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Improving the performance of medical imaging applications using SYCL

As opposed to the Open Computing Language (OpenCL) programming model, in which host and device codes are generally written in different programming languages, SYCL can combine host and device codes for an application in a type-safe way to improve development productivity and performance portability. Hence, this report shows the experimental results of applying the SYCL programming model to medical imaging applications for a study on performance portability and programming productivity between OpenCL and SYCL. Rodinia is a widely used open-source benchmark suite for heterogeneous computing. We choose two medical imaging applications (Heart Wall and Particle Filter) in the benchmark suite, migrate the OpenCL implementations of the applications to the SYCL implementations, and evaluate their performance and productivity on Intel® microprocessors that contain a central processing unit (CPU) and an integrated graphics processing unit (GPU). The maturing SYCL compilers, which are based on a conformant implementation of the SYCL 1.2.1 Khronos specification, have been actively optimized for Intel® computing platforms. The experimental results are promising in terms of the raw performance and productivity. Although the SYCL implementation of the Heart Wall application does not execute successfully on a CPU, the SYCL implementations of the application can achieve comparable or better performance than the OpenCL implementation on Intel® integrated GPUs. For the Particle Filter application, the performance difference between the SYCL and OpenCL implementations is comparable on the GPUs for most cases, but the SYCL implementations are on average 4X faster than the OpenCL implementations on Intel® Xeon® CPUs. For programming productivity, we arguably use lines of code as a way to measure programming productivity in software. The SYCL programs reduce the lines of code of the OpenCL programs by 52% and 38% for the Heart Wall and Particle Filter, respectively. The results indicate that SYCL is a promising programming model for heterogeneous computing with the maturing compilers. We organize the remainder of the report as follows. Section II introduces the SYCL programming model, compares the major differences between an OpenCL program and a SYCL program, and describes the characteristics of the two applications. Section III describes the SYCL programming model in more details, and shows the SYCL implementation of a kernel function in the Particle Filter application as an example. In Section IV, we evaluate the performance of the applications on the CPUs and GPUs. Section V concludes the report.

59 BASIC BIOLOGICAL SCIENCES↗

Advanced CMOS Reliability Update: Sub 20nm FinFET Assessment

Advances in FinFET design and fabrication enable manufacturing of denser, more compact integrated circuits (ICs) with substantially reduced leakage while shortening the channel-lengths. The same stress-induced leakage and breakdown degradation mechanisms that affect planar transistors also impact FinFET devices. Reliability concerns such as Bias Temperature Instability (BTI), Time Dependent Dielectric Breakdown (TDDB), and Hot Carrier Injection (HCI) become very important with changes to transistor geometry and fin sidewall crystal orientation. Recent testing has shown that FinFETs respond differently to radiation (radiation effects such as total ionizing dose) when compared to planar transistors. These reliability and radiation effects issues become very important when changing transistor geometry and scaling FinFETs towards smaller feature sizes (22-nm, 16-nm, 14- nm, 10-nm, and smaller critical dimensions). The comparable 2019 state of the art transistor densities in current high-volume manufacturing silicon-based foundries is 7-nm (ISMC, Samsung) and 10-nm (Intel) [www.anandtech.com,fuse.wikichip.org]. Released products include supporting components for the cellphone and commercial microprocessor markets respectively. Extensive development in the foundry industry is driving to a 5-nm technology node in late 2020.

47 OTHER INSTRUMENTATION↗

NERC MISOPS

This investigation was commissioned by the Office of Electricity of the Department of Energy in response to reviewing the NERC State of Reliability report. The study is an attempt to proactively address electric utility industry needs. “Monitoring, analyzing, and tracking trends in Protection System Misoperations are critical to improve BES reliability. Historically, Protection System Misoperations have exacerbated the severity of most cascading power outages.” The NERC misoperations data shows that unnecessary trips are by far the leading category of reported misoperations and that a majority of misoperations are those of line protection packages. A significant number of misoperations are tied to microprocessor relays. Approximately one quarter of reported misoperations are due to incorrect settings and another one quarter of misoperations are due to relay failures/malfunctions and communication failures.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Power System Waveform Classification Using Time-Frequency and CNN

Many modern reclosers and circuit breakers have microprocessor relays that record waveforms of system events. In some cases, utilities may record a half-a-dozen event captures for every event. This is thousands of events per year. The industry needs faster, more automated, more conclusive, and easy-to-use systems that can process massive amounts of event recordings without extensive input/support from power system engineers. To address the need for a commercially viable solution that can classify waveform data, energies were directed to develop a universal neural network (NN) structure (deep learning algorithm) that works for a wide variety of system event types. The structure that showed the most promise was one that included the use of spectrograms. The technique has shown positive results in audio engineering, particularly with respect to speech recognition. A waveform signature could be treated as a spoken word like audio waveforms for specific things such as “YES” or “UP”. No two people produce the exact same waveform when speaking each of these words, but audio processing algorithms based on spectrograms and convolutional neural networks (CNN) can still distinguish the word regardless of the speaker. No two circuits produce the exact same waveform for a given event, but the NN can be trained to classify the event type regardless of the circuit or location on the circuit. A Power System Neural Network (PSNN) has been developed to use a CNN to classify events within waveform data for power systems. The waveform is converted to an array of values by way of spectrograms and interpreted as an image. This image is passed into the CNN. The test results on independent simulated test and validation datasets show greater than 99% accuracy. While the results thus far are based on simulated data, the performance of the PSNN is very promising and should work for a wide variety of power system conditions of interest. Ultimately, much of the custom code and tools used today and much of the manual effort expended today may be automated using this PSNN.

24 POWER TRANSMISSION AND DISTRIBUTION↗

CRADA Number NFE-18-07342 with Lux Semiconductors, LLC (CRADA Final Report)

Lux Semiconductors is a flexible microelectronics startup developing a new class of Systemon-Foil electronics for rapidly emerging Internet-of-Things (IoT) markets. By leveraging its patent pending breakthrough in thin-film recrystallization, Lux is able to produce highly crystalline and flexible silicon substrates on a thin metal backing. This novel platform allows for high-speed silicon circuitry to be patterned directly into the substrate alongside low-cost printed electronics. The System-on-Foil approach has potential to enable the fabrication and integration of all core IoT functionality, including microprocessors, sensors, antennas, interconnects, and power supplies, required to enable highly durable, low profile, flexible electronics.

42 ENGINEERING↗

A Cybersecurity Threat Profile for a Connected Lighting System

In anticipation of improved energy performance and cost savings, cities and building owners are increasingly considering “smart lighting initiatives” that aim to convert their collection of simple luminaires (i.e., lighting fixtures) into an intelligent connected lighting system (CLS) capable of remotely monitoring energy consumption and fault conditions, and possibly implementing adaptive lighting schemes. The U.S. Department of Energy (DOE) has set an national goal of tripling the energy efficiency and demand flexibility of the buildings sector by 2030, relative to 2020 levels 1. It is forecast that connected lighting systems can contribute to that goal by delivering 125 TWh of annual energy savings by 2035 2, equivalent to the annual output of 50 typical (500 MW) power plants. However, these energy savings and the DOE goal are put at significant risk if connected technologies are not adopted due to real or perceived cybersecurity concerns. Connected IoT devices such as these have historically been rife with vulnerabilities which sometimes put security considerations secondary to functionality and operability. What are the cybersecurity threats that will impact these systems, as formerly banal luminaires transition into intelligent connected devices that collect information about themselves, their surrounding environment, and possibly us? In this paper we analyze a threat profile performed on a fault-detection use case for streetlights. A threat profile establishes security requirements, justifies security measures, yields actionable controls, and effectively communicates risk to stakeholders. This effort provides critical information for making threat-based decisions to increase security at a reasonable cost, and can effectively be used by development teams, software architects, and managers to make cybersecurity a part of their ongoing culture of awareness, training, and prevention. This leads to more secure systems and better-understood security. On-premise, cloud, and hybrid architectures with different authentication mechanisms were modeled and later categorized using the Microsoft STRIDE framework. An analysis of the recommended controls for each threat was performed to determine which controls could and should be put in place by manufacturers or third-party suppliers, and which controls need to be left up the end-user to implement. Fifty-seven threats were identified. Among our key findings: (1) 65% (37/57) of the threats did not involve the luminaires, but rather the other components needed to communicate with and manage them; (2) 63% (36/57) of the threats could have been mitigated through manufacturer-implemented defensive techniques or “controls”; and (3) 23% (13/57) of the threats were dependent on the network configuration. Recommendations based on the results of this work are made to key stakeholder groups. Notably, lighting technology developers are advised to address all threats that can be reasonably controlled with baked-in technology solutions (e.g., encryption or authentication controls), and employ some form of secure supply chain management and tracking where other parts (e.g., sensors, microprocessors) of a luminaire must also be built and manufactured with the proper security controls in place. Developers should also review threats involving assets not developed in-house to understand how connectivity with other devices will affect their product during system operation and determine if a compensating control for a defense-in-depth strategy will be needed. Finally, those interested in deploying CLS should compare the differences between cloud and on-premise models to determine which is more suitable for their needs and the abilities of their security team.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SIS-AOP Cueing/Segmenting Algorithm (FOA_SIS-AOP) Using the Sandia FOA 4.0 Framework

For machine vision, one of the most important operations is fast and effective object cueing or segmentation. Sandia National Labs has a long history of development and implementation of very fast and effective cueing/segmentation algorithms. This report covers the history, motivation and implementation of evolving frameworks (Sandia FOA Frameworks) upon which this long legacy of successful algorithms are built. The report describes the innovative microprocessor implementation, enabling extremely fast morphological processing, combined with a novel adaptive quantization front - end and a feature - based backend that resulted in Sandia developing fast and effective cueing in a wide variety of applications, from defect detection to SAR ATR. The report covers evolution from Sandia FOA 1.0 Framework (1995) to current Sandia FOA 4.0 Framework (2021). Requirements for the cueing algorithm for SIS - AOP (FOA_SIS - AOP) that drove the Sandia FOA 4.0 Framework development are discussed, along with information on how to use the Sandia FOA Frameworks.

97 MATHEMATICS AND COMPUTING↗

Open Radiation Monitoring: Conceptual System Design

The Open Radiation Monitoring (ORM) Project seeks to develop and demonstrate a modular radiation detection architecture designed specifically for use in arms control treaty verification (ACTV) applications that will facilitate rapid development of trusted systems to meet the needs of potential future treaties. Development of trusted systems to support potential future treaties is a complex and costly endeavor that typically results in a purpose-built system designed to perform one specific task. The majority of prior trusted system development efforts have relied on the use of commercial embedded computers or microprocessors to control the system and process the acquired data. These processors are complex, making authentication and certification of measurement systems and collected data challenging and time consuming. We believe that a modular architecture can be used to reduce more complex systems to a series of single-purpose building blocks that could be used to implement a variety of detection modalities with shared functionalities. With proper design, the functionality of individual modules can be confirmed through simple input/output testing, thereby facilitating equipment inspection and in turn building trust in the equipment by all treaty parties. Furthermore, a modular architecture can be used to control data flow within the measurement system, reducing the risk of "hidden switches" and constraining the amount of sensitive information that could potentially be inadvertently leaked. This report documents a conceptual modular system architecture that is designed to facilitate inspection in an effort to reduce overall authentication and certification burden. As of publication, this architecture remains in a conceptual phase and additional funding is required to prove out the utility of a modular architecture and test the assumptions used to rationalize the design.

61 RADIATION PROTECTION AND DOSIMETRY↗

Exploring the Limits of Cooling for Extreme Heat Flux Applications: Data Centers and Power Electronic

We developed an Extreme Heat Flux Micro-cooler (EHFµ-C) capable of removing heat flux of ~1 kW/cm 2 with a small temperature rise ~10°C. This represents greater than 10× reduction in thermal resistance compared to the state-of-the-art single-phase cooling technologies (~0.5 cm 2 -°C/W) that greatly increases the efficiency, resulting in improved performance and reliability for microprocessors and power electronics. The EHFµ-Cooler utilizes liquid wicking (no pump) and thin-film evaporation in a 30 µm thick wick porous microstructure such as copper inverse opal (CIO), silicon and AlN pin fins along with a 3D manifold (copper wiremesh and silicon) with liquid routing and vapor extraction channels achieving an unprecedented vapor quality ~ >0.9. The proposed EHFµ-Cooler significantly reduces device temperature, resulting in 25-50% improvement in reliability and device performance. Based on very conservative estimates, the total energy saving for data centers due to improved performance can be 6 billion kWh/year (>$300M). Better cooling, leading to more efficient, higher performance and more reliable power electronics, would save the nation 3 Quad of primary energy in 2030. Just for automotive application, a 10% increase in fuel efficiency for SiC-based power electronics equates to >20 million gallons of fuel savings annually. The proposed EHFµ-Cooler technology ensures the United States maintains its technological lead in high-performance computing and high-power electronics, while at the same time improving the energy efficiency, and as a result reducing energy-related emissions such as greenhouse gases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Extreme Efficiency 240 Vac to Load Data Center Power Delivery Topologies and Control

The research explored innovative new circuit topologies and power converter architectures for data center power delivery, from the 240 V ac voltage at the input of a server rack, down to the less than 1 V dc power supply of the latest microprocessors. The research pursued three parallel tracks to increase the power conversion efficiency and to reduce the overall size of the servers: 1) An innovative new ac-dc power converter topology which enables improved efficiency through use of a novel direct step-down topology, well suited for the popular 48V dc power distribution. 2) A new series-stacked power delivery approach for servers comprising a large number of similar loads, such as hard drives in storage servers. The approach greatly reduces the power conversion losses, and achieves efficiency well over 99%. 3) A new family of hybrid switched-capacitor power converters that enable improved efficiency and reduced size through the use of dense ceramic capacitors and new circuit topologies that leverage GaN and low-voltage Si transistor technology. Together, the accomplished research achieved the goal of reducing the power conversion losses in datacenters, thereby reducing greenhouse gas emissions, operating costs, and overall electricity consumption.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Secondary battery management

A method of managing a battery system, the battery system including at least one battery cell, at least one sensor configured to measure at least one characteristic of the battery cell, and a battery management system including a microprocessor and a memory, the method comprising receiving by the battery management system, from the at least one sensor at least one measured characteristic of the battery cell at a first time and at least one measured characteristic of the battery cell at a second time. The battery management system estimating, at least one state of the battery cell by applying a physics-based battery model, the physics based battery model being based on differential algebraic equations; and regulating by the battery management system, at least one of charging or discharging of the battery cell based on the at least one estimated state.

25 ENERGY STORAGE↗

Optical device for in-line and real-time monitoring of microorganisms

A multi-wavelength laser diode based optical sensor system capable of monitoring the dynamics and physiological changes of a microorganism culture in real-time. The microorganism culture from a microorganism production chamber is pumped to a flow chamber. Laser diodes emit light at certain wavelengths through the flow chamber, which is sensed by photodiodes. A laser control circuitry is operatively connected to the laser diodes and a signal conditioning circuitry is operatively connected to the photodiodes. A microprocessor reads and records voltage signals corresponding to the wavelengths. A data acquisition system converts said voltage signals into measurements of biological parameters, which are displayed on a graphical user interface and allow a user to monitor the measurements in real time.

47 OTHER INSTRUMENTATION↗

Low power and privacy preserving sensor platform for occupancy detection

A low-cost, low-power, stand-alone sensor platform having a visible-range camera sensor, a thermopile array, a microphone, a motion sensor, and a microprocessor that is configured to perform occupancy detection and counting while preserving the privacy of occupants. The platform is programmed to extract shape/texture from images in spatial domain; motion from video in time domain; and audio features in frequency domain. Embedded binarized neural networks are used for efficient object of interest detection. The platform is also programmed with advanced fusion algorithms for multiple sensor modalities addressing dependent sensor observations. The platform may be deployed for (i) residential use in detecting occupants for autonomously controlling building systems, such as HVAC and lighting systems, to provide energy savings, (ii) security and surveillance, such as to detect loitering and surveil places of interest, (iii) analyzing customer behavior and flows, (iv) identifying high performing stores by retailers.

Velipasalar, Senem↗

CRITICAL FUNCTION ASSURANCE: Understanding Critical Function and Critical Function Delivery is Foundational for Meaningful ICS Security Improvement and Policy Efforts

Modern life is enabled by a complex and interdependent web of critical functions, including energy, communications, transportation, food, and water. Automation has significantly reduced or replaced human interactions in the delivery of these functions, resulting in a web of goods and services that are made available 24/7 only through unique and intentional deployments of microprocessors, software, and firmware technologies. The prospect of cyber-enabled sabotage of these processes disrupts traditional risk determination models. Critical Function Assurance (CFA) is a foundational approach to identifying, prioritizing, and mitigating the risk that is inherent in the delivery of critical functions that depend on digital technology. It provides rapid focus to what matters most and illuminates elements and areas of risk that otherwise are often overlooked. This focus enables effective application of available security resources and optimizes security strategy and policy efforts. This paper introduces CFA to decision makers and risk executives (including CEOs, COOs, CFOs, and CISOs) whose organizations support and deliver the critical functions that underpin national defense, societal health and safety, and a vibrant economy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Development of a Hybrid Single/Two-Phase Capillary-Based Micro-Cooler Using Copper Inverse Opals Wick with Silicon 3D Manifold for High-Heat-Flux Cooling Application: Preprint

Previously, two-phase capillary-based cooling from narrow (200-1,000 micrometer) heater-bridge copper inverse opal (CIO) wicks with heat flux levels exceeding 1,400 watts per square cm with a low superheat of approximately 10 degrees C was demonstrated. Here, we demonstrate the area scaling of the proposed technology to large-area micro-cooler for the high-heat-flux cooling of microprocessors and power electronics. We developed a hybrid single/two-phase micro-cooler that relies on capillary wicking in 25-micrometer-thick CIOs with an open channel silicon 3D-manifold for liquid delivery and vapor extraction, to achieve a high heat flux of approximately 400 watts per square cm over a heated area of 1 square cm. For the range of inlet water (21 degrees C water temperature) flowrates from 5 to 60 mL per min, we achieved total thermal resistances and vapor qualities of 0.68-0.2 square cm Kelvin per watt and 0.55-0.12, respectively. The high heat flux levels are achieved with flowrates that are 10 times smaller than conventional single- or two-phase microchannel cooling technology. The corresponding two-phase thermal resistances are in the range of 0.05 to 0.02 square cm Kelvin per watt with temperature superheat of 8 to 6 degrees C. While the overall performance of the large-area (10 by 10 square millimeter) capillary-based micro-cooler degraded compared to previous demonstration of the technology for a heated area of 5 by 5 square millimeter, preliminary computational fluid dynamics (CFD) modeling indicates that an improved manifold design will be able to achieve comparable performance.

capillary flow↗

Field Programmable Gate Array Data Capture for Control Systems

Some Industrial Control Systems (ICS) networks are based on protocols such as Serial and Industrial Ethernet. These protocols currently have no existing cybersecurity monitoring tools, leaving a large gap in the cyber defense of critical infrastructure. In order to analyze such ICS traffic, it is first necessary to implement methods of capturing the ICS data. Whereas traditional methods of analyzing data would use microprocessors, the nature of high-speed analog data can be difficult to implement on such a versatile processor, as they are rather inefficient for doing a single task. Whereas Field Programmable Gate Arrays (FPGAs) provide an adequate tool in analyzing high speed data, as despite the lack of program versatility, Programmable Logic can implement a solution with minimal clock cycles, allowing time for each new packet of data to be captured before a new data sample is taken.

42 ENGINEERING↗

Generalized and Mechanistic PV Module Performance Prediction From Computer Vision and Machine Learning on Electroluminescence Images

Electroluminescence (EL) imaging of photovoltiac (PV) modules offers high-speed, high-resolution information about device performance, affording opportunities for greater insight and efficiency in module characterization across manufacturing, research and development, and power plant operations and management. Predicting module electrical properties from EL image features is a critical step toward these applications. In this article, we demonstrate quantification of both generalized and performance mechanism-specific EL image features, using pixel intensity-based and machine learning classification algorithms. From EL image features, we build predictive models for PV module power and series resistance, using time-series current-voltage (I-V) and EL data obtained stepwise on five brands of modules spanning three Si cell types through two accelerated exposures: damp heat (DH) (85°C/85% RH) and thermal cycling (TC) (IEC 61215). Overall, 195 pairs of EL images and I-V characteristics were analyzed, yielding 11700 individual PV cell images. A convolutional neural network was built to classify cells by the severity of busbar corrosion with high accuracy (95%). Generalized power predictive models estimated the maximum power of PV modules from EL images with high confidence and an adjusted-R 2 of 0.88, across all module brands and cell types in extended DH and TC exposures. Mechanistic degradation prediction was demonstrated by quantification of busbar corrosion in EL images of three module brands in DH, and subsequent modeling of series resistance using these mechanism-specific EL image features. For modules exhibiting busbar corrosion, we demonstrated series resistance predictive models with adjusted-R 2 of up to 0.73.

14 SOLAR ENERGY↗

Novel Module Architecture for Lower CapEx and Improved Recyclability for c-Si PV Modules

Photovoltaic (PV) energy production is currently increasing at a rate at which recycling is becoming necessary. A novel module architecture has been demonstrated that has potential for high value recycling for c-Si PV. This architecture eliminates the vacuum lamination process and cross-linked en capsulants. Functioning prototypes of c-Si have been fabricated for stress testing in collaboration with NREL. These modules are being tested against traditionally manufactured modules. Based on preliminary results, this module architecture is a potentially viable solution for improving the manufacturing cost and recyclability of PV modules while retaining module performance.

computer architecture↗