Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “random access”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-Efficient ReRAM

The wide adoption of deep neural networks has been accompanied by ever-increasing energy and performance demands due to the expensive nature of training them. Additionally, numerous special-purpose architectures have been proposed to accelerate training: both digital and hybrid digital-analog using resistive RAM (ReRAM) crossbars. ReRAM-based accelerators have demonstrated the effectiveness of ReRAM crossbars at performing matrix-vector multiplication operations that are prevalent in training. However, they still suffer from inefficiency due to the use of serial reads and writes for performing the weight gradient and update step. A few works have demonstrated the possibility of performing outer products in crossbars, which can be used to realize the weight gradient and update step without the use of serial reads and writes. However, these works have been limited to low precision operations which are not sufficient for typical training workloads. Moreover, they have been confined to a limited set of training algorithms for fully-connected layers only. To address these limitations, we propose a bit-slicing technique for enhancing the precision of ReRAM-based outer products, which is substantially different from bit-slicing for matrix-vector multiplication only. We incorporate this technique into a crossbar architecture with three variants catered to different training algorithms. To evaluate our design on different types of layers in neural networks (fully-connected, convolutional, etc.) and training algorithms, we develop PANTHER, an ISA-programmable training accelerator with compiler support. Our design can also be integrated into other accelerators in the literature to enhance their efficiency. Our evaluation shows that PANTHER achieves up to 8.02×, 54.21×, and 103× energy reductions as well as 7.16×, 4.02×, and 16× execution time reductions compared to digital accelerators, ReRAM-based accelerators, and GPUs, respectively.

42 ENGINEERING↗
DOE OSTI2021

Application of Markov Chain Monte Carlo Methods for Uncertainty Quantification in Inverse Transport Problems

Determination of the components of a radioactive source/shield system using the system’s radiation signature is of great importance in homeland security, material safeguards, and waste management. Although significant progress has been made toward solving this inverse transport problem in recent years, work remains to be done to quantify the uncertainty in reconstructed results. In this article we apply two Markov chain Monte Carlo (MCMC) approaches, the delayed rejection adaptive metropolis (DRAM) and differential evolution adaptive metropolis (DREAM) methods, to solve inverse problems and quantify uncertainty. The DRAM method uses delayed rejection combined with global adaptation of the proposal covariance matrix. Furthermore, the DREAM method hybridizes MCMC sampling with the differential evolution (DE) algorithm. In numerical test cases, the DRAM and DREAM methods are shown to be superior to a first-order inverse Hessian approach for problems with noisy data and multiple unknown quantities, with DREAM converging to the posterior distribution more quickly than DRAM. The DREAM and DRAM results indicate that a full posterior distribution is required to quantify uncertainty in many inverse transport problems.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Accelerating large scale de novo metagenome assembly using GPUs

Metagenomic workflows involve studying uncultured microorganisms directly from the environment. These environmental samples when processed by modern sequencing machines yield large and complex datasets that exceed the capabilities of metagenomic software. The increasing sizes and complexities of datasets make a strong case for exascale-capable metagenome assemblers. However, the underlying algorithmic motifs are not well suited for GPUs. This poses a challenge since the majority of next-generation supercomputers will rely primarily on GPUs for computation. In this paper we present the first of its kind GPU-Accelerated implementation of the local assembly approach that is an integral part of a widely used large-scale metagenome assembler, MetaHipMer. Local assembly uses algorithms that induce random memory accesses and non-deterministic workloads, which make GPU offloading a challenging task. Our GPU implementation outperforms the CPU version by about 7x and boosts the performance of MetaHipMer by 42% when running on 64 Summit nodes.

Awan, Muaaz Gul↗
DOE OSTI2022

Design-Technology Co-Optimization for NVM-based Neuromorphic Processing Elements

An emerging use-case of machine learning (ML) is to train a model on a high-performance system and deploy the trained model on energy-constrained embedded systems. Neuromorphic hardware platforms, which operate on principles of the biological brain, can significantly lower the energy overhead of a machine learning inference task, making these platforms an attractive solution for embedded ML systems. In this paper, we present a design-technology tradeoff analysis to implement such inference tasks on the processing elements (PEs) of a Non-Volatile Memory (NVM)-based neuromorphic hardware. Through detailed circuit-level simulations at scaled process technology nodes, we show the negative impact of technology scaling on the information-processing latency, which impacts the quality-of-service (QoS) of an embedded ML system. At a finer granularity, the latency inside a PE depends on 1) the delay introduced by parasitic components on its current paths, and 2) the varying delay to sense different resistance states of its NVM cells. Based on these two observations, we make the following three contributions. First, on the technology front, we propose an optimization scheme where the NVM resistance state that takes the longest time to sense is set on current paths having the least delay, and vice versa, reducing the average PE latency, which improves the QoS. Second, on the architecture front, we introduce isolation transistors within each PE to partition it into regions that can be individually power-gated, reducing both latency and energy. Finally, on the system-software front, we propose a mechanism to leverage the proposed technological and architectural enhancements when implementing a machine-learning inference task on neuromorphic PEs of the hardware. Evaluations with a recent neuromorphic hardware architecture show that our proposed design-technology co-optimization approach improves both performance and energy efficiency of machine-learning inference tasks without incurring high cost-per-bit.

42 ENGINEERING↗
DOE OSTI2024

Prospects for Antiferromagnetic Spintronic Devices

This article examines recent advances in the field of antiferromagnetic spintronics from the perspective of potential device realization and applications. We discuss advances in the electrical control of antiferromagnetic order by current-induced spin–orbit torques, particularly in antiferromagnetic thin films interfaced with heavy metals. We also review possible scenarios for using voltage-controlled magnetic anisotropy as a more efficient mechanism to control antiferromagnetic order in thin films with perpendicular magnetic anisotropy. Next, we discuss the problem of electrical detection (i.e., readout) of antiferromagnetic order and highlight recent experimental advances in realizing anomalous Hall and tunneling magnetoresistance effects in thin films and tunnel junctions, respectively, which are based on noncollinear antiferromagnets. Understanding the domain structure and dynamics of antiferromagnetic materials is essential for engineering their properties for applications. For this reason, we then provide an overview of imaging techniques as well as micromagnetic simulation approaches for antiferromagnets. Finally, we present a perspective on potential applications of antiferromagnets for magnetic memory devices, terahertz sources, and detectors.

36 MATERIALS SCIENCE↗
NASA NTRS1972

Fault tolerant data management system

Described in detail are: (1) results obtained in modifying the onboard data management system software to a multiprocessor fault tolerant system; (2) a functional description of the prototype buffer I/O units; (3) description of modification to the ACADC and stimuli generating unit of the DTS; and (4) summaries and conclusions on techniques implemented in the rack and prototype buffers. Also documented is the work done in investigating techniques of high speed (5 Mbps) digital data transmission in the data bus environment. The application considered is a multiport data bus operating with the following constraints: no preferred stations; random bus access by all stations; all stations equally likely to source or sink data; no limit to the number of stations along the bus; no branching of the bus; and no restriction on station placement along the bus.

Gustin, W. M.↗
NASA NTRS1986

Wide field and diffraction limited array camera for SIRTF

The Infrared Array Camera for the space Infrared Telescope Facility (SIRTF/IRAC) is capable of two-dimensional photometry in either a wide field or diffraction-limited mode over the wavelength interval from 2 to 30 microns. Three different two-dimensional direct readout (DRO) array detectors will be used: Band 1-InSb or Si:In (2-5 microns) 128 x 128 pixels, Band 2-Si:Ga (5-18 microns) 64 x 64 pixels, and Band 3-Si:Sb (18-30 microns) 64 x 64 pixels. The hybrid DRO readout architecture has the advantages of low read noise, random pixel access with individual readout rates, and nondestructive readout. The scientific goals of IRAC are discussed, which are the basis for several important requirements and capabilities of the array camera: (1) diffraction-limited resolution from 2-30 microns, (2) use of the maximum unvignetted field of view of SIRTF, (3) simultaneous observations within the three infrared spectral bands, and (4) the capability for broad and narrow bandwidth spectral resolution. A strategy has been developed to minimize the total electronic and environmental noise sources to satisfy the scientific requirements.

Fazio, G. G.↗
NASA NTRS1986

Wide field and diffraction limited array camera for SIRTF

The Infrared Array Camera for the Space Infrared Telescope Facility (SIRTF/IRAC) is capable of two-dimensional photometry in either a wide field or diffraction-limited mode over the wavelength interval from 2 to 30 microns. Three different two-dimensional direct readout (DRO) array detectors are being considered: Band 1-InSb or Si:In (2-5 microns) 128 x 128 pixels, Band 2-Si:Ga (5-18 microns) 64 x 64 pixels, and Band 3-Si:Sb (18-30 microns) 64 x 64 pixels. The hybrid DRO readout architecture has the advantages of low read noise, random pixel access with individual readout rates, and nondestructive readout. The scientific goals of IRAC are discussed, which are the basis for several important requirements and capabilities of the array camera: (1) diffraction-limited resolution from 2-30 microns, (2) use of the maximum unvignetted field of view of SIRTF, (3) simultaneous observations within the three infrared spectral bands, and (4) the capability for broad and narrow bandwidth spectral resolution. A strategy has been developed to minimize the total electronic and environmental noise sources to satisfy the scientific requirements.

Fazio, G. G.↗
NASA NTRS2007

CASPER Version 2.0

CASPER is designed to perform automated planning of interdependent activities within a system subject to requirements, constraints, and limitations on resources. In contradistinction to the traditional concept of batch planning followed by execution, CASPER implements a concept of continuous planning and replanning in response to unanticipated changes (including failures), integrated with execution. Improvements over other, similar software that have been incorporated into CASPER version 2.0 include an enhanced executable interface to facilitate integration with a wide range of execution software systems and supporting software libraries; features to support execution while reasoning about urgency, importance, and impending deadlines; features that enable accommodation to a wide range of computing environments that include various central processing units and random- access-memory capacities; and improved generic time-server and time-control features.

Chien, Steve↗
NASA NTRS2011

FPGA Implementation of Stereo Disparity with High Throughput for Mobility Applications

High speed stereo vision can allow unmanned robotic systems to navigate safely in unstructured terrain, but the computational cost can exceed the capacity of typical embedded CPUs. In this paper, we describe an end-to-end stereo computation co-processing system optimized for fast throughput that has been implemented on a single Virtex 4 LX160 FPGA. This system is capable of operating on images from a 1024 x 768 3CCD (true RGB) camera pair at 15 Hz. Data enters the FPGA directly from the cameras via Camera Link and is rectified, pre-filtered and converted into a disparity image all within the FPGA, incurring no CPU load. Once complete, a rectified image and the final disparity image are read out over the PCI bus, for a bandwidth cost of 68 MB/sec. Within the FPGA there are 4 distinct algorithms: Camera Link capture, Bilinear rectification, Bilateral subtraction pre-filtering and the Sum of Absolute Difference (SAD) disparity. Each module will be described in brief along with the data flow and control logic for the system. The system has been successfully fielded upon the Carnegie Mellon University's National Robotics Engineering Center (NREC) Crusher system during extensive field trials in 2007 and 2008 and is being implemented for other surface mobility systems at JPL.

Random access memory↗
NASA NTRS2011

Integration of the Reconfigurable Self-Healing eDNA Architecture in an Embedded System

In this work we describe the first real world case study for the self-healing eDNA (electronic DNA) architecture by implementing the control and data processing of a Fourier Transform Spectrometer (FTS) on an eDNA prototype. For this purpose the eDNA prototype has been ported from a Xilinx Virtex 5 FPGA to an embedded system consisting of a PowerPC and a Xilinx Virtex 5 FPGA. The FTS instrument features a novel liquid crystal waveguide, which consequently eliminates all moving parts from the instrument. The addition of the eDNA architecture to do the control and data processing has resulted in a highly fault-tolerant FTS instrument. The case study has shown that the early stage prototype of the autonomous self-healing eDNA architecture is expensive in terms of execution time.

Computer architecture↗
NASA NTRS2012

Programmatic Impact of SDRAM SEFI

The Elpida EDS5104(08)ABTA 512Mb SDRAM is examined for programmatic impact of SEE. Use cases for the devices including EDAC and mode register reload are examined. Results indicate some SEE mitigation methods require careful application to achieve system-level benefits, while some event types are essentially mitigated by the application use. In the studied devices MBE and SEFI are identified and investigated as mechanisms requiring special consideration.

Single Event Functionality Interrupt (SEFI)↗
DOE OSTI2017

Random On-Board Pixel Sampling (ROPS) X-Ray Camera

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. Here we first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Generation of random geological models using multi-randomization for machine learning

Generating high-fidelity geological models is essential for advancing machine learning (ML) methods in automated seismic interpretation. For instance, seismic images paired with corresponding fault labels are foundational for ML-based fault detection from seismic migration sections. While several open-access datasets of random geological models exist, open-source tools specifically designed to produce large volumes of such models for ML applications remain scarce. To address this gap, we present RGM (Random Geological Model), an open-source software package for efficiently generating 2D and 3D synthetic geological models tailored for ML workflows. RGM supports the creation of diverse model components, including medium property distributions (P-/S-wave velocities and density), seismic reflectivity images (i.e., synthetic migration sections), relative geological time, and discrete fault attributes such as probability, dip, strike, rake, and displacement. It also accommodates the creation of complex geological features such as salt bodies and unconformities. The model generation algorithm employs a multi-randomization strategy, yielding an effectively infinite-dimensional model space that encompasses a wide range of geological scenarios and associated seismic features. Furthermore, RGM incorporates a method to generate synthetic elastic migration images using analytical elastic reflection coefficients combined with frequency-dependent scaling. This functionality enables the creation of training datasets for ML models that leverage elastic seismic images. RGM is implemented in modern object-oriented Fortran, allowing users to flexibly control statistical parameters governing model variability. We demonstrate the capability, performance, and geological realism of the package through comprehensive 2D and 3D examples.

58 GEOSCIENCES↗
DOE OSTI2025

Spatial quantum-interference landscapes of multi-site-controlled quantum dots coupled to extended photonic cavity modes

Abstract A compact platform to integrate emitters in a cavity-like support is to embed quantum dots (QDs) in a photonic crystal (PhC) structure, making them promising candidates for integrated quantum photonic circuits. The emission properties of QDs can be modified by tailored photonic structures, relying on the Purcell effect or strong light-matter interactions. However, the effects of photonic states on spatial features of exciton emissions in these systems are rarely explored. Such effect is difficult to access due to random positions of self-assembled QDs in PhC structures, and the fact that quantum well excitons’ wavefunctions resemble photonic states in a conventional distributed Bragg reflector cavity system. In this work, we instead observe a spatial signature of exciton emission using site-controlled QDs embedded in PhC cavities. In particular, we observe the detuning-dependent spatial repulsion of the QD exciton emissions by polarized imaging of the micro-photoluminescence, dependent on the controlled QD’s position in a spatially extended photonic pattern. The observed effect arises due to the quantum interference between QD decay channel in a spatially-extended cavity mode. Our findings suggest that integration of site-controlled QDs in tailored photonic structures can enable spatially distributed single-photon sources and photon switches.

Physics↗
NASA NTRS1979

Processing of on-board recorded data for quick analysis of aircraft performance

A system of independent computer programs for the processing of digitized pulse code modulated (PCM) and frequency modulated (FM) data is described. Information is stored in a set of random files and accessed to produce both statistical and graphical output. The software system is designed primarily to present these reports within a twenty-four hour period for quick analysis of the helicopter's performance.

Michaud, N. H.↗
NASA NTRS1992

JPL activities on development of acousto-optic tunable filter imaging spectrometer

Recent activities of JPL in the development of a new type of imaging spectrometers for earth observation and planetary exploration are reported. This instrument uses the acousto-optic tunable filter (AOTF) as high resolution and fast programmable bandpass filter. AOTF operates in the principle of acousto-optic interaction in an anisotropic medium. This filter can be tuned in sequential, random, and multiwavelength access modes, providing observational flexibility. The diffraction process in the filter generates two diffracted monochromatic beams with polarization orthogonal to each other, creating a unique capability to measure both polarimetric and spectral properties of the incoming light simultaneously with a single instrument. The device gives wide wavelength operations with reasonably large throughput. In addition, it is in a compact solid-state structure without moving parts, providing system reliability. These attractive features give promising opportunities to develop a new generation of airborne/spaceborne and ground, real-time, imaging spectrometer systems for remote sensing applications.

Cheng, Li-Jen↗