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At least 595 records · Page 33

Re-Design and Beat Testing of the Man-Machine Integration Design and Analysis System: MIDAS

The Man-machine Design and Analysis System (MIDAS) is a human factors design and analysis system that combines human cognitive models with 3D CAD models and rapid prototyping and simulation techniques. MIDAS allows designers to ask 'what if' types of questions early in concept exploration and development prior to actual hardware development. The system outputs predictions of operator workload, situational awareness and system performance as well as graphical visualization of the cockpit designs interacting with models of the human in a mission scenario. Recently, MIDAS was re-designed to enhance functionality and usability. The goals driving the redesign include more efficient processing, GUI interface, advances in the memory structures, implementation of external vision models and audition. These changes were detailed in an earlier paper. Two Beta test sites with diverse applications have been chosen. One Beta test site is investigating the development of a new airframe and its interaction with the air traffic management system. The second Beta test effort will investigate 3D auditory cueing in conjunction with traditional visual cueing strategies including panel-mounted and heads-up displays. The progress and lessons learned on each of these projects will be discussed.

Shively, R. Jay↗

Case Study of the Space Shuttle Cockpit Avionics Upgrade Software

The purpose of the Space Shuttle Cockpit Avionics Upgrade project was to reduce crew workload and improve situational awareness. The upgrade was to augment the Shuttle avionics system with new hardware and software. An early version of this system was used to gather human factor statistics in the Space Shuttle Motion Simulator of the Johnson Space Center for one month by multiple teams of astronauts. The results were compiled by NASA Ames Research Center and it was was determined that the system provided a better than expected increase in situational awareness and reduction in crew workload. Even with all of the benefits nf the system, NASA cancelled the project towards the end of the development cycle. A major success of this project was the validation of the hardware architecture and software design. This was significant because the project incorporated new technology and approaches for the development of human rated space software. This paper serves as a case study to document knowledge gained and techniques that can be applied for future space avionics development efforts. The major technological advances were the use of reflective memory concepts for data acquisition and the incorporation of Commercial off the Shelf (COTS) products in a human rated space avionics system. The infused COTS products included a real time operating system, a resident linker and loader, a display generation tool set, and a network data manager. Some of the successful design concepts were the engineering of identical outputs in multiple avionics boxes using an event driven approach and inter-computer communication, a reconfigurable data acquisition engine, the use of a dynamic bus bandwidth allocation algorithm. Other significant experiences captured were the use of prototyping to reduce risk, and the correct balance between Object Oriented and Functional based programming.

Ferguson, Roscoe C.↗

TU-A-17A-01: Memorial to Benjamin M. Galkin - Memorial Lecture

This past year Medical Physics lost one of its active members, Benjamin M. Galkin. Ben Galkin was a Past-Treasurer of the AAPM. During his leadership role he played an important part in Securing membership, for the AAPM, in the American Institute of physics. As Treasurer he was also a prime mover in starting the journal, Medical Physics, and served as its business manager in the formative years.Ben Galkin received his Masters Degree at Columbia University in New York, under the mentorship of Dr. Edith Quimby, one of the pioneer Hospital Radiation Physicists in the country. He started his professional career at Jefferson Hospital in Philadelphia, joining Robert Gorson, and remained there until retirement. He served as the institution’s Radiation Safety Officer throughout his career. His research interest was Breast Imaging. He held joint faculty appointments in the Department of Radiology and the Department of Radiation Therapy and Nuclear Medicine, rising up to the rank of Full professor. He was a well respected teacher for the residents in Radiology.

60 APPLIED LIFE SCIENCES↗

SU-F-T-256: 4D IMRT Planning Using An Early Prototype GPU-Enabled Eclipse Workstation

Purpose: True 4D IMRT planning, based on simultaneous spatiotemporal optimization has been shown to significantly improve plan quality in lung radiotherapy. However, the high computational complexity associated with such planning represents a significant barrier to widespread clinical deployment. We introduce an early prototype GPU-enabled Eclipse workstation for inverse planning. To our knowledge, this is the first GPUintegrated Eclipse system demonstrating the potential for clinical translation of GPU computing on a major commercially-available TPS. Methods: The prototype system comprised of four NVIDIA Tesla K80 GPUs, with a maximum processing capability of 8.5 Tflops per K80 card. The system architecture consisted of three key modules: (i) a GPU-based inverse planning module using a highly-parallelizable, swarm intelligence-based global optimization algorithm, (ii) a GPU-based open-source b-spline deformable image registration module, Elastix, and (iii) a CUDA-based data management module. For evaluation, aperture fluence weights in an IMRT plan were optimized over 9 beams,166 apertures and 10 respiratory phases (14940 variables) for a lung cancer case (GTV = 95 cc, right lower lobe, 15 mm cranio-caudal motion). Sensitivity of the planning time and memory expense to parameter variations was quantified. Results: GPU-based inverse planning was significantly accelerated compared to its CPU counterpart (36 vs 488 min, for 10 phases, 10 search agents and 10 iterations). The optimized IMRT plan significantly improved OAR sparing compared to the original internal target volume (ITV)-based clinical plan, while maintaining prescribed tumor coverage. The dose-sparing improvements were: Esophagus Dmax 50%, Heart Dmax 42% and Spinal cord Dmax 25%. Conclusion: Our early prototype system demonstrates that through massive parallelization, computationally intense tasks such as 4D treatment planning can be accomplished in clinically feasible timeframes. With further optimization, such systems are expected to enable the eventual clinical translation of higher-dimensional and complex treatment planning strategies to significantly improve plan quality. This work was partially supported through research funding from National Institutes of Health (R01CA169102) and Varian Medical Systems, Palo Alto, CA, USA.

60 APPLIED LIFE SCIENCES↗

Enhancing scalability of a matrix-free eigensolver for studying many-body localization

We propose several techniques to enhance the parallel scalability of a matrix-free eigensolver designed for studying many-body localization (MBL) of quantum spin chain models with nearest-neighbor interactions and on-site disorder. This type of problem is computationally challenging because the dimension of the associated Hamiltonian matrix grows exponentially with respect to the number of spins L, and we need to average over different realizations of the random disorder to obtain relevant statistical behavior. For each disorder realization, we need to compute eigenvalues from different regions of the spectrum and their corresponding eigenvectors. In previous work, the interior eigenstates for a single eigenvalue problem are computed via the shift-and-invert Lanczos algorithm. Due to the extremely high memory footprint of the LU factorizations, this technique is not well suited for large L’s. For example, we need thousands of compute nodes on modern high performance computing infrastructures to go beyond L = 24. The matrix-free approach does not suffer from this memory bottleneck, however, its scalability is limited by a computation and communication load imbalance. To reduce this imbalance and to significantly enhance the scalability of the matrix-free eigensolver, we reorder the matrix and leverage the consistent space runtime, CSPACER. We also show its efficiency in managing irregular communication patterns at scale compared to optimized MPI non-blocking two-sided and one-sided RMA implementation variants. This effort enables us to study MBL for spin chains with a larger number of spins. The efficiency and effectiveness of the proposed algorithm is demonstrated by computing eigenstates on a massively parallel many-core high performance computer.

METIS↗

The Revised WIPP Passive Institutional Controls Program - A Conceptual Plan - 13145

The Department of Energy/Carlsbad Field Office (DOE/CBFO) is responsible for managing all activities related to the disposal of TRU and TRU-mixed waste in the geologic repository, 650 m below the land surface, at WIPP, near Carlsbad, New Mexico. The main function of the Passive Institutional Controls (PIC's) program is to inform future generations of the long-lived radioactive wastes buried beneath their feet in the desert. For the first 100 years after cessation of disposal operations, the rooms are closed and the shafts leading underground sealed, WIPP is mandated by law to institute Active Institutional Controls (AIC's) with fences, gates, and armed guards on patrol. At this same time a plan must be in place of how to warn/inform the future, after the AIC's are gone, of the consequences of intrusion into the geologic repository disposal area. A plan was put into place during the 1990's with records management and storage, awareness triggers, permanent marker design concepts and testing schedules. This work included the thoughts of expert panels and individuals. The plan held up under peer review and met the requirements of the U.S. Environmental Protection Agency (EPA). Today the NEA is coordinating a study called the 'Preservation of Records, Knowledge and Memory (RK and M) Across Generations' to provide the international nuclear waste repository community with a guide on how a nuclear record archive programs should be approached and developed. CBFO is cooperating and participating in this project and will take what knowledge is gained and apply that to the WIPP program. At the same time CBFO is well aware that the EPA and others are expecting DOE to move forward with planning for the future WIPP PIC's program; so a plan will be in place in time for WIPP's closure slated for the early 2030's. The DOE/CBFO WIPP PIC's program in place today meets the regulatory criteria, but complete feasibility of implementation is questionable, and may not be in conformance with the international guidance being developed. International guidance currently under development may suggest that the inter-generational equity principle strives to warn the future, however, in doing so not to unduly burden present generations. Building markers and monuments that are out of proportion to the risk being presented to the future is not in keeping with generational equity. With this in mind the DOE/CBFO is developing conceptual plans for re-evaluating and revising the current WIPP PIC's program. These conceptual plans will suggest scientific and technical work that must be completed to develop a 'new' PICs program that takes the best ideas of the present plan, blended with new ideas from the RK and M project, and proposed alternative permanent markers designs and materials in consideration. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Versatile High-Gain Low-Noise Readout ASIC for Silicon Microstrip Tracking Detectors

This work presents Turpial, a custom-designed low- power front-end readout ASIC for microstrip silicon sensors. Implemented in 130 nm CMOS technology, the chip integrates 64 identical readout channels, each including a configurable charge-sensitive amplifier, a bipolar pulse shaper, a 32-sample 50 Msps analog memory, and a 12-bit RC-hybrid SAR ADC operating at 1 Msps. To satisfy the target power budget of 5 mW per channel, the architecture employs a time-decoupled readout scheme in which fast transient signals are first captured in the analog memory and subsequently digitized at a lower rate. Turpial supports a wide dynamic range from 1 kℎ+ to 1 Mℎ+ while maintaining low noise performance, targeting an equivalent noise charge (ENC) below 200 𝑒−including the sensor, and providing a maximum gain of 1500 mV/fC. A digital block manages slow control, data acquisition, and data serialization through dual CML 300 Mb/s serializers. In addition, an on-chip reference circuit, based on a sub-1 V bandgap reference and an integrated LDO regulator, eliminates the need for external reference circuitry. Experimental results demonstrate that both the individual building blocks and the fully integrated ASIC meet the design specifications.

Hernandez, Hugo [Stanford University] (ORCID:00000↗

Autonomous Telemetry Collection for Single-Processor Small Satellites

For the Space Technology 5 mission, which is being developed under NASA's New Millennium Program, a single spacecraft processor will be required to do on-board real-time computations and operations associated with attitude control, up-link and down-link communications, science data processing, solid-state recorder management, power switching and battery charge management, experiment data collection, health and status data collection, etc. Much of the health and status information is in analog form, and each of the analog signals must be routed to the input of an analog-to-digital converter, converted to digital form, and then stored in memory. If the micro-operations of the analog data collection process are implemented in software, the processor may use up a lot of time either waiting for the analog signal to settle, waiting for the analog-to-digital conversion to complete, or servicing a large number of high frequency interrupts. In order to off-load a very busy processor, the collection and digitization of all analog spacecraft health and status data will be done autonomously by a field-programmable gate array that can configure the analog signal chain, control the analog-to-digital converter, and store the converted data in memory.

Speer, Dave↗

Network acceleration techniques

Splintered offloading techniques with receive batch processing are described for network acceleration. Such techniques offload specific functionality to a NIC while maintaining the bulk of the protocol processing in the host operating system ("OS"). The resulting protocol implementation allows the application to bypass the protocol processing of the received data. Such can be accomplished this by moving data from the NIC directly to the application through direct memory access ("DMA") and batch processing the receive headers in the host OS when the host OS is interrupted to perform other work. Batch processing receive headers allows the data path to be separated from the control path. Unlike operating system bypass, however, the operating system still fully manages the network resource and has relevant feedback about traffic and flows. Embodiments of the present disclosure can therefore address the challenges of networks with extreme bandwidth delay products (BWDP).

Crowley, Patricia↗

Towards Ultra-high-resolution E3SM Land Modeling on Exascale Computers

Here we present an ultra-high-resolution E3SM land model (uELM) for high-fidelity land simulations targeting new Exascale computers. After considering modeling infrastructure compatibility and ELM software features, we designed a parallel model for the uELM development targeting hybrid architectures of new US Exascale computers. We also described a function unit test framework to expedite the piece-wise code porting (with compiler directives), verification, and global variable management. Furthermore, in this study, we report an early uELM model development using OpenACC within a function unit test framework on a pre-Exascale computer, demonstrate the performance of a uLEM submodel with a 3.0-time speedup, and summarize the code porting experience regarding global variable handling, deepcopy, memory reduction, and parallel loop reconstruction.

97 MATHEMATICS AND COMPUTING↗

CRADA Final Report: Open Microgrid Platform

Current microgrid control technology is mostly proprietary, expensive, and inflexible. An open-source, vendor-neutral, publish-subscribe controller will significantly lower the barrier to entry for new technologies and market entrants: inverter, battery, and load control manufacturers; cloud and services providers; and energy aggregators. An OpenFMB controller can significantly reduce the acquisition, integration, and ongoing operating and maintenance costs and increase revenue opportunities for energy producers and consumers. It allows distributed energy resource (DER) owners to replace individual DER components as richer-function, lower-cost devices become available or to incorporate new forecast and optimization algorithms as they are developed. A standard, secure, full-function DER field controller will also provide a low-cost means for grid operators to effectively manage the variability and uncertainty of solar photovoltaics (PV). Under the terms of this CRADA, ORNL has worked with Open Energy Solutions (OES) to advance the transition of ORNL’s existing open-source microgrid controller into a platform geared toward mainstream implementation. Using a more prevalent and memory-safe programming language, Rust, OES has converted ORNL’s current generation on-grid optimization into an application more suitable for industry use. The results of the ported optimization were analyzed by inputting the same arguments in both the current-generation and next-generation optimizers and verifying that the results were equivalent.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs

Increasing the accuracy of storm-surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm-surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm-surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and, most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite-element-based codes. It affords a capability for simulating tidal circulation and storm-surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm-surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate. To keep the computational load manageable, this work was conducted using only the wind stress, calculated by using historical data from Hurricane Camille, as the input condition for the model. Hurricane storm-surge simulations were performed on an eight-node Linux computer cluster. Each node contained dual 2-GHz processors, 2GB of memory, and a 40GB hard drive. The digital elevation model (DEM) for this region was specified using a combination of Navy data (over water), NOAA data (for the coastline), and optimized Interferometric Synthetic Aperture Radar data (over land). This high-resolution topographical data of the Mississippi coastal region provided the ADCIRC model with improved input with which to calculate improved storm-surge forecasts.

Valenti, Elizabeth↗

A Partitioned - Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a platform for multiscale modeling of composites which can perform analysis of materials with any arbitrary number of length scales. The platform supports modularity, scalability, and interoperability using recursive procedures and data structures. A Macro solver driven parallelization scheme often limits the capability of NASMAT to scale as it has access to limited memory and number of cores (often one core/thread) and often forces to implement macro solver specific changes to the platform. In this work, a partitioned task-parallel approach is adopted, where the parallelization strategy adopted for NASMAT is independent of the macro solver and the computational resources are managed independently. The programming architecture takes into account the hierarchy of multiple scales (task-dependence) and the heterogeneous nature (dynamic load balancing) of computation through implementation of a hierarchy-informed task parallel model. The partitioned nature of the framework further extends the “plug and play” capability of NASMAT. preCICE, an open-source library for coupling multiphysics solver in a partitioned manner, is adopted to integrate NASMAT with an external macro solver by implementing a NASMAT adapter for preCICE. Speedup and scalability of the framework is studied for micromechanical models of varying size.

task-parallel↗

Predicting Air Traffic Management Initiatives Using Supervised Learning

Terminal Traffic Management Initiatives (TMIs) such as Ground Stops (GS) and Ground Delay Programs (GDP) are implemented to manage excess demand or lowered capacity at an airport. Air Traffic Flow Management (TFM) specialists identify situations such as aviation constraints, current and forecasted weather conditions, airport demand and capacity, and initiate TMIs for safe and orderly movement of air traffic. In this paper, we outline supervised learning techniques that can be used to predict and recommend TMIs at an airport based on current weather and airport conditions. Our research involves building classic Machine Learning (ML) models such as Logistic Regression, K-Nearest Neighbor, Random Forest and XGBoost, as well as Long short-term memory (LSTM) networks. We trained the models on 3-year historical data (weather, airport demand, capacity and TMIs) from Newark (EWR) airport which was selected based on its higher TMI implementation rates and varied weather conditions. Although Random Forest and XGBoost algorithms are able to predict if a TMI is needed or not, they have difficulty in predicting specific program type. For this purpose, we found that LSTM time-series forecasting models performed better as they also learn from past TMI program type sequences. This study also lays down the foundation for advanced modeling techniques and architectures to predict TMIs in advance for future periods. The ability to predict TMIs in advance will be highly beneficial to the traffic controllers and managers as this will help them to prepare for and manage TMIs more efficiently.

Manoj Agrawal↗

Cooperative single-photon subradiant states in a three-dimensional atomic array

We propose a complete superradiant and subradiant states that can be manipulated and prepared in a three-dimensional atomic array. These subradiant states can be realized by absorbing a single photon and imprinting the spatially-dependent phases on the atomic system. We find that the collective decay rates and associated cooperative Lamb shifts are highly dependent on the phases we manage to imprint, and the subradiant state of long lifetime can be found for various lattice spacings and atom numbers. We also investigate both optically thin and thick atomic arrays, which can serve for systematic studies of super- and sub-radiance. Our proposal offers an alternative scheme for quantum memory of light in a three-dimensional array of two-level atoms, which is applicable and potentially advantageous in quantum information processing. - Highlights: • Cooperative single-photon subradiant states in a three-dimensional atomic array. • Subradiant state manipulation via spatially-increasing phase imprinting. • Quantum storage of light in the subradiant state in two-level atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

PARAFAC_T1

This is a method of performing trilinear analysis on large data sets using a modification of the PARAFAC-ALS algorithm. It iteratively decomposes the data matrix into a core matrix and three loading matrices based on the Tucker1 model. The algorithm is particularly useful for data sets that are too large to upload into a computer?s main memory. While the performance advantage in utilizing our algorithm is dependent on the number of data elements and dimensions of the data array, we have seen a significant performance improvement over operating PARAFAC-ALS on the full data set. SAND2020-12649 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Van Benthem, Mark↗

IceNet for FireBox - A Berkeley Warehouse-Scale Computer

Berkeley’s FireBox is a next-generation warehouse-scale computer (WSC) that utilizes the energy-efficiency and bandwidth density of integrated silicon-photonic interconnects to enable a new high-bandwidth and low-latency network fabric connecting thousands of compute nodes to petabytes of DRAM and Flash storage. The high bandwidth, low latency and high connectivity of FireBox’s WSC network fabric (IceNet) will enable dramatic improvements in the overall system energy efficiency enabling fine-grain power control on system resources (processors, links and memory/storage components). IceNet is a special 3-stage photonic Clos network architected to achieve ultra-low-latency connectivity between processor nodes and memory, drastically cutting down on the energy wasted in resource idling (processors and memory stalled due to pending network requests). This is achieved by integration of the first and last switch stages into processor/memory hub clients and by heavy over-provisioning of the high-radix middle switches (FlareSwitches). A key hardware component developed in this program is an active laser power management photonic integrated circuits called LightSpark. It interacts with the FlareSwitch and provides laser power to a subset of occupied switch ports, increasing the utilization of laser light in the photonic network by an order of magnitude. In addition to guiding the laser power where it is needed, the laser-power management module enables both wavelength and laser redundancy, significantly increasing the robustness of the system. The goal of the IceNet fabric is to enable communication between 1000s of processor nodes and PBs of memory/storage with <100ns latency, <10pJ/b wall-plug energy cost at multiple Pb/s of available connectivity bandwidth. These metrics represent two-orders of magnitude improvement with respect to the status of current data-center technology.

42 ENGINEERING↗