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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 541 records · Page 30

Assessment of Multi-Scale Thermal-Hydraulic Codes and Models for DNB Challenge Problem Applications

The objectives of this milestone work are to assess the improved capabilities of the multi-scale thermal-hydraulic (T/H) codes and models developed by the Consortium for Advanced Simulation of Light Water Reactors (CASL) for Departure from Nucleate Boiling (DNB) Challenge Problem (CP), in accordance with the DNB CP implementation plan. The multi-scale models can range from fine mesh Computational Fluid Dynamics (CFD) simulation of flow field surrounding a fuel rod to a full core modeling of a Pressurized Water Reactor (PWR). The assessments are performed based on the CASL subchannel code COBRA-TF (CTF) and the CFD code Hydra-TH. Significant improvements have been achieved on the CASL multi-scale T/H code and modeling capabilities based on the CTF subchannel code and the Hydra-TH CFD code in the past year for DNB CP applications. The improvements are reflected in the new transient modeling for the Reactivity Insertion Accident (RIA) DNB predictions and full assembly modeling using the CTF code and its processor, as well as the rod bundle modeling for single-phase flow and heat transfer simulations using the Hydra-TH code, the pre-processor for mesh generation and the post-processor for data visualization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An Integrated Framework for Memory-Centric Analysis: From Trace Collection to Co-Design

The memory wall phenomenon—where advances in processor performance significantly outpace those in memory subsystems—poses a fundamental challenge for contemporary computing systems. In memory-bound applications, memory subsystem behavior dominates performance, yet existing analysis approaches present significant limitations: detailed microarchitectural simulators require days to weeks to simulate modest workloads; hardware performance counters provide only aggregate statistics that obscure temporal and spatial access patterns; and scaled simulation approaches face challenges in capturing certain behaviors that emerge at larger scales. These limitations reflect a processor-centric design philosophy increasingly misaligned with memory-bound workloads where detailed understanding of memory access patterns, cache hierarchy interactions, and contention is critical for effective optimization. This paper presents an integrated framework for memory-centric analysis that enables effective hardware-software co-design. We describe practical trace collection techniques, including hardware-assisted processor tracing with minimal overhead and portable software-based instrumentation with statistical sampling. We present multi-perspective analysis methods that examine memory behavior from temporal, sequential, spatial, and relational viewpoints, revealing distinct optimization opportunities invisible in aggregate metrics. We detail an architectural modeling framework that uses sampled traces with temporal interpolation and confidence-based filtering to evaluate cache and memory configurations. Evaluation on representative benchmarks demonstrates that this framework achieves practical accuracy (L2 cache errors of 2.64\%, confidence-filtered L3 errors of 9.92\%, bandwidth errors of 7.33\%) while providing substantial speedup (26.8×) over cycle-accurate simulation, enabling rapid design space exploration. We demonstrate how this integrated framework enables systematic identification of both hardware optimizations (memory controller tuning, bank partitioning, NUMA configuration) and software optimizations (data layout restructuring, prefetching strategies, memory-aware scheduling). Through this comprehensive treatment of the memory-centric analysis pipeline—from trace collection through architectural modeling to co-design application—we provide researchers and practitioners with practical techniques for addressing memory bottlenecks in contemporary computing systems.

Gajaria, Dhruv Mayur↗

Recall Performance for Content-Addressable Memory Using Adiabatic Quantum Optimization

A content-addressable memory (CAM) stores key-value associations such that the key is recalled by providing its associated value. While CAM recall is traditionally performed using recurrent neural network models, we show how to solve this problem using adiabatic quantum optimization. Our approach maps the recurrent neural network to a commercially available quantum processing unit by taking advantage of the common underlying Ising spin model. We then assess the accuracy of the quantum processor to store key-value associations by quantifying recall performance against an ensemble of problem sets. We observe that different learning rules from the neural network community influence recall accuracy but performance appears to be limited by potential noise in the processor. The strong connection established between quantum processors and neural network problems supports the growing intersection of these two ideas.

97 MATHEMATICS AND COMPUTING↗

PATCHWORK: A Multipatch Infrastructure for Multiphysics/Multiscale/Multiframe Fluid Simulations

Here, we present a "multipatch" infrastructure for the numerical simulation of fluid problems in which subregions require different grid scales, different grid geometries, different physical equations, or different reference frames. Its key element is a sophisticated client–router–server framework for efficiently linking processors supporting different regions ("patches") that must exchange boundary data. This infrastructure may be used with a wide variety of fluid dynamics codes; the only requirement is that their primary dependent variables be the same in all patches, e.g., fluid mass density, internal energy density, and velocity. Its structure can accommodate either Newtonian or relativistic dynamics. The overhead imposed by this system is both problem and computer cluster architecture dependent. Compared to a conventional simulation using the same number of cells and processors employed on a problem not requiring multipatch methods, the cell update per processor rate decreases by an amount that can range from negligible to a factor of a few; however, even in these problems, the infrastructure can permit substantial decreases in the total number of cell updates required.

97 MATHEMATICS AND COMPUTING↗

An Approach to Enhance pnetCDF Performance in Environmental Modeling Applications

I/O has been considered as a bottleneck in parallel applications. The software package, pnetCDF which works with parallel file systems, was developed to address this issue and provide parallel I/O capability. This study examines the performance of a novel approach which performs data aggregation along either row or column dimension of the spatial domain, and then applies the pnetCDF parallel I/O paradigm. The test was done with three different domain sizes which represents small, moderately large and large data domains, using a small scale Community Multi-scale Air Quality model (CMAQ) mocked up code. The examination includes comparing I/O performance with traditional serial I/O technique, straight application of pnetCDF, and the data aggregation along row and column dimension before applying pnetCDF. After the comparison, “optimal” I/O configurations for this new novel approach were quantified. Data aggregation along the row dimension (pnetCDFcr) works better than along the column dimension (pnetCDFcc) although it may perform slightly worse than straight the pnetCDF method with a small number of processors. When the number of processors becomes larger, pnetCDFcr out performs pnetCDF significantly. If the number of processors keeps increasing, pnetCDF reaches a point that the performance is even worse than the serial I/O technique. This new approach has also been tested on a real application where it performs two times better than the straight pnetCDF paradigm.

I/O↗

Method and apparatus of parallel computing with simultaneously operating stream prefetching and list prefetching engines

A prefetch system improves a performance of a parallel computing system. The parallel computing system includes a plurality of computing nodes. A computing node includes at least one processor and at least one memory device. The prefetch system includes at least one stream prefetch engine and at least one list prefetch engine. The prefetch system operates those engines simultaneously. After the at least one processor issues a command, the prefetch system passes the command to a stream prefetch engine and a list prefetch engine. The prefetch system operates the stream prefetch engine and the list prefetch engine to prefetch data to be needed in subsequent clock cycles in the processor in response to the passed command.

97 MATHEMATICS AND COMPUTING↗

Radio-nuclide mixture identification using medium energy resolution detectors

According to one embodiment, a method for identifying radio-nuclides includes receiving spectral data, extracting a feature set from the spectral data comparable to a plurality of templates in a template library, and using a branch and bound method to determine a probable template match based on the feature set and templates in the template library. In another embodiment, a device for identifying unknown radio-nuclides includes a processor, a multi-channel analyzer, and a memory operatively coupled to the processor, the memory having computer readable code stored thereon. The computer readable code is configured, when executed by the processor, to receive spectral data, to extract a feature set from the spectral data comparable to a plurality of templates in a template library, and to use a branch and bound method to determine a probable template match based on the feature set and templates in the template library.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant

System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.

47 OTHER INSTRUMENTATION↗

Architectural Techniques For Managing Non-volatile Caches

As chip power dissipation becomes a critical challenge in scaling processor performance, computer architects are forced to fundamentally rethink the design of modern processors and hence, the chip-design industry is now at a major inflection point in its hardware roadmap. The high leakage power and low density of SRAM poses serious obstacles in its use for designing large on-chip caches and for this reason, researchers are exploring non-volatile memory (NVM) devices, such as spin torque transfer RAM, phase change RAM and resistive RAM. However, since NVMs are not strictly superior to SRAM, effective architectural techniques are required for making them a universal memory solution. This book discusses techniques for designing processor caches using NVM devices. It presents algorithms and architectures for improving their energy efficiency, performance and lifetime. It also provides both qualitative and quantitative evaluation to help the reader gain insights and motivate them to explore further. This book will be highly useful for beginners as well as veterans in computer architecture, chip designers, product managers and technical marketing professionals.

Cache architecture↗

A Survey of Architectural Techniques For Improving Cache Power Efficiency

Modern processors are using increasingly larger sized on-chip caches. Also, with each CMOS technology generation, there has been a significant increase in their leakage energy consumption. For this reason, cache power management has become a crucial research issue in modern processor design. To address this challenge and also meet the goals of sustainable computing, researchers have proposed several techniques for improving energy efficiency of cache architectures. This paper surveys recent architectural techniques for improving cache power efficiency and also presents a classification of these techniques based on their characteristics. For providing an application perspective, this paper also reviews several real-world processor chips that employ cache energy saving techniques. The aim of this survey is to enable engineers and researchers to get insights into the techniques for improving cache power efficiency and motivate them to invent novel solutions for enabling low-power operation of caches.

architectural techniques↗

Multiprocessor switch with selective pairing

System, method and computer program product for a multiprocessing system to offer selective pairing of processor cores for increased processing reliability. A selective pairing facility is provided that selectively connects, i.e., pairs, multiple microprocessor or processor cores to provide one highly reliable thread (or thread group). Each paired microprocessor or processor cores that provide one highly reliable thread for high-reliability connect with a system components such as a memory "nest" (or memory hierarchy), an optional system controller, and optional interrupt controller, optional I/O or peripheral devices, etc. The memory nest is attached to a selective pairing facility via a switch or a bus

97 MATHEMATICS AND COMPUTING↗

Computing an operating parameter of a unified power flow controller

A Unified Power Flow Controller described herein comprises a sensor that outputs at least one sensed condition, a processor that receives the at least one sensed condition, a memory that comprises control logic that is executable by the processor; and power electronics that comprise power storage, wherein the processor causes the power electronics to selectively cause the power storage to act as one of a power generator or a load based at least in part upon the at least one sensed condition output by the sensor and the control logic, and wherein at least one operating parameter of the power electronics is designed to facilitate maximal transmittal of electrical power generated at a variable power generation system to a grid system while meeting power constraints set forth by the electrical power grid.

97 MATHEMATICS AND COMPUTING↗

System-wide power management control via clock distribution network

An apparatus, method and computer program product for automatically controlling power dissipation of a parallel computing system that includes a plurality of processors. A computing device issues a command to the parallel computing system. A clock pulse-width modulator encodes the command in a system clock signal to be distributed to the plurality of processors. The plurality of processors in the parallel computing system receive the system clock signal including the encoded command, and adjusts power dissipation according to the encoded command.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimization and Parallelization of the Thermal-Hydraulic Sub-channel Code CTF for High-Fidelity Multi-physics Applications

This paper describes major improvements to the computational infrastructure of the CTF sub-channel code so that full-core sub-channel-resolved simulations can now be performed in much shorter run-times, either in stand-alone mode or as part of coupled-code multi-physics calculations. These improvements support the goals of the Department Of Energy (DOE) Consortium for Advanced Simulations of Light Water (CASL) Energy Innovation Hub to develop high fidelity multi-physics simulation tools for nuclear energy design and analysis. A set of serial code optimizations--including fixing computational inefficiencies, optimizing the numerical approach, and making smarter data storage choices--are first described and shown to reduce both execution time and memory usage by about a factor of ten. Next, a Single Program Multiple Data (SPMD) parallelization strategy targeting distributed memory Multiple Instruction Multiple Data (MIMD) platforms and utilizing domain-decomposition is presented. In this approach, data communication between processors is accomplished by inserting standard MPI calls at strategic points in the code. The domain decomposition approach implemented assigns one MPI process to each fuel assembly, with each domain being represented by its own CTF input file. The creation of CTF input files, both for serial and parallel runs, is also fully automated through use of a pre-processor utility that takes a greatly reduced set of user input over the traditional CTF input file. To run CTF in parallel, two additional libraries are currently needed; MPI, for inter-processor message passing, and the Parallel Extensible Toolkit for Scientific Computation (PETSc), which is leveraged to solve the global pressure matrix in parallel. Results presented include a set of testing and verification calculations and performance tests assessing parallel scaling characteristics up to a full core, sub-channel-resolved model of Watts Bar Unit 1 under hot full-power conditions (193 17x17 assemblies, ~56,000 pins, ~59,000 sub-channels, ~2.8 million thermal-hydraulic (TH) control volumes). Results demonstrate that CTF can now perform full core analysis (not previously possible due to excessively long runtimes and memory requirements) on the order of 20 minutes. This new capability is not only useful to standalone CTF users, but is also being leveraged in support of coupled code multi-physics calculations being done in the CASL program.

COBRA-TF↗

Domi

Domi (Greek for "structure") is a Trilinos package that provides support for multi-dimensional data arrays distributed over multiple processors of a high performance computing system. The software supports data arrays of arbitrary number of dimensions mapped to a multi-dimensional grid of processors. Domi provides local access to the data, as well as the ability to compute global quantities such as norms, maxima and minima. Data arrays can be constructed with boundary and communication padding, necessary for finite difference algorithms, and provides high-level methods for communicating data between processors to update these buffers. The distributed maps and vectors in Domi can be converted to the equivalent data structures in Epetra and Tpetra (both of which assume unstructured data), using view semantics when appropriate, for use with other Trilinos solvers.

Spotz, William F.↗

Single bus star connected reluctance drive and method

A system and methods for operating a switched reluctance machine includes a controller, an inverter connected to the controller and to the switched reluctance machine, a hysteresis control connected to the controller and to the inverter, a set of sensors connected to the switched reluctance machine and to the controller, the switched reluctance machine further including a set of phases the controller further comprising a processor and a memory connected to the processor, wherein the processor programmed to execute a control process and a generation process.

33 ADVANCED PROPULSION SYSTEMS↗

System and method for memory allocation in a multiclass memory system

A system for memory allocation in a multiclass memory system includes a processor coupleable to a plurality of memories sharing a unified memory address space, and a library store to store a library of software functions. The processor identifies a type of a data structure in response to a memory allocation function call to the library for allocating memory to the data structure. Using the library, the processor allocates portions of the data structure among multiple memories of the multiclass memory system based on the type of the data structure.

97 MATHEMATICS AND COMPUTING↗

Active non-volatile memory post-processing

A computing node includes an active Non-Volatile Random Access Memory (NVRAM) component which includes memory and a sub-processor component. The memory is to store data chunks received from a processor core, the data chunks comprising metadata indicating a type of post-processing to be performed on data within the data chunks. The sub-processor component is to perform post-processing of said data chunks based on said metadata.

97 MATHEMATICS AND COMPUTING↗