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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Secondary Frequency Control for Reconfigurable Interconnecting Microgrids

Microgrids and microgrid technologies offer an operations and control framework for realizing the needed aggregation of a growing share of distributed energy resources. As the number of microgrids increases, so will the incentive to interconnect them, leading to a combinatorial growth of potential operating states. At the same time, their growing complexity nudges interconnected microgrids conceptually closer to balancing authorities in the bulk power system. This paper focuses on secondary frequency control and leverages the conceptual similarity between balancing authorities and interconnected microgrids to adopt an automatic generation control design with some adaptations. Frequency control and restoration is demonstrated via several use-cases with switching and reconfiguration events.

Schweitzer, Eran↗
NASA NTRS1992

Reconfigurable optical interconnection network for multimode optical fiber sensor arrays

A single-source, single-detector architecture has been developed to implement a reconfigurable optical interconnection network multimode optical fiber sensor arrays. The network was realized by integrating LiNbO3 electrooptic (EO) gratings working at the Raman Na regime and a massive fan-out waveguide hologram (WH) working at the Bragg regime onto a multimode glass waveguide. The glass waveguide utilized the whole substrate as a guiding medium. A 1-to-59 massive waveguide fan-out was demonstrated using a WH operating at 514 nm. Measured diffraction efficiency of 59 percent was experimentally confirmed. Reconfigurability of the interconnection was carried out by generating an EO grating through an externally applied electric field. Unlike conventional single-mode integrated optical devices, the guided mode demonstrated has an azimuthal symmetry in mode profile which is the same as that of a fiber mode.

Chen, R. T.↗
NASA NTRS1994

Reconfigurable optical interconnections via dynamic computer-generated holograms

A system is proposed for optically providing one-to-many irregular interconnections, and strength-adjustable many-to-many irregular interconnections which may be provided with strengths (weights) w(sub ij) using multiple laser beams which address multiple holograms and means for combining the beams modified by the holograms to form multiple interconnections, such as a cross-bar switching network. The optical means for interconnection is based on entering a series of complex computer-generated holograms on an electrically addressed spatial light modulator for real-time reconfigurations, thus providing flexibility for interconnection networks for largescale practical use. By employing multiple sources and holograms, the number of interconnection patterns achieved is increased greatly.

Liu, Hua-Kuang↗
NASA NTRS1996

Reconfigurable Optical Interconnections Via Dynamic Computer-Generated Holograms

A system is presented for optically providing one-to-many irregular interconnections, and strength-adjustable many-to-many irregular interconnections which may be provided with strengths (weights) w(sub ij) using multiple laser beams which address multiple holograms and means for combining the beams modified by the holograms to form multiple interconnections, such as a cross-bar switching network. The optical means for interconnection is based on entering a series of complex computer-generated holograms on an electrically addressed spatial light modulator for real-time reconfigurations, thus providing flexibility for interconnection networks for large-scale practical use. By employing multiple sources and holograms, the number of interconnection patterns achieved is increased greatly.

Liu, Hua-Kuang↗
DOE OSTI2020

Phase I Final Technical Report on Energy-Efficient Reconfigurable Universal Accelerator Interconnect

It is well known that application specific computing systems, optimally designed and configured for a given workload, offer much higher energy-efficiency and throughput than general purpose systems. In modern computing systems, heterogeneous computing systems have emerged that exploit the energy and performance benefits of combining various different domain-specific processor architectures. Application domains such as high-performance computing and machine learning now process terabyte-sized data sets, requiring enormous processing and memory resources. These applications have very high-power consumption due to bottlenecks in the electrical interconnection between processing units. This project aims to reduce both communication energy and latency by integrating universally available accelerators with silicon photonics. It also aims to increase system throughput by exploiting emerging technologies in silicon photonic reconfigurable interconnects; this will allow the system to balance itself in real time to accommodate changes in workloads and data flows.

2.5D/3D integration↗
NASA NTRS1989

Characterization of robotics parallel algorithms and mapping onto a reconfigurable SIMD machine

The kinematics, dynamics, Jacobian, and their corresponding inverse computations are six essential problems in the control of robot manipulators. Efficient parallel algorithms for these computations are discussed and analyzed. Their characteristics are identified and a scheme on the mapping of these algorithms to a reconfigurable parallel architecture is presented. Based on the characteristics including type of parallelism, degree of parallelism, uniformity of the operations, fundamental operations, data dependencies, and communication requirement, it is shown that most of the algorithms for robotic computations possess highly regular properties and some common structures, especially the linear recursive structure. Moreover, they are well-suited to be implemented on a single-instruction-stream multiple-data-stream (SIMD) computer with reconfigurable interconnection network. The model of a reconfigurable dual network SIMD machine with internal direct feedback is introduced. A systematic procedure internal direct feedback is introduced. A systematic procedure to map these computations to the proposed machine is presented. A new scheduling problem for SIMD machines is investigated and a heuristic algorithm, called neighborhood scheduling, that reorders the processing sequence of subtasks to reduce the communication time is described. Mapping results of a benchmark algorithm are illustrated and discussed.

Lee, C. S. G.↗
NASA NTRS1990

Optical computing and image processing using photorefractive gallium arsenide

Recent experimental results on matrix-vector multiplication and multiple four-wave mixing using GaAs are presented. Attention is given to a simple concept of using two overlapping holograms in GaAs to do two matrix-vector multiplication processes operating in parallel with a common input vector. This concept can be used to construct high-speed, high-capacity, reconfigurable interconnection and multiplexing modules, important for optical computing and neural-network applications.

Cheng, Li-Jen↗
NASA NTRS1991

Multiple-mode reconfigurable electro-optic switching network for optical fiber sensor array

This paper reports the first switching network compatible with multimode fibers. A one-to-many cascaded reconfigurable interconnection was built. A thin glass substrate was used as the guiding medium which provides not only higher coupling efficiency from multimode fiber to waveguide but also better tolerance of phase-matching conditions. Involvement of a total-internal-reflection hologram and multimode waveguide eliminates interface problems between fibers and waveguides. The DCG polymer graft has proven to be reliable from -180 C to +200 C. Survivability of such an electrooptic system in harsh environments is further ensured. LiNbO3 was chosen as the E-O material because of its stability at high temperatures (phase-transition temperature of more than 1000 C) and maturity of E-O device technology. Further theoretical calculation was conducted to provide the optimal interaction length and device capacitance.

Chen, Ray T.↗
DOE OSTI2021

Freely scalable and reconfigurable optical hardware for deep learning

Abstract As deep neural network (DNN) models grow ever-larger, they can achieve higher accuracy and solve more complex problems. This trend has been enabled by an increase in available compute power; however, efforts to continue to scale electronic processors are impeded by the costs of communication, thermal management, power delivery and clocking. To improve scalability, we propose a digital optical neural network (DONN) with intralayer optical interconnects and reconfigurable input values. The path-length-independence of optical energy consumption enables information locality between a transmitter and a large number of arbitrarily arranged receivers, which allows greater flexibility in architecture design to circumvent scaling limitations. In a proof-of-concept experiment, we demonstrate optical multicast in the classification of 500 MNIST images with a 3-layer, fully-connected network. We also analyze the energy consumption of the DONN and find that digital optical data transfer is beneficial over electronics when the spacing of computational units is on the order of $$>10\,\upmu $$ > 10 μ m.

42 ENGINEERING↗
DOE OSTI2021

Machine-learning-aided cognitive reconfiguration for flexible-bandwidth HPC and data center networks [Invited]

This paper proposes a machine-learning (ML)-aided cognitive approach for effective bandwidth reconfiguration in optically interconnected datacenter/high-performance computing (HPC) systems. The proposed approach relies on a Hyper-X-like architecture augmented with flexible-bandwidth photonic interconnections at large scales using a hierarchical intra/inter-POD photonic switching layout. We first formulate the problem of the connectivity graph and routing scheme optimization as a mixed-integer linear programming model. A two-phase heuristic algorithm and a joint optimization approach are devised to solve the problem with low time complexity. Then, we propose an ML-based end-to-end performance estimator design to assist the network control plane with intelligent decision making for bandwidth reconfiguration. Numerical simulations using traffic distribution profiles extracted from HPC applications traces as well as random traffic matrices verify the accuracy performance of the ML design estimator ( < <#comment/> 9 % <#comment/> error) and demonstrate up to 5 × <#comment/> throughput gain from the proposed approach compared with the baseline Hyper-X network using fixed all-to-all intra/inter-portable data center interconnects.

Chen, Xiaoliang (ORCID:0000000278056237)↗
NASA NTRS2006

Self-Adaptive System based on Field Programmable Gate Array for Extreme Temperature Electronics

In this work, we report the implementation of a self-adaptive system using a field programmable gate array (FPGA) and data converters. The self-adaptive system can autonomously recover the lost functionality of a reconfigurable analog array (RAA) integrated circuit (IC) [3]. Both the RAA IC and the self-adaptive system are operating in extreme temperatures (from 120 C down to -180 C). The RAA IC consists of reconfigurable analog blocks interconnected by several switches and programmable by bias voltages. It implements filters/amplifiers with bandwidth up to 20 MHz. The self-adaptive system controls the RAA IC and is realized on Commercial-Off-The-Shelf (COTS) parts. It implements a basic compensation algorithm that corrects a RAA IC in less than a few milliseconds. Experimental results for the cold temperature environment (down to -180 C) demonstrate the feasibility of this approach.

adaptive hardwares↗
DOE OSTI2022

Performance trade-offs in reconfigurable networks for HPC

Designing efficient interconnects to support high-bandwidth and low-latency communication is critical toward realizing high performance computing (HPC) and data center (DC) systems in the exascale era. At extreme computing scales, providing the requisite bandwidth through overprovisioning becomes impractical. These challenges have motivated studies exploring reconfigurable network architectures that can adapt to traffic patterns at runtime using optical circuit switching. Despite the plethora of proposed architectures, surprisingly little is known about the relative performances and trade-offs among different reconfigurable network designs. We aim to bridge this gap by tackling two key issues in reconfigurable network design. First, we study how cost, power consumption, network performance, and scalability vary based on optical circuit switch (OCS) placement in the physical topology. Specifically, we consider two classes of reconfigurable architectures: one that places OCSs between top-of-rack (ToR) switches—ToR-reconfigurable networks (TRNs)—and one that places OCSs between pods of racks—pod-reconfigurable networks (PRNs). Second, we tackle the effects of reconfiguration frequency on network performance. Our results, based on network simulations driven by real HPC and DC workloads, show that while TRNs are optimized for low fan-out communication patterns, they are less suited for carrying high fan-out workloads. PRNs exhibit better overall trade-off, capable of performing comparably to a fully non-blocking fat tree for low fan-out workloads, and significantly outperform TRNs for high fan-out communication patterns.

Teh, Min Yee↗
DOE OSTI2023

Modular chip-integrated photonic control of artificial atoms in diamond waveguides

A central goal in creating long-distance quantum networks and distributed quantum computing is the development of interconnected and individually controlled qubit nodes. Atom-like emitters in diamond have emerged as a leading system for optically networked quantum memories, motivating the development of visible-spectrum, multi-channel photonic integrated circuit (PIC) systems for scalable atom control. However, it has remained an open challenge to realize optical programmability with a qubit layer that can achieve high optical detection probability over many optical channels. Here, we address this problem by introducing a modular architecture of piezoelectrically actuated atom-control PICs (APICs) and artificial atoms embedded in diamond nanostructures designed for high-efficiency free-space collection. The high-speed four-channel APIC is based on a splitting tree mesh with triple-phase shifter Mach–Zehnder interferometers. This design simultaneously achieves optically broadband operation at visible wavelengths, high-fidelity switching (>40dB) at low voltages, submicrosecond modulation timescales (>30MHz), and minimal channel-to-channel crosstalk for repeatable optical pulse carving. Via a reconfigurable free-space interconnect, we use the APIC to address single silicon vacancy color centers in individual diamond waveguides with inverse tapered couplers, achieving efficient single photon detection probabilities (∼15%) and second-order autocorrelation measurements g (2) (0)<0.14 for all channels. The modularity of this distributed APIC–quantum memory system simplifies the quantum control problem, potentially enabling further scaling to thousands of channels.

47 OTHER INSTRUMENTATION↗