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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The Pele Simulation Suite for Reacting Flows at Exascale

In this work, we present the Pele suite of software tools for compressible and incompressible reacting flows. The Pele suite leverages several different libraries, notably AMReX and SUNDIALS, to achieve performance portability on heterogeneous computing architectures across the supercomputing landscape. The Pele suite is comprised of PeleC, a compressible reacting flow block-structured adaptive mesh refinement solver, PeleLMeX, a low-Mach number reacting flow block-structured adaptive mesh refinement solver, Pele-Physics, a library for transport, thermodynamics, finite rate chemistry, soot, spray and radiation physics. The objective of this paper is (i) to present the code development efforts necessary to achieve highly effective and scalable applications for exascale machines and (ii) to detail the performance results of the Combustion-Pele project applications on Oak Ridge National Laboratory's Frontier. We show good weak and strong scaling results for both PeleC and PeleLMeX up to more than 50 billion cells on more than 4096 Frontier graphics processing unit nodes. We also present a capability demonstration simulation of a dual-fuel pulse compression ignition engine (six adaptive mesh refinement levels, and 60 billion cells or 2.1 trillion degrees of freedom) on Frontier, to date one of the largest simulations performed on the first exascale-class supercomputer.

adaptive mesh refinement↗
DOE OSTI2024

Enabling Parallel Performance and Portability of Solid Mechanics Simulations Across CPU and GPU Architectures

Efficiently simulating solid mechanics is vital across various engineering applications. As constitutive models grow more complex and simulations scale up in size, harnessing the capabilities of modern computer architectures has become essential for achieving timely results. This paper presents advancements in running parallel simulations of solid mechanics on multi-core CPUs and GPUs using a single-code implementation. This portability is made possible by the C++ matrix and array (MATAR) library, which interfaces with the C++ Kokkos library, enabling the selection of fine-grained parallelism backends (e.g., CUDA, HIP, OpenMP, pthreads, etc.) at compile time. MATAR simplifies the transition from Fortran to C++ and Kokkos, making it easier to modernize legacy solid mechanics codes. We applied this approach to modernize a suite of constitutive models and to demonstrate substantial performance improvements across different computer architectures. This paper includes comparative performance studies using multi-core CPUs along with AMD and NVIDIA GPUs. Results are presented using a hypoelastic–plastic model, a crystal plasticity model, and the viscoplastic self-consistent generalized material model (VPSC-GMM). The results underscore the potential of using the MATAR library and modern computer architectures to accelerate solid mechanics simulations.

Morgan, Nathaniel (ORCID:0000000276118449)↗
DOE OSTI2026

Developments in Performance and Portability of BlockGen

For more than a decade Monte Carlo event generators with the current matrix element algorithms have been used for generating hard scattering events on CPU platforms, with excellent flexibility and good efficiency. While the HL-LHC is approaching and precision requirements are becoming more demanding, many studies have been made to solve the bottleneck in the current Monte Carlo event generator tool chains. The novel BlockGen family of fast matrix element algorithms shown in this report, is one of the new developments that are more suitable for GPU acceleration. We report the development experience of porting BlockGen using Kokkos. Moreover, we discuss the performance of the Kokkos version in comparison with the dedicated GPU version in CUDA.

Bothmann, E. [Gottingen U.]↗
DOE OSTI2025

SPADES (Scalable Parallel Discrete Events Simulation) [SWR-24-99]

SPADES (Solver for PArallel Discrete Event Simulation) is an open-source parallel discrete event simulation (PDES) package built on the AMReX library. Targeted at solving discrete event systems in parallel, this software package aims to be performance portable and scalable on heterogeneous computing architectures, e.g., graphic processing units (GPU). SPADES implements optimistic synchronization with rollback through an implementation of the Time Warp algorithm. An alternative conservative synchronization approach is also implemented using the Lower Bound on Incoming Time Stamp. In our implementation, logical processes are represented as cells in a grid and event messages are represented as particles. SPADES supports various parallel decomposition strategies, including the use of the Message Passing Interface (MPI) and OpenMP threading. All major GPU architectures (e.g., Intel, AMD, NVIDIA) are supported through the use of performance portability functionalities implemented in AMReX. The SPADES software is released in NREL Software Record SWR-24-99 “SPADES (Scalable Parallel Discrete Events Simulation)”.

Henry de Frahan, Marc [National Renewable Energy L↗
DOE OSTI2022

Developments in Performance and Portability for MadGraph5_aMC@NLO

Event generators simulate particle interactions using Monte Carlo techniques, providing the primary connection between experiment and theory in experimental high energy physics. These software packages, which are the first step in the simulation worflow of collider experiments, represent approximately 5 to 20% of the annual WLCG usage for the ATLAS and CMS experiments. With computing architectures becoming more heterogeneous, it is important to ensure that these key software frameworks can be run on future systems, large and small. In this contribution, recent progress on porting and speeding up the Madgraph5_aMC@NLO event generator on hybrid architectures, i.e. CPU with GPU accelerators, is discussed. The main focus of this work has been in the calculation of scattering amplitudes and "matrix elements", which is the computational bottleneck of an event generation application. For physics processes limited to QCD leading order, the code generation toolkit has been expanded to produce matrix element calculations using C++ vector instructions on CPUs and using CUDA for NVidia GPUs, as well as using Alpaka, Kokkos and SYCL for multiple CPU and GPU architectures. Performance is reported in terms of matrix element calculations per time on NVidia, Intel, and AMD devices. The status and outlook for the integration of this work into a production release usable by the LHC experiments, with the same functionalities and very similar user interfaces as the current Fortran version, is also described.

Valassi, Andrea↗
DOE OSTI2018

Constructing Highly Porous Thermoelectric Monoliths with High-Performance and Improved Portability from Solution-Synthesized Shape-Controlled Nanocrystals

Thermoelectricity offers a viable and reliable solution to convert waste heat into electricity. To enhance the performance and portability of thermoelectric materials, the crystal grain and pore structure should be simultaneously manipulated to achieve high electrical conductivity (σ), low thermal conductivity (κ), high figure of merit (zT), and low relative density. However, they cannot be synchronously realized using nanocrystals with uncontrolled domain size and shape as building blocks. Here, we employ solution-synthesized PbS nanocrystals with large grain size, controllable shape and tunable spatial packing to realize the aforementioned structural tuning. In this work, the as-sintered highly porous and well crystalline monolith exhibits high σ, low κ, high zT (1.06 at 838 K) and low relative density (82%). The phonon transport is studied by density functional theory highlighting the crucial role of phonon–pore scattering in reducing κ to enhance zT. Our strategy may benefit thermoelectrics and shed light on other technical fields such as catalysis, gas sensing, photovoltaics, and so forth.

nanocrystal↗
DOE OSTI2026

Entity—Hardware-agnostic Particle-in-cell Code for Plasma Astrophysics. I. Curvilinear Special Relativistic Module

Entity is a new-generation, fully open-source particle-in-cell (PIC) code developed to overcome key limitations in astrophysical plasma modeling, particularly the extreme separation of scales and the performance challenges associated with evolving, GPU-centric computing infrastructures. It achieves hardware-agnostic performance portability across various GPU and CPU architectures using the Kokkos library. Crucially, Entity maintains a high standard for usability, clarity, and customizability, offering a robust and easy-to-use framework for developing new algorithms and grid geometries, which allows extensive control without requiring edits to the core source code. This paper details the core general-coordinate special relativistic module. Entity is the first PIC code designed to solve the Vlasov–Maxwell system in general coordinates, enabling a coordinate-agnostic framework that provides the foundational structure for straightforward extension to arbitrary coordinate geometries. The core methodology achieves numerical stability by solving particle equations of motion in the global orthonormal Cartesian basis, despite using generalized coordinates like Cartesian, axisymmetric spherical, and quasi-spherical grids. Charge conservation is ensured via a specialized current deposition technique using conformal currents. The code exhibits robust scalability and performance portability on major GPU platforms (AMD MI250X, NVIDIA A100, and Intel Max Series), with the 3D particle pusher and the current deposition operating efficiently at about 2 ns per particle per time step. Functionality is validated through a comprehensive suite of standard Cartesian plasma tests and the accurate modeling of relativistic magnetospheres in curvilinear axisymmetric geometries.

Hakobyan, Hayk [Flatiron Institute, New York, NY (↗
DOE OSTI2018

Multithreaded sparse matrix-matrix multiplication for many-core and GPU architectures

Sparse matrix-matrix multiplication is a key kernel that has applications in several domains such as scientific computing and graph analysis. Several algorithms have been studied in the past for this foundational kernel. In this work, we develop parallel algorithms for sparse matrix-matrix multiplication with a focus on performance portability across different high performance computing architectures. The performance of these algorithms depend on the data structures used in them. We compare different types of accumulators in these algorithms and demonstrate the performance difference between these data structures. Furthermore, we develop a meta-algorithm, kkSpGEMM, to choose the right algorithm and data structure based on the characteristics of the problem. We show performance comparisons on three architectures and demonstrate the need for the community to develop two phase sparse matrix-matrix multiplication implementations for efficient reuse of the data structures involved.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Evaluating the performance of portable air filter walls for the James Webb Space Telescope launch campaign

The James Webb Space Telescope (JWST) launched from the Centre Spatial Guyanais (CSG) in December 2021. JWST’s requirements permitted processing in International Organization for Standardization (ISO) Class 7 or better facilities, but CSG was only equipped with ISO Class 8 facilities. To temporarily upgrade the air cleanliness in the Payload Processing Facility, Fueling Hall, and Final Assembly Building Encapsulation Hall, NASA provided two portable High Efficiency Particulate Air (HEPA) and carbon filter walls that were used in each location. The walls were comprised of stacks of two modules high and arranged in push-push configurations as shown to be most effective via Computational Fluid Dynamics simulations of expected floor layouts in each facility. After delivery to NASA’s Goddard Space Flight Center in 2020, the walls underwent initial verification measurements inside a cleanroom and validation testing in an uncontrolled area to quantify their improvement of air cleanliness and particle and molecular fallout. Validation testing showed improvements of 83-99% for airborne particle counts, 79-91% for particle fallout, and 50-90% for molecular fallout. The particle improvements were applied to the contamination budget analysis that tracked current and predicted future cleanliness against End-of-Life requirements for JWST’s critical surfaces. At CSG, the walls successfully maintained an ISO Class 7 environment or better within their envelope in each location, despite their presence in ISO Class 8 facilities with dense integration operations.

HEPA, Contamination Control, Filtration↗
NASA NTRS2022

Evaluating the Performance of Portable Air Filter Walls for the James Webb Space Telescope Launch Campaign

The James Webb Space Telescope (JWST) launched from the Centre Spatial Guyanais (CSG) in December 2021. JWST’s requirements permitted processing in International Organization for Standardization (ISO) Class 7 or better facilities, but CSG was only equipped with ISO Class 8 facilities. To temporarily upgrade the air cleanliness in the Payload Processing Facility, Fueling Hall, and Final Assembly Building Encapsulation Hall, NASA provided two portable High Efficiency Particulate Air (HEPA) and carbon filter walls that were used in each location. The walls were comprised of stacks of two modules high and arranged in push-push configurations as shown to be most effective via Computational Fluid Dynamics simulations of expected floor layouts in each facility. After delivery to NASA’s Goddard Space Flight Center in 2020, the walls underwent initial verification measurements inside a cleanroom and validation testing in an uncontrolled area to quantify their improvement of air cleanliness and particle and molecular fallout. Validation testing showed improvements of 83-99% for airborne particle counts, 79-91% for particle fallout, and 50-90% for molecular fallout. The particle improvements were applied to the contamination budget analysis that tracked current and predicted future cleanliness against End-of-Life requirements for JWST’s critical surfaces. At CSG, the walls successfully maintained an ISO Class 7 environment or better within their envelope in each location, despite their presence in ISO Class 8 facilities with dense integration operations.

HEPA, Contamination Control, Filtration↗
NASA NTRS1998

Performance Analysis and Portability of the PLUM Load Balancing System

The ability to dynamically adapt an unstructured mesh is a powerful tool for solving computational problems with evolving physical features; however, an efficient parallel implementation is rather difficult. To address this problem, we have developed PLUM, an automatic portable framework for performing adaptive numerical computations in a message-passing environment. PLUM requires that all data be globally redistributed after each mesh adaption to achieve load balance. We present an algorithm for minimizing this remapping overhead by guaranteeing an optimal processor reassignment. We also show that the data redistribution cost can be significantly reduced by applying our heuristic processor reassignment algorithm to the default mapping of the parallel partitioner. Portability is examined by comparing performance on a SP2, an Origin2000, and a T3E. Results show that PLUM can be successfully ported to different platforms without any code modifications.

Oliker, Leonid↗
DOE OSTI2024

Toward Automated Detection of Portability Bugs in Kokkos Parallel Programs

Performance-portable programming frameworks provide abstractions for parallel execution to allow easily porting an application to multiple backend programming models, such as CUDA, HIP, and OpenMP. However, programs may still have portability bugs that manifest only on specific backends. Traditional testing is ineffective in discovering these bugs, as it would require concrete execution on all supported hardware configurations for a potentially infinite set of inputs. To mitigate this issue, we focused on a specific programming framework, Kokkos, and identified several categories of common portability bugs. We then developed Klokkos, a static analysis approach based on symbolic execution that can run on commodity hardware, before execution on supercomputers. As a proof-of-concept, we ran Klokkos on examples encoding the identified bugs. Our results show that Klokkos is effective, efficient, and precise: it detected all the considered bugs, quickly, and without any false positives. Although preliminary, our results motivate further research and development in this direction.

Kale, Vivek↗
DOE OSTI2025

Enabling Multireference Calculations on Multimetallic Systems with Graphic Processing Units

Modeling multimetallic systems efficiently enables faster prediction of desirable chemical properties and the design of new materials. This work describes an initial implementation for performing multireference wave function method localized active-space self-consistent field (LASSCF) calculations through the use of multiple graphics processing units (GPUs) to accelerate time-to-solution. Density fitting is leveraged to reduce memory requirements, and we demonstrate the ability to fully utilize multi-GPU compute nodes. Performance improvements of 5–10x in total application runtime were observed in LASSCF calculations for multimetallic catalyst systems up to 1200 AOs and an active space of (22e,40o) using up to four NVIDIA A100 GPUs. Furthermore, written with performance portability in mind, a comparable performance is also observed in early runs on the Aurora exascale system using Intel Max Series GPUs.

Algorithms↗