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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A Survey on the Expanding Scope and Interdisciplinary Opportunities for Processing-in-Memory Techniques

Processing-in-Memory (PIM) is emerging as a practical path to overcome the limitations of traditional von Neumann architectures. At its core, PIM systems implement computing primitives such as logic operations and multiply-accumulate acceleration through compute-in-memory, near-memory processing, or hybrid designs. The role of memory cells varies widely across technologies, acting as inputs, outputs, or analog accumulators through bit-lines and sense amplifiers. This diversity creates trade-offs in precision, bandwidth, latency, and programmability, making it difficult to build a unified understanding on the progress of the field. In this survey, we organize recent advances of PIM into three areas. First, we discuss the progress on the architectural optimizations of PIM and its integration with both DRAM and emerging non-volatile memories. Second, we examine how PIM is being used to accelerate key computing domains, including generative AI workloads and high-performance kernels, along with new approaches. Third, we highlight the growing adoption of PIM in computational sciences, where it is being applied to solve interdisciplinary problems such as genome analysis, mRNA quantification, mass spectrometry, quantum circuit simulation, wave modeling, and secure computation. Finally, we synthesize the major challenges that continue to slow PIM adoption, including manufacturing constraints, power delivery, thermal reliability, data consistency, runtime and memory-management coordination, and the difficulty of building portable software abstractions without sacrificing commercial viability. This work provides an updated, structured perspective on PIM’s potential across computing and computational sciences and the barriers that must be solved for it to reach its full impact.

Asifuzzaman, Kazi [Oak Ridge National Laboratory (↗
DOE OSTI2024

RAP: Resource-aware Automated GPU Sharing for Multi-GPU Recommendation Model Training and Input Preprocessing

Ensuring high-quality recommendations for newly onboarded users requires the continuous retraining of Deep Learning Recommendation Models (DLRMs) with freshly generated data. To serve the online DLRM retraining, existing solutions use hundreds of CPU computing nodes designated for input preprocessing, causing significant power consumption that surpasses even the power usage of GPU trainers. To this end, we propose RAP, an end-to-end DLRM training framework that supports Resource-aware Automated GPU sharing for DLRM input Preprocessing and Training. The core idea of RAP is to accurately capture the remaining GPU computing resources during DLRM training for input preprocessing, achieving superior training efficiency without requiring additional resources. Specifically, RAP utilizes a co-running cost model to efficiently assess the costs of various input preprocessing operations, and it implements a resource-aware horizontal fusion technique that adaptively merges smaller kernels according to GPU availability, circumventing any interference with DLRM training. In addition, RAP leverages a heuristic searching algorithm that jointly optimizes both the input preprocessing graph mapping and the co-running schedule to maximize the end-to-end DLRM training throughput. The comprehensive evaluation shows that RAP achieves 78.3× speedup on average over CPU-based DLRM input preprocessing frameworks. In addition, the end-to-end training throughput of RAP is only 2.04% lower than the ideal case, which has no input preprocessing overhead.

Wang, Zheng↗
DOE OSTI2022

Microfluidic Uranium Microspheres Production for TRISO and Advanced Fuel Concepts

The purpose of this project was to expand existing internal gelation sol-gel capabilities at PNNL to explore producing uranium dioxide spheres for potential use as fuel kernels in next generation Tri-isotropic (TRISO) particle fuel. This project expands on previous sol-gel efforts at PNNL by (1) increasing the size regime of sphere production from the micro-fluidic range to the milli-fluidic range, and (2) producing uranium spheres. The approach involved first scaling up the channel size of the fluidic system to the millimeter range, with radiation safety considerations in mind; testing and demonstration on non-radioactive surrogate material, cerium oxide; then transitioning to uranium production and finally optimizing system parameters. Commercially available fluidic chips in the desired size range were could not be found, therefore the project designed and fabricated a T-junction with 1mm channels for droplet production. Because the production process is temperature sensitive, prior efforts have involved performing droplet production in a lab freezer. To reduce radiological waste and footprint, two alternative chilling methods were explored using aluminum thermal beads as a chill bath and a custom aluminum block fit to reagent reservoir sizes. Both were successful in the cerium tests, however the aluminum block design outperformed the thermal bead bath and was further adapted for the radiological test and production run in the Radiochemical Processing Laboratory (RPL). Gelation trials were performed to determine an acceptable range of feed solution parameters for the uranium dioxide gels, characterized by R-values, which is determined by the ratio of uranium nitrate to Hexamethylenetetramine (HMTA)/urea in the feed solution. R-values ranging from 1.6-2 were examined in the gelation trials, with only the 1.8 condition being tested in production. The project was successful in demonstrating a proof of concept design for producing uranium dioxide spheres, however further optimization is needed to dial in production parameters and improve sphere quality and homogeneity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

SST-GPU: A Scalable SST GPU Component for Performance Modeling and Profiling

Programmable accelerators have become commonplace in modern computing systems. Advances in programming models and the availability of unprecedented amounts of data have created a space for massively parallel accelerators capable of maintaining context for thousands of concurrent threads resident on-chip. These threads are grouped and interleaved on a cycle-by-cycle basis among several massively parallel computing cores. One path for the design of future supercomputers relies on an ability to model the performance of these massively parallel cores at scale. The SST framework has been proven to scale up to run simulations containing tens of thousands of nodes. A previous report described the initial integration of the open-source, execution-driven GPU simulator, GPGPU-Sim, into the SST framework. This report discusses the results of the integration and how to use the new GPU component in SST. It also provides examples of what it can be used to analyze and a correlation study showing how closely the execution matches that of a Nvidia V100 GPU when running kernels and mini-apps.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Determination of Average Burnup in AGR-3/4 Compacts 1-4 and 7-4

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program third and fourth irradiation experiments (AGR-3/4), originally planned as separate tests, were combined in one test train for irradiation in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). The irradiation test began on December 14, 2011, and ended on April 12, 2014 (Collin 2016). The originally planned AGR-3 and AGR-4 irradiation experiments were both focused on obtaining data on fission product transport to support the improvement of modeling. The AGR-3 experimental plan was focused on gaseous and metallic fission product release from the kernels and diffusion in the coatings during irradiation and post-irradiation safety testing. The AGR-4 experimental plan was focused on diffusivities and sorptivities in the compact matrix and reactor graphite. These two goals were combined in the AGR-3/4 irradiation, which consisted of 12 independently monitored capsules that each contained four AGR-3/4 compacts in a single stack surrounded by an inner ring of matrix or graphite and an outer ring of graphite. Two capsule types were used: a standard capsule and a so-called fuel body, in which the outer graphite ring included a floor and cap that fully enclosed the fuel. The fuel body design supported post-irradiation safety testing of the intact fuel and ring assembly to provide data on fission product transport and release from the matrix and graphite at accident temperatures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A statistical model to predict ignition probability

Ignition capability is a critical design constraint for aeronautical gas turbines. However the current trend toward overall lean burn is detrimental to the engine ignition and relight and the ignition system must be adapted to ensure a fast and reliable light-round in all circumstances. As ignition is a stochastic phenomenon, the optimization of an ignition system requires to build ignition probability maps, which is difficult and costly with either experiment or numerical simulation as both require many tests. Here, this work proposes a model to predict the ignition probability map, knowing only flow statistics in non-reacting conditions, i.e., with only one test. The originality of the model is to construct statistics of the flame kernel trajectory, which are then combined with local flow indicators to evaluate the ignition probability at the considered sparking location. Application to a swirled burner operated in premixed, non-premixed and spray combustion modes illustrates the model concepts and demonstrates its ability to recover the experimental ignition map with good accuracy.

42 ENGINEERING↗
DOE OSTI2024

Integrated photonic encoder for low power and high-speed image processing

Abstract Modern lens designs are capable of resolving greater than 10 gigapixels, while advances in camera frame-rate and hyperspectral imaging have made data acquisition rates of Terapixel/second a real possibility. The main bottlenecks preventing such high data-rate systems are power consumption and data storage. In this work, we show that analog photonic encoders could address this challenge, enabling high-speed image compression using orders-of-magnitude lower power than digital electronics. Our approach relies on a silicon-photonics front-end to compress raw image data, foregoing energy-intensive image conditioning and reducing data storage requirements. The compression scheme uses a passive disordered photonic structure to perform kernel-type random projections of the raw image data with minimal power consumption and low latency. A back-end neural network can then reconstruct the original images with structural similarity exceeding 90%. This scheme has the potential to process data streams exceeding Terapixel/second using less than 100 fJ/pixel, providing a path to ultra-high-resolution data and image acquisition systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Towards On-Chip Learning for Low Latency Reasoning with End-to-End Synthesis

The Software Defined Architectures (SODA) Synthesizer is an open-source compiler-based tool able to automatically generate domain-specialized systems targeting Application-Specific Integrated Circuits (ASICs) or Field Programmable Gate Arrays (FPGAs) starting from high-level programming. SODA is composed of a frontend, SODA-OPT, which leverages the multilevel intermediate representation (MLIR) framework to interface with productive programming tools (e.g., machine learning frame-works), identify kernels suitable for acceleration, and perform high-level optimizations, and of a state-of-the-art high-level synthesis backend, Bambu from the PandA framework, to generate custom accelerators. One specific application of the SODA Synthesizer is the generation of accelerators to enable ultra-low latency inference and control on autonomous systems for scientific discovery (e.g., electron microscopes, sensors in particle accelerators, etc.). This paper provides an overview of the flow in the context of the generation of accelerators for edge processing to be integrated in transmission electron microscopy (TEM) devices, focusing on use cases from precision material synthesis. We show the tool in action with an example of design space exploration for inference on reconfigurable devices with a conventional deep neural network model (LeNet). Finally, we discuss the research directions and opportunities enabled by SODA in the area of autonomous control for scientific experimental workflows.

Castellana, Vito G.↗
DOE OSTI2026

CORE-BFS: Communication-Optimized REctangular-partitioned BFS Achieving 160.845 TeraTEPS on Frontier Supercomputer

Distributed Breadth-First Search (BFS) is fundamental to many large-scale graph applications, but its performance on parallel systems is often limited by high communication overhead. This paper presents CORE-BFS, an extremely scalable GPU-based BFS implementation that introduces a unique rectangular 2D partitioning-based design for Frontier supercomputer. To further improve performance, we propose four key optimizations: (1) Rectangular 2D-partition specific data formats that use two compressed row and one compressed column status array bitmaps combined with a Double Compressed Sparse Row (DCSR) format per partition, reducing memory footprint and inter-rank traffic; (2) Adaptive frontier & communication strategy that unifies top-down and bottom-up traversal on the rectangular layout, uses lazy synchronization in top-down levels, and switches variants based on frontier size to minimize communication overhead; (3) Frontier-split degree-aware update that maps frontier vertices to thread-centric, wavefront-centric, and block-centric kernels based on their degree to improve GPU utilization and memory coalescing; (4) Row-reduction pipeline that overlaps bottom-up adjacency list processing with row-wise bitmap reduction to hide inter-rank latency. Together, these techniques increase parallelism while reducing memory and communication overhead. On the Graph500 benchmark, CORE - BFS scales up to 9,248 Frontier nodes with scale-42 graphs and reaches 160.845 TTEPS, delivering a 5.42 × speedup over our previous Frontier implementation.

Yang, Haoshen [Rutgers University]↗
DOE OSTI2020

Radial Deconsolidation and Leach-Burn-Leach of AGR-3/4 Compact 1-4 and 10-4

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program third and fourth irradiation experiments (AGR-3/4), originally planned as separate tests, were combined in one test train for irradiation in the Advanced Test Reactor at Idaho National Laboratory (INL). The irradiation test began on December 14, 2011 and ended on April 12, 2014 (Collin 2016). The originally planned AGR-3 and AGR-4 irradiation experiments were both focused on obtaining data on fission product transport to support the improvement of modeling. The AGR-3 experimental plan was focused on gaseous and metallic fission product release from the kernels and diffusion in the coatings during irradiation and postirradiation safety testing. The AGR-4 experimental plan was focused on diffusivities and sorptivities in the compact matrix and reactor graphite (Petti et al. 2005). These two goals were combined in the AGR-3/4 irradiation, which consisted of twelve independently monitored capsules that each contained four AGR-3/4 compacts in a single stack surrounded by an inner ring of matrix or graphite and an outer ring of graphite. There were two capsule types: a standard capsule and a “fuel body”, in which the outer graphite ring included a floor and cap that fully enclosed the fuel (Stempien et al. 2018a). The fuel body design supported post-irradiation safety testing of the intact fuel and ring assembly to provide data on fission product transport and release from matrix and graphite at accident temperatures (Demkowicz 2017).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Radial Deconsolidation and Leach-Burn-Leach of AGR-3/4 Compacts 8-4 and 7-4

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program’s third and fourth irradiation experiments (AGR-3/4), originally planned as separate tests, were combined into one test train for irradiation in the Advanced Test Reactor at Idaho National Laboratory (INL). The irradiation test began on December 14, 2011, and ended on April 12, 2014 (Collin 2016). The originally planned AGR-3 and AGR-4 irradiation experiments were both to be focused on obtaining fission product transport data to support improvements in modeling. The AGR-3 experimental plan was focused on gaseous and metallic fission product release from the kernels and diffusion in the coatings during irradiation and postirradiation safety testing. The AGR-4 experimental plan was focused on diffusivities and sorptivities in the compact matrix and reactor graphite (Petti et al. 2005). These goals were combined in the AGR-3/4 irradiation experiment, which consisted of twelve independently monitored capsules that each contained four AGR-3/4 compacts in a single stack surrounded by an inner ring of matrix or graphite and an outer ring of graphite. There were two capsule types: a standard capsule and a fuel body, in which the outer graphite ring included a floor and cap to fully enclose the fuel (Stempien et al. 2018a). The fuel body design supported post-irradiation safety testing of the intact fuel and ring assembly to obtain data on fission product transport and release from matrix and graphite at accident temperatures (Demkowicz 2017).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Radial Deconsolidation and Leach-Burn-Leach of AGR-3/4 Compacts 1-3, 4-3, 10-1, and 10-2

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program’s third and fourth irradiation experiments (AGR-3/4), originally planned as separate tests, were combined into one test train for irradiation in the Advanced Test Reactor at Idaho National Laboratory (INL). The irradiation test began on December 14, 2011 and ended on April 12, 2014 (Collin 2016). The originally planned AGR-3 and AGR-4 irradiation experiments were both focused on obtaining data on fission product transport to support modeling improvement. The AGR-3 experimental plan was focused on gaseous and metallic fission product release from the kernels and diffusion in the coatings during irradiation and post-irradiation safety testing. The AGR-4 experimental plan was focused on diffusivities and sorptivities in the compact matrix and reactor graphite (Petti et al. 2005). These two goals were combined in the AGR-3/4 irradiation, which consisted of twelve independently monitored capsules that each contained four AGR-3/4 compacts in a single stack surrounded by an inner ring of matrix or graphite and an outer ring of graphite. There were two capsule types: a standard capsule and a fuel body in which the outer graphite ring included a floor and cap that fully enclosed the fuel (Stempien et al. 2018a). The fuel body design supported post-irradiation safety testing of the intact fuel and ring assembly to provide data on fission product transport and release from matrix and graphite at accident temperatures (Demkowicz 2017)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Design and implementation of dynamic I/O control scheme for large scale distributed file systems

In this paper, we have analyzed the input/output (I/O) activities of Cori, which is a high-performance computing system at the National Energy Research Scientific Computing Center at Lawrence Berkeley National Laboratory. Our analysis results indicate that most users do not adjust storage configurations but rather use the default settings. In addition, owing to the interference from many applications running simultaneously, the performance varies based on the system status. To configure file systems autonomously in complex environments, we developed DCA-IO, a dynamic distributed file system configuration adjustment algorithm that utilizes the system log information to adjust storage configurations automatically. Our scheme aims to improve the application performance and avoid interference from other applications without user intervention. Moreover, DCA-IO uses the existing system logs and does not require code modifications, an additional library, or user intervention. To demonstrate the effectiveness of DCA-IO, we performed experiments using I/O kernels of real applications in both an isolated small-sized Lustre environment and Cori. Our experimental results shows that our scheme can improve the performance of HPC applications by up to 263% with the default Lustre configuration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Unraveling the impact of initial choices and in-loop interventions on learning dynamics in autonomous scanning probe microscopy

The current focus in Autonomous Experimentation (AE) is on developing robust workflows to conduct the AE effectively. This entails the need for well-defined approaches to guide the AE process, including strategies for hyperparameter tuning and high-level human interventions within the workflow loop. This paper presents a comprehensive analysis of the influence of initial experimental conditions and in-loop interventions on the learning dynamics of Deep Kernel Learning (DKL) within the realm of AE in scanning probe microscopy. We explore the concept of the “seed effect,” where the initial experiment setup has a substantial impact on the subsequent learning trajectory. Additionally, we introduce an approach of the seed point interventions in AE allowing the operator to influence the exploration process. Using a dataset from Piezoresponse Force Microscopy on PbTiO 3 thin films, we illustrate the impact of the “seed effect” and in-loop seed interventions on the effectiveness of DKL in predicting material properties. The study highlights the importance of initial choices and adaptive interventions in optimizing learning rates and enhancing the efficiency of automated material characterization. This work offers valuable insights into designing more robust and effective AE workflows in microscopy with potential applications across various characterization techniques.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Estimation of distributions via multilevel Monte Carlo with stratified sampling

We design and implement a novel algorithm for computing a multilevel Monte Carlo (MLMC) estimator of the joint cumulative distribution function (CDF) of a vector-valued quantity of interest in problems with random input parameters and initial conditions. Our approach combines MLMC with stratified sampling of the input sample space by replacing standard Monte Carlo at each level with stratified Monte Carlo initialized with proportionally allocated samples. We show that the resulting stratified MLMC (sMLMC) algorithm is more efficient than its standard MLMC counterpart due to the additional variance reduction provided by the stratification of the random parameter's domain, especially at the coarsest levels. Additional computational cost savings are obtained by smoothing the indicator function with a Gaussian kernel, which proves to be an efficient and robust alternative to recently developed polynomial-based techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Exploring temporal community evolution: algorithmic approaches and parallel optimization for dynamic community detection

Abstract Dynamic (temporal) graphs are a convenient mathematical abstraction for many practical complex systems including social contacts, business transactions, and computer communications. Community discovery is an extensively used graph analysis kernel with rich literature for static graphs. However, community discovery in a dynamic setting is challenging for two specific reasons. Firstly, the notion of temporal community lacks a widely accepted formalization, and only limited work exists on understanding how communities emerge over time. Secondly, the added temporal dimension along with the sheer size of modern graph data necessitates new scalable algorithms. In this paper, we investigate how communities evolve over time based on several graph metrics under a temporal formalization. We compare six different algorithmic approaches for dynamic community detection for their quality and runtime. We identify that a vertex-centric (local) optimization method works as efficiently as the classical modularity-based methods. To its advantage, such local computation allows for the efficient design of parallel algorithms without incurring a significant parallel overhead. Based on this insight, we design a shared-memory parallel algorithm DyComPar , which demonstrates between 4 and 18 fold speed-up on a multi-core machine with 20 threads, for several real-world and synthetic graphs from different domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Coupled SAM/Griffin Model of a Reference Fluoride-Salt-Cooled High-Temperature Reactor for Multi-Physics Simulations

A multi-physics coupled simulation model of a reference pebble bed fluoride-salt-cooled high-temperature reactor (PB-FHR) has been developed with SAM and Griffin computer codes for transient safety analysis. The reference problem of a prototypical reactor design serves as the foundation for the U.S. NRC (Nuclear Regulatory Commission) to verify the adequacy of computer codes and evaluation models for specific reactor types. In this work, the previously developed SAM model for PB-FHR primary loop has been updated for the coupled simulation. The updated SAM PB-FHR model includes a 2-D axial symmetric core region and external core components in 0-D/1-D. In addition to the primary loop, a detailed model of the RCCS (reactor cavity cooling system) is added. The 2-D and 1-D domains are tightly coupled using the single-solve approach developed in SAM. In the pebble bed region, the SAM multiscale explicit pebble model is applied to calculate the pebble and TRISO fuel kernel temperatures. The Griffin model used in this work is based on a model developed at Idaho National Laboratory in collaboration with the U.S. NRC. The Griffin neutronics model and SAM thermal hydraulics model is coupled with the Comprehensive Reactor Analysis Bundle (CRAB or alternately BlueCRAB) application. Both steady-state and transient scenarios are simulated to demonstrate the model's suitability for multi-physics simulations of PB-FHR transients.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗