Results for “code portability” — Page 24

DOE OSTI2014

PETSc Users Manual (Rev. 3.4)

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication. PETSc includes an expanding suite of parallel linear, nonlinear equation solvers and time integrators that may be used in application codes written in Fortran, C, C++, Python, and MATLAB (sequential). PETSc provides many of the mechanisms needed within parallel application codes, such as parallel matrix and vector assembly routines. The library is organized hierarchically, enabling users to employ the level of abstraction that is most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users. PETSc is a sophisticated set of software tools; as such, for some users it initially has a much steeper learning curve than a simple subroutine library. In particular, for individuals without some computer science background, experience programming in C, C++ or Fortran and experience using a debugger such as gdb or dbx, it may require a significant amount of time to take full advantage of the features that enable efficient software use. However, the power of the PETSc design and the algorithms it incorporates may make the efficient implementation of many application codes simpler than “rolling them” yourself; For many tasks a package such as MATLAB is often the best tool; PETSc is not intended for the classes of problems for which effective MATLAB code can be written. PETSc also has a MATLAB interface, so portions of your code can be written in MATLAB to “try out” the PETSc solvers. The resulting code will not be scalable however because currently MATLAB is inherently not scalable; and PETSc should not be used to attempt to provide a “parallel linear solver” in an otherwise sequential code. Certainly all parts of a previously sequential code need not be parallelized but the matrix generation portion must be parallelized to expect any kind of reasonable performance. Do not expect to generate your matrix sequentially and then “use PETSc” to solve the linear system in parallel. Since PETSc is under continued development, small changes in usage and calling sequences of routines will occur. PETSc is supported; see the web site http://www.mcs.anl.gov/petsc for information on contacting support. A http://www.mcs.anl.gov/petsc/publications may be found a list of publications and web sites that feature work involving PETSc. We welcome any reports of corrections for this document.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

PETSc Users Manual (Rev. 3.5)

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication. PETSc includes an expanding suite of parallel linear, nonlinear equation solvers and time integrators that may be used in application codes written in Fortran, C, C++, Python, and MATLAB (sequential). PETSc provides many of the mechanisms needed within parallel application codes, such as parallel matrix and vector assembly routines. The library is organized hierarchically, enabling users to employ the level of abstraction that is most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users. PETSc is a sophisticated set of software tools; as such, for some users it initially has a much steeper learning curve than a simple subroutine library. In particular, for individuals without some computer science background, experience programming in C, C++ or Fortran and experience using a debugger such as gdb or dbx, it may require a significant amount of time to take full advantage of the features that enable efficient software use. However, the power of the PETSc design and the algorithms it incorporates may make the efficient implementation of many application codes simpler than “rolling them” yourself. ;For many tasks a package such as MATLAB is often the best tool; PETSc is not intended for the classes of problems for which effective MATLAB code can be written. PETSc also has a MATLAB interface, so portions of your code can be written in MATLAB to “try out” the PETSc solvers. The resulting code will not be scalable however because currently MATLAB is inherently not scalable; and PETSc should not be used to attempt to provide a “parallel linear solver” in an otherwise sequential code. Certainly all parts of a previously sequential code need not be parallelized but the matrix generation portion must be parallelized to expect any kind of reasonable performance. Do not expect to generate your matrix sequentially and then “use PETSc” to solve the linear system in parallel. Since PETSc is under continued development, small changes in usage and calling sequences of routines will occur. PETSc is supported; see the web site http://www.mcs.anl.gov/petsc for information on contacting support. A http://www.mcs.anl.gov/petsc/publications may be found a list of publications and web sites that feature work involving PETSc. We welcome any reports of corrections for this document.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

PETSc Users Manual Revision 3.7

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

PETSc Users Manual Revision 3.8

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

PETSc Users Manual (Rev. 3.11)

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

PETSc Users Manual (Rev. 3.13)

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication. PETSc includes an expanding suite of parallel linear solvers, nonlinear solvers, and time integrators that may be used in application codes written in Fortran, C, C++, and Python. PETSc provides many of the mechanisms needed within parallel application codes, such as parallel matrix and vector assembly routines. The library is organized hierarchically, enabling users to employ the level of abstraction that is most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users. PETSc is a sophisticated set of software tools; as such, for some users it initially has a much steeper learning curve than a simple subroutine library. In particular, for individuals without some computer science background, experience programming in C, C++, python, or Fortran and experience using a debugger such as gdb or dbx, it may require a significant amount of time to take full advantage of the features that enable efficient software use. However, the power of the PETSc design and the algorithms it incorporates may make the efficient implementation of many application codes simpler than \rolling them" yourself.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Updating a PWR Simulator in Python

A nuclear reactor is a complicated system that is comprised of many systems and components. In order to fully model a reactor, several approximations and correlations must be used for a real-time simulation. In 1984 as part of a doctoral dissertation at Massachusetts Institute of Technology (MIT), a FORTRAN 77 program was developed to simulate a four-loop, Westinghouse pressurized water reactor (PWR). The program was later called PRISM and extended to include a comprehensive set of features accessible in a DOS-based user interface. This present work seeks to update the original PRISM program for cross platform deployment using the Python language. The goal of this present work is to update and improve a teaching tool for both students and reactor operators. Originally, PRISM was created as part of a PhD project in FORTRAN 77, but the code no longer works readily on modern operating systems. Python was chosen to rewrite the program because of the ease of use of the Python modules including Kivy as well as the portability of the program to various operating systems. This project aims to develop desktop and mobile versions of the software, allowing the user flexibility in choice of platform. This simulator is scheduled to be deployed in time for a live demonstration at the 2016 Annual ANS meeting. The project aims to produce a reactor simulator that will showcase the dynamics of a PWR system in real-time under various conditions. Some potential scenarios include startup conditions, scram operations, or failure conditions such as a break in a coolant leg. The user will be able to induce various failure scenarios and the program will simulate how the reactor will behave. The simulation will include a suite of monitoring functions that will allow automatic systems to attempt to adapt to the changing conditions, e.g., control rod movement. This program will provide an educational resource for anyone learning about nuclear reactor kinetics or dynamics of a reactor system. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Characterizing GPU Energy Usage in Exascale-Ready Portable Science Applications

We characterize the GPU energy usage of two widely adopted exascale-ready applications representing two classes of particle and mesh solvers: (i) QMCPACK, a quantum Monte Carlo package, and (ii) AMReX-Castro, an adaptive mesh astrophysical code. We analyze power, temperature, utilization, and energy traces from double-/single (mixed)-precision benchmarks on NVIDIA’s A100 and H100 and AMD’s MI250X GPUs using queries in NVML and rocm_smi_lib, respectively. We explore application-specific metrics to provide insights on energy vs. performance trade-offs. Our results suggest that mixed-precision energy savings range between 6–25% on QMCPACK and 45% on AMReX-Castro. Also, we found gaps in the AMD tooling used on Frontier GPUs that need to be understood, while query resolutions on NVML have little variability between 1 ms-1 s. Overall, application level knowledge is crucial to define energy-cost/science-benefit opportunities for the codesign of future supercomputer architectures in the post-Moore era.

Godoy, William [ORNL] (ORCID:0000000225905178)↗

DOE OSTI2016

Nebo: An efficient, parallel, and portable domain-specific language for numerically solving partial differential equations

This study presents Nebo, a declarative domain-specific language embedded in C++ for discretizing partial differential equations for transport phenomena on multiple architectures. Application programmers use Nebo to write code that appears sequential but can be run in parallel, without editing the code. Currently Nebo supports single-thread execution, multi-thread execution, and many-core (GPU-based) execution. With single-thread execution, Nebo performs on par with code written by domain experts. With multi-thread execution, Nebo can linearly scale (with roughly 90% efficiency) up to 12 cores, compared to its single-thread execution. Moreover, Nebo’s many-core execution can be over 140x faster than its single-thread execution.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1990

Cobweb/3: A portable implementation

An algorithm is examined for data clustering and incremental concept formation. An overview is given of the Cobweb/3 system and the algorithm on which it is based, as well as the practical details of obtaining and running the system code. The implementation features a flexible user interface which includes a graphical display of the concept hierarchies that the system constructs.

Mckusick, Kathleen↗

DOE OSTI2020

Joint Genome Institute Analysis Workflow Service (JAWS) v2.7

The U.S. Department of Energy Joint Genome Institute (JGI) has developed the JGI Analysis Workflow Service (JAWS) as a distributed framework to run computational workflows across diverse high-performance computing (HPC) and cloud environments. JAWS enhances the reusability, scalability, and robustness of scientific workflows by orchestrating data movement, code execution, and results retrieval across multiple DOE facilities. At its core, JAWS integrates the Cromwell workflow engine to run workflows expressed in the Workflow Description Language (WDL), ensuring portability and interoperability. To provide consistent runtime environments, JAWS employs container technologies such as Shifter, Apptainer, and Docker. Workflow tasks are managed via HTCondor on HPC backends, while Globus ensures secure and efficient data transfer between sites. JAWS is deployed as a multi-site workflow manager across national laboratory computing facilities, with dedicated instances supporting community projects such as the National Microbiome Data Collaborative (NMDC) and KBase. This distributed, service-oriented architecture enables users to "write once, run anywhere," providing scalable, production-quality workflow execution.

Kirton, Edward↗

NASA NTRS1989

Simulating Scenes In Outer Space

Multimission Interactive Picture Planner, MIP, computer program for scientifically accurate and fast, three-dimensional animation of scenes in deep space. Versatile, reasonably comprehensive, and portable, and runs on microcomputers. New techniques developed to perform rapidly calculations and transformations necessary to animate scenes in scientifically accurate three-dimensional space. Written in FORTRAN 77 code. Primarily designed to handle Voyager, Galileo, and Space Telescope. Adapted to handle other missions.

Callahan, John D.↗

NASA NTRS2004

MODEST: A Tool for Geodesy and Astronomy

Features of the JPL VLBI modeling and estimation software "MODEST" are reviewed. Its main advantages include thoroughly documented model physics, portability, and detailed error modeling. Two unique models are included: modeling of source structure and modeling of both spatial and temporal correlations in tropospheric delay noise. History of the code parallels the development of the astrometric and geodetic VLBI technique and the software retains many of the models implemented during its advancement. The code has been traceably maintained since the early 1980s, and will continue to be updated with recent IERS standards. Scripts are being developed to facilitate user-friendly data processing in the era of e-VLBI.

Sovers, Ojars J.↗

DOE OSTI2023

Accelerated kinetic model for global macro stability studies of high-beta fusion reactors

The field reversed configuration (FRC), such as studied in the C-2W experiment at TAE Technologies, is an attractive candidate for realizing a nuclear fusion reactor. In an FRC, kinetic ion effects play the majority role in macroscopic stability, which allows global stability studies to make use of fluid-kinetic hybrid (also referred to as Ohm's law) models wherein ions are treated kinetically while electrons are treated as a fluid. The development and validation of such a hybrid particle-in-cell algorithm in the Exascale Computing Project code WarpX are reported here. Implementation of this model in the WarpX framework benefits from the numerical efficiency of WarpX as well as its scalability on large HPC systems and portability to different architectures. Performance benchmarks of the new algorithm for large, 3-dimensional, full device simulations from the Perlmutter supercomputer are presented. Results of a series of FRC simulations are discussed in which the impact of two-fluid effects on the tilt-mode growth rate was studied. It was observed that, in agreement with previous Hall-MHD studies, two-fluid effects have a stabilizing impact on the tilt mode.

Physics↗

DOE OSTI2018

Speeding up software with VecCore

Portable and efficient vectorization is a significant challenge in large software projects such as GeantV, ROOT, and experiments’ frameworks. Nevertheless, fully exploiting SIMD parallelism will be a required step in order to bridge the widening gap between the needs and availability of computing resouces for data analysis and processing in particle physics. Although there are SIMD libraries that wrap compiler intrinsics into a convenient interface, they do not always support all available architectures, or they only perform well in some of them. The VecCore library was created to address some of these performance and portability issues by providing a unified abstraction layer on top of existing libraries, such as Vc or UME::SIMD. In this article, we discuss VecCore’s programming model for SIMD code and some use cases in HEP software packages such as VecGeom and GeantV.

Amadio, G.↗

DOE OSTI2022

Kubernetes Bindings for the Flux Workload Manager

Flux is a framework for writing resource managers as well as a resource manager for HPC systems. It allows for hierarchical nesting and providing a portable interface for job scheduling across systems. The flux-k8s software provides an interface between Flux and Kubernetes so the two frameworks can use each other's functionality. The code is currently licensed under the LGPL-3.0 License, but we request to re-license the code to promote outside collaboration and community adoption.

Ahn, DongH↗

DOE OSTI2024

KLOKKOS: Automated test generation for performance-portable programs

SAND2024-13830O The KLOKKOS project provides a suite of test generation and validation tools to increase maintainability and portability of Kokkos programs. KLOKKOS, a portmanteau of Klee and Kokkos, is developing an automated test generation for performance-portable programs using Clang/low-level virtual machine (LLVM) and formal methods. KLOKKOS is based on several topics in computer science: the development of symbolic and concolic analysis of LLVM and C++ codes, formal semantics and type theory, C++ templates and language features, LLVM compiler infrastructure, and data parallel primitives. 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

SciDAC↗

NASA NTRS1986

Ah!Help: A generalized on-line help facility

The idea behind the help facility discussed is relatively simple. It is made unique by the fact that it is written in Ada and uses aspects of the language which make information retrieval rapid and simple. Specifically, the DIRECT IO facility allows for random access into the help files. It is necessary to discuss the advantages of random access over sequential access. The mere fact that the program in written in Ada implies a saving in terms of lines of code. This introduces the possibility of eventually adapting the program to run at the microcomputer level, a major consideration . Additionally, since the program uses only standard Ada generics, it is portable to other systems. This is another aspect which must always be taken into consideration in writting any software package in the modern day world of computer programming.

Yu, Wong Nai↗