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All sources NASA NTRS DOE OSTI

DOE OSTI2019

Development and Verification of a Numerical Library for Solving Global Terrestrial Multiphysics Problems

Abstract Current generation Land Surface Models (LSMs) routinely simulate many nonlinear multiphysics processes. The complexity of future generation LSMs is expected to increase as critical new biophysical and biogeochemical processes are incorporated. Current generation LSMs have several shortcomings including the lack of robust numerical methods to solve discretized equations, monolithic software design that hinders testing of a process representation in isolation from other components, and absence of a flexible coupling framework to solve tightly coupled multiphysics problems. While the LSMs community vigorously evaluates the accuracy of the conceptual model to represent reality (validation), the accuracy of the numerical implementation of the conceptual model (verification) is seldom examined. Method of Manufactured Solutions is a technique for verifying complex codes when analytical solutions are unavailable. In this work, we present a stand‐alone, open source numerical library for solving global terrestrial multiphysics processes that includes a flexible coupling framework. Robust numerical solution for linear and nonlinear equations is provided via the Portable, Extensible Toolkit for Scientific Computation library. We verify the numerical library using Method of Manufactured Solutions for a range of problems comprising single and multiphysics steady state problems that are applied in one or multiple physical domains. This work provides an example of incorporating code verification as an integral part of Land Surface Model development activities.

58 GEOSCIENCES↗

DOE OSTI2021

PUMIPic: A mesh-based approach to unstructured mesh Particle-In-Cell on GPUs

Unstructured mesh particle-in-cell, PIC, simulations executing on the current and next generation of massively parallel systems require new methods for both the mesh and particles to achieve performance and scalability on GPUs. The traditional approach to implementing PIC simulations defines data structures and algorithms in terms of particles with a full copy of the unstructured mesh on every process. To effectively scale the unstructured mesh and particles, mesh-based PIC uses the unstructured mesh as the predominant data structure with the particles stored in terms of the mesh entities. Here, this paper details the PUMIPic library, a framework for developing efficient and performance-portable mesh-based PIC simulations on GPU systems. A pseudo physics simulation based on a five-dimensional gyro-kinetic code for modeling plasma physics is used to examine the performance of PUMIPic. Scaling studies of the unstructured mesh partition and number of particles are performed up to 4096 nodes of the Summit system at Oak Ridge National Laboratory. The studies show that mesh-based PIC can utilize a partitioned mesh and maintain scaling up to system limitations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Reducing the bulk of the bulk synchronous parallel model

For over two decades the dominant means for enabling portable performance of computational science and engineering applications on parallel processing architectures has been the bulk-synchronous parallel programming (BSP) model. Code developers, motivated by performance considerations to minimize the number of messages transmitted, have typically pursued a strategy of aggregating message data into fewer, larger messages. Emerging and future high-performance architectures, especially those seen as targeting Exascale capabilities, provide motivation and capabilities for revisiting this approach. In this paper we explore alternative configurations within the context of a large-scale complex multi-physics application and a proxy that represents its behavior, presenting results that demonstrate some important advantages as the number of processors increases in scale.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

miniWeather

The code “miniWeather” solves the 2-D Euler equations with a Finite-Volume method on a regular Cartesian grid with Runge-Kutta time stepping, 4th-order hypervisocisty, and 4th-order spatial accuracy. The code is primarily a parallel programming training mini application in Fortran, C, and C++ with MPI, OpenMP, OpenMP offload, OpenACC, and C++ portability approaches. It can also serve as a mini application for acceptance testing for new machines and compilers for both functionality and performance.

Norman, MatthewR↗

DOE OSTI2024

MUPPET: An automated OpenMP mutation testing framework for performance optimization

MUPPET is a tool for OpenMP programs that identifies program modifications, called mutations, aimed at improving program performance. Existing performance optimization techniques, including profiling-based and auto-tuning techniques, fail to indicate program modifications at the source level thus preventing their portability across compilers. MUPPET aims to help HPC developers reason about performance defects and missed opportunities to improve performance at the source code level.

Parasyris, Konstantinos↗

DOE OSTI2025

HydraGNN v4.0

The new version of HydraGNN v4.0 provides additional core capabilities, such as: Inclusion of multi-body atomistic cluster expansion MACE, polarizable atom interaction neural network PAINN, and equivariant principal neighborhood aggregation (PNAEq) among the message passing layers supported -Inclusion of graph transformers to directly model long-range interactions between nodes that are distant in the graph topology Integration of graph transformers with message passing layers by combining the graph embedding generated by the two mechanisms, which allows for an improved expressivity of the HydraGNN architecture Improved re-implementation of multi-task learning (MTL) to allow its use for stabilized training across imbalanced, multi-source, multi-fidelity data Introduction of multi-task parallelism, a newly proposed type of model parallelism specifically for MTL architectures, which allows to dispatch different output decoding heads to different GPU devices Integration of multi-task parallelism with pre-existing distributed data parallelism to enable a 2D parallelization for distributed training Improved portability of the distributed training across Intel GPUs, which has been testes on ALCF exascale supercomputer Aurora Inclusion of 2-level fine-grained energy profilers portable across NVIDIA, AMD, and Intel GPUs to monitor the power and energy consumption associated with different functions executed by the HydraGNN code during data pre-load and training Restructuring of previous examples and inclusion of new sets of examples to illustrate the download, preprocess, and training of HydraGNN models on new large-scale open-source datasets for atomistic materials modeling (e.g., Alexandria, Transition1x, OMat24, OMol25)

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗

DOE OSTI2014

Achieving Robustness to Uncertainty for Financial Decision-making

This report investigates the concept of robustness analysis to support financial decision-making. Financial models, that forecast future stock returns or market conditions, depend on assumptions that might be unwarranted and variables that might exhibit large fluctuations from their last-known values. The analysis of robustness explores these sources of uncertainty, and recommends model settings such that the forecasts used for decision-making are as insensitive as possible to the uncertainty. A proof-of-concept is presented with the Capital Asset Pricing Model. The robustness of model predictions is assessed using info-gap decision theory. Info-gaps are models of uncertainty that express the “distance,” or gap of information, between what is known and what needs to be known in order to support the decision. The analysis yields a description of worst-case stock returns as a function of increasing gaps in our knowledge. The analyst can then decide on the best course of action by trading-off worst-case performance with “risk”, which is how much uncertainty they think needs to be accommodated in the future. The report also discusses the Graphical User Interface, developed using the MATLAB® programming environment, such that the user can control the analysis through an easy-to-navigate interface. Three directions of future work are identified to enhance the present software. First, the code should be re-written using the Python scientific programming software. This change will achieve greater cross-platform compatibility, better portability, allow for a more professional appearance, and render it independent from a commercial license, which MATLAB® requires. Second, a capability should be developed to allow users to quickly implement and analyze their own models. This will facilitate application of the software to the evaluation of proprietary financial models. The third enhancement proposed is to add the ability to evaluate multiple models simultaneously. When two models reflect past data with similar accuracy, the more robust of the two is preferable for decision-making because its predictions are, by definition, less sensitive to the uncertainty.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Copy Hiding Application Interface

CHAI is a light-weight framework which abstracts the automated movement of data (e.g. to/from Host/Device) via RAJA like performance portability programming model constructs. It can be viewed as a utility framework and an adjunct to FAJA (A Performance Portability Framework). Performance Portability is a technique that abstracts the complexities of modern Heterogeneous Architectures while allowing the original program to undergo incremental minimally invasive code changes in order to adapt to the newer architectures.

Jones, Holger↗

DOE OSTI2026

TChem-atm (v2.0.0): scalable performance-portable multiphase atmospheric chemistry

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high-performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. In a proof-of-concept integration with the particle-resolved model PartMC, TChem-atm reproduces the existing PartMC–CAMP implementation within solver tolerances and delivers substantial GPU speedups, especially for large particle populations. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. TChem-atm enables performance-portable execution across CPUs and GPUs, though optimal efficiency may require modest architecture-specific tuning (e.g., team and vector sizes), with up to a twofold improvement on the NVIDIA H100. It directly supports sectional and particle-resolved host models, while modal aerosol schemes require minor adaptation to provide particle-scale quantities such as representative diameters. By enabling chemically detailed, multiphase simulations with performance portability and host-model flexibility, TChem-atm facilitates the incorporation of advanced chemistry into atmospheric models.

Díaz-Ibarra, Oscar Homero [Sandia National Laborat↗

NASA NTRS1984

Minimum-distance Problems in Protocol Design

Codes for use in personal computer file transfer as control characters, when only upper-case ASCII can be used to avoid dependence on unique machine features and promote portability. If ten control functions are needed, a number used in at least one protocol, a subset of ten upper-case ASCII characters with good distance properties is sought. The control functions form themselves naturally into three groups, one of two functions (ACK and NAK) and two of four. The aim is to make ACK and NAK as antipodal as possible (distance 6), make the distances within each of the other groups as large as possible (4), and otherwise have as few 2's in the distance table as possible, recognizing that only even distances can occur. The minimum and an assignment that attains the minimum are found. The code is essentially unique. The analogous problem for two groups of three control functions and one group of four is also solved.

Posner, E. C.↗

NASA NTRS1998

Charon Message-Passing Toolkit for Scientific Computations

The Charon toolkit for piecemeal development of high-efficiency parallel programs for scientific computing is described. The portable toolkit, callable from C and Fortran, provides flexible domain decompositions and high-level distributed constructs for easy translation of serial legacy code or design to distributed environments. Gradual tuning can subsequently be applied to obtain high performance, possibly by using explicit message passing. Charon also features general structured communications that support stencil-based computations with complex recurrences. Through the separation of partitioning and distribution, the toolkit can also be used for blocking of uni-processor code, and for debugging of parallel algorithms on serial machines. An elaborate review of recent parallelization aids is presented to highlight the need for a toolkit like Charon. Some performance results of parallelizing the NAS Parallel Benchmark SP program using Charon are given, showing good scalability.

VanderWijngaart, Rob F.↗

NASA NTRS1998

Charon Message-Passing Toolkit for Scientific Computations

VanderWijngarrt, Rob F.↗

DOE OSTI2025

ChatHPC: Building the Foundations for a Productive and Trustworthy AI-Assisted HPC Ecosystem

ChatHPC democratizes large language models for the high-performance computing (HPC) community by providing the infrastructure, ecosystem, and knowledge needed to apply modern generative AI technologies to rapidly create specific capabilities for critical HPC components while using relatively modest computational resources. Our divide-and-conquer approach focuses on creating a collection of reliable, highly specialized, and optimized AI assistants for HPC based on the cost-effective and fast Code Llama fine-tuning processes and expert supervision. We target major components of the HPC software stack, including programming models, runtimes, I/O, tooling, and math libraries. Thanks to AI, ChatHPC provides a more productive HPC ecosystem by boosting important tasks related to portability, parallelization, optimization, scalability, and instrumentation, among others. With relatively small datasets (on the order of KB), the AI assistants, which are created in a few minutes by using one node with two NVIDIA H100 GPUs and the ChatHPC library, can create new capabilities with Meta’s 7-billion parameter Code Llama base model to produce high-quality software with a level of trustworthiness of up to 90% higher than the 1.8-trillion parameter OpenAI ChatGPT-4o model for critical programming tasks in the HPC software stack.

Young, Aaron [ORNL] (ORCID:0000000254484667)↗

NASA NTRS2000

Automatic Generation of OpenMP Directives and Its Application to Computational Fluid Dynamics Codes

The shared-memory programming model is a very effective way to achieve parallelism on shared memory parallel computers. As great progress was made in hardware and software technologies, performance of parallel programs with compiler directives has demonstrated large improvement. The introduction of OpenMP directives, the industrial standard for shared-memory programming, has minimized the issue of portability. In this study, we have extended CAPTools, a computer-aided parallelization toolkit, to automatically generate OpenMP-based parallel programs with nominal user assistance. We outline techniques used in the implementation of the tool and discuss the application of this tool on the NAS Parallel Benchmarks and several computational fluid dynamics codes. This work demonstrates the great potential of using the tool to quickly port parallel programs and also achieve good performance that exceeds some of the commercial tools.

Yan, Jerry↗

DOE OSTI2022

Portability for GPU-accelerated molecular docking applications for cloud and HPC: can portable compiler directives provide performance across all platforms?

High-throughput structure-based screening of drug-like molecules has become a common tool in biomedical research. Recently, acceleration with graphics processing units (GPUs) has provided a large performance boost for molecular docking programs. Both cloud and high-performance computing (HPC) resources have been used for large screens with molecular docking programs; while NVIDIA GPUs have dominated cloud and HPC resources, new vendors such as AMD and Intel are now entering the field, creating the problem of software portability across different GPUs. Ideally, software productivity could be maximized with portable programming models that are able to maintain high performance across architectures. While in many cases compiler directives have been used as an easy way to offload parallel regions of a CPU-based program to a GPU accelerator, they may also be an attractive programming model for providing portability across different GPU vendors, in which case the porting process may proceed in the reverse direction: from low-level, architecture-specific code to higher-level directive-based abstractions. MiniMDock is a new mini-application (miniapp) designed to capture the essential computational kernels found in molecular docking calculations, such as are used in phar-maceutical drug discovery efforts, in order to test different solutions for porting across GPU architectures. Here we extend MiniMDock to GPU offloading with OpenMP directives, and compare to performance of kernels using CUDA and HIP on NVIDIA and AMD GPUs, respectively, as well as across different compilers, exploring performance bottlenecks. We document this reverse-porting process, from highly optimized device code to a higher-level version using directives, compare code structure, and describe barriers that were overcome in this effort.

Thavappiragasam, Mathialakan↗

DOE OSTI2015

INteroperable Tools for Rapid dEveloPment of compatible Discretizations

Intrepid is a library of interoperable tools for compatible discretizations of Partial Differential Equations (PDEs).Current version is intended primarily for application developers who want to reuse large parts of their existing code frameworks such as I/O, data structures, assembly routines, etc. while gaining access to advanced discretization capabilities provided by Intrepid. Intrepid2 is a performance portable version of Intrepid, that requires all input data types be Kokkos (performance-portability library from Trillions) multidimentional arrays. this restriction is needed for providing performance portability in Intrepid2 and break backward-compatibility of Intrepid.

Source record↗

NASA NTRS1999

An Efficient Objective Analysis System for Parallel Computers

A new atmospheric objective analysis system designed for parallel computers will be described. The system can produce a global analysis (on a 1 X 1 lat-lon grid with 18 levels of heights and winds and 10 levels of moisture) using 120,000 observations in 17 minutes on 32 CPUs (SGI Origin 2000). No special parallel code is needed (e.g. MPI or multitasking) and the 32 CPUs do not have to be on the same platform. The system is totally portable and can run on several different architectures at once. In addition, the system can easily scale up to 100 or more CPUS. This will allow for much higher resolution and significant increases in input data. The system scales linearly as the number of observations and the number of grid points. The cost overhead in going from 1 to 32 CPUs is 18%. In addition, the analysis results are identical regardless of the number of processors used. This system has all the characteristics of optimal interpolation, combining detailed instrument and first guess error statistics to produce the best estimate of the atmospheric state. Static tests with a 2 X 2.5 resolution version of this system showed it's analysis increments are comparable to the latest NASA operational system including maintenance of mass-wind balance. Results from several months of cycling test in the Goddard EOS Data Assimilation System (GEOS DAS) show this new analysis retains the same level of agreement between the first guess and observations (O-F statistics) as the current operational system.

Stobie, J.↗

NASA NTRS1999

An Efficient Objective Analysis System for Parallel Computers

A new objective analysis system designed for parallel computers will be described. The system can produce a global analysis (on a 2 x 2.5 lat-lon grid with 20 levels of heights and winds and 10 levels of moisture) using 120,000 observations in less than 3 minutes on 32 CPUs (SGI Origin 2000). No special parallel code is needed (e.g. MPI or multitasking) and the 32 CPUs do not have to be on the same platform. The system Ls totally portable and can run on -several different architectures at once. In addition, the system can easily scale up to 100 or more CPUS. This will allow for much higher resolution and significant increases in input data. The system scales linearly as the number of observations and the number of grid points. The cost overhead in going from I to 32 CPus is 18%. in addition, the analysis results are identical regardless of the number of processors used. T'his system has all the characteristics of optimal interpolation, combining detailed instrument and first guess error statistics to produce the best estimate of the atmospheric state. It also includes a new quality control (buddy check) system. Static tests with the system showed it's analysis increments are comparable to the latest NASA operational system including maintenance of mass-wind balance. Results from a 2-month cycling test in the Goddard EOS Data Assimilation System (GEOS DAS) show this new analysis retains the same level of agreement between the first guess and observations (0-F statistics) throughout the entire two months.

Stobie, James G.↗