `code-scribe translate` applies project-specific TOML-based few-shot prompt templates and submits the composed prompt to a pluggable LLM backend (OpenAI, Anthropic, Argonne ARGO, any OpenAI-compatible endpoint, or local Hugging Face checkpoints), producing a C++ source file, a header, and a Fortran-C++ interface file for each translated routine so the codebase compiles and runs correctly throughout the migration. Beyond translation, CodeScribe includes a tool-using coding agent (`code-scribe agent`) with read, bash, edit, and write capabilities, and a bounded loop mode (`code-scribe loop`) that runs repeated stateless agent sessions over a task file with restricted tool access — enabling sustained, auditable software development workflows for broader scientific computing tasks.

Dhruv, Akash [Argonne National Laboratory (ANL), A↗
DOE OSTI2025

Fiats: Functional inference and training for surrogates

Fiats provides a platform for research on the training and deployment of neural-network surrogate models for computational science. Fiats also supports exploring, advancing, and combining functional, object-oriented, and parallel programming patterns in Fortran 2023. As such, the Fiats name has dual expansions: “Functional Inference And Training for Surrogates” or “Fortran Inference And Training for Science.” Fiats inference and training procedures are pure and therefore satisfy a language constraint imposed on procedure invocations inside Fortran’s parallel loop construct: do concurrent. Furthermore, the Fiats training procedures are built around a do concurrent parallel reduction. Several compilers can automatically parallelize do concurrent on Central Processing Units (CPUs) or Graphics Processing Units (GPUs). Fiats thus aims to achieve performance portability through standard language mechanisms.

Rouson, Damian [Lawrence Berkeley National Laborat↗
DOE OSTI2026

Coupling Noah-Multiparameterization land-surface Model with Energy Research and Forecasting Model

The Energy Research and Forecasting (ERF) model is a high-performance atmospheric model built on the AMReX adaptive mesh refinement (AMR) framework, enabling efficient simulations on heterogeneous computing platforms that combine multicore processors with hardware accelerators. To support land–atmosphere interactions within ERF’s AMR-based environment, a land-surface model must be capable of operating directly on hierarchically refined meshes. In this work, we present a methodology for coupling the Fortran-based Noah-Multiparameterization (Noah-MP) land-surface model with ERF’s C++ codebase. Rather than rewriting Noah-MP, we construct a Fortran–C interoperability layer using CodeScribe, a tool that leverages large language models (LLMs) to automate the generation of interface code. CodeScribe applies structured prompting techniques to generate bindings that support efficient data exchange and function calls between ERF and Noah-MP. The coupling framework also incorporates AMR-aware data handling strategies, allowing NoahMP to operate seamlessly within ERF’s hierarchical mesh structure. This work provides a structured approach for integrating legacy Fortran models into modern C++-based modeling systems using LLM-assisted code generation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Characterization of the space shuttle reaction control system engine

A computer program was developed and written in FORTRAN 5 which predicts the transient and steady state performance and heat transfer characteristics of a pulsing GO2/GH2 rocket engine. This program predicts the dynamic flow and ignition characteristics which, when combined in a quasi-steady state manner with the combustion and mixing analysis program, will provide the thrust and specific impulse of the engine as a function of time. The program also predicts the transient and steady state heat transfer characteristics of the engine using various cooling concepts. The computer program, test case, and documentation are presented. The program is applicable to any system capable of utilizing the FORTRAN 4 or FORTRAN 5 language.

Wilson, M. S.↗
NASA NTRS1973

Determination of the geometrical factor and of the spatial distributions of particles for a cosmic ray telescope using a Monte Carlo approach

A program is presented which uses a Monte Carlo technique to compute the geometrical factor of a detector, and the spatial and angular distributions of simulated particles at designated layers within the detector. As the program is written, each layer is assumed to be rectangular, parallel to every other layer with its edges parallel to the edges of every other layer, and centered about a common axis. This program is written in Fortran 4 for the IBM 360 computers and is currently being run under the Fortran 4 (h) compiler. Same features such as the subroutine ERRSET, RANDU, and REMTIM and the type declarations REAL *8 and LOGICAL *1 may need to be changed for use with a different computer system. The use of input data cards, and a sample data set are presented. Lists of the symbol definition, card images of the FORTRAN object deck and subroutines are included along with a flow diagram.

Hemmer, M.↗
NASA NTRS1974

Star adaptation for two-algorithms used on serial computers

Two representative algorithms used on a serial computer and presently executed on the Control Data Corporation 6000 computer were adapted to execute efficiently on the Control Data STAR-100 computer. Gaussian elimination for the solution of simultaneous linear equations and the Gauss-Legendre quadrature formula for the approximation of an integral are the two algorithms discussed. A description is given of how the programs were adapted for STAR and why these adaptations were necessary to obtain an efficient STAR program. Some points to consider when adapting an algorithm for STAR are discussed. Program listings of the 6000 version coded in 6000 FORTRAN, the adapted STAR version coded in 6000 FORTRAN, and the STAR version coded in STAR FORTRAN are presented in the appendices.

Howser, L. M.↗
NASA NTRS1978

The programming language EFL

EFL is a comprehensive language designed to make it easy to write portable, understandable programs. It provides a rich set of data types and structures, a convenient operator set, and good control flow forms. The lexical form is easy to type and to read. Whenever possible, EFL uses the same forms that Ratfor does; in this sense EFL may be viewed as a superset of Ratfor. EFL is a well-defined language; this distinguishes it from most FORTRAN preprocessors which only add simple flow of control constructs to FORTRAN. The EFL compiler generates (possibly tailored) Standard FORTRAN as its output. EFL should catch and diagnose all syntax errors.

Feldman, S. I.↗
NASA NTRS1980

Analysis and testing of numerical formulas for the initial value problem

Three computer programs for evaluating and testing numerical integration formulas used with fixed stepsize programs to solve initial value systems of ordinary differential equations are described. A program written in PASCAL SERIES, takes as input the differential equations and produces a FORTRAN subroutine for the derivatives of the system and for computing the actual solution through recursive power series techniques. Both of these are used by STAN, a FORTRAN program that interactively displays a discrete analog of the Liapunov stability region of any two dimensional subspace of the system. The derivatives may be used by CLMP, a FORTRAN program, to test the fixed stepsize formula against a good numerical result and interactively display the solutions.

Brown, R. L.↗
NASA NTRS1983

NAMELIST Preprocessor

FORTRAN code modified for use with F4P compiler. NAMELIST provides FORTRAN programer with additional, flexible input and output capabilities. Feature is particularly useful in area of data input because NAMELIST data are input in form of variable symbolic name being set equal to constant value, similar to standard FORTRAN statement. Allows user to review input data readily and relieves user from having to place data in certain columns and formats as required in formatted READ statements.

Merwarth, P. D.↗
NASA NTRS1984

QUICK Interactive Graphics Analysis

Cross-section and body-line plots generated for error detection and analysis. FORTRAN 77 version of QUICK Interactive Graphics Analysis program QUIAGA, performs same operations as FORTRAN IV counterpart. QUIAGA displays aircraft QUICK geometry data to aid in detection and analysis of errors. QUICK-geometry data used to generate completelyanalytical aircraft geometry description for finite difference flow codes. QUIAGA program written in FORTRAN 77.

Townsend, J. C.↗