On the Application of Model-based Parameter Estimation For Mitigating Corrupted Data in Radar Applications.
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Cold climate Heat Pumps (CCHPs) using single-speed compressors in tandem have been successfully built and tested to reach its performance metrics with outdoor temperatures as low as -25°C. CCHPs must be designed to alleviate the problems of too high discharge temperatures, low suction pressure and high-pressure ratio at low ambient conditions and insufficient heating capacity relative to the heating capacity at 8.3°C. In this paper we recognize those concerns. Low-GWP refrigerants are screened based on the shape of their T-S saturation boundary. Simulations of the performance of low-GWP refrigerants (R32, R454B, R466A, and R452B) relative to R410A is done using the DOE/ORNL Heat Pump Design Model at the component level. Systemic inefficiency, the root cause of lost work, is addressed by component-level exergy analysis to refine design options. CCHPs using low-GWP refrigerants addresses issues of reducing energy consumption, lowering carbon footprint, and enabling environmentally sustainability. The CCHP was designed to meet a HSPF > 11.0 and SEER > 15.0 having adequate heat pump heating capacity down to -25°C. It is estimated that at least 2.6 million U.S homes using electric furnaces and heat pumps in cold or very old climates with an annual energy consumption of 0.17EJ would benefit by CCHPs.
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Purpose: The objective is to improve the efficiency and efficacy of Xoft™ Axxent™ electronic brachytherapy (EBT) calibration of the source & surface applicator using AAPM TG-61 formalism. Methods: Current method of Xoft EBT source calibration involves determination of absolute dose rate of the source in each of the four conical surface applicators using in-air chamber measurements & TG61 formalism. We propose a simplified TG-61 calibration methodology involving initial characterization of surface cone applicators. This is accomplished by calibrating dose rates for all 4 surface applicator sets (for 10 sources) which establishes the “applicator output ratios” with respect to the selected reference applicator (20 mm applicator). After the initial time, Xoft™ Axxent™ source TG61 Calibration is carried out only in the reference applicator. Using the established applicator output ratios, dose rates for other applicators will be calculated. Results: 200 sources & 8 surface applicator sets were calibrated cumulatively using a Standard Imaging A20 ion-chamber in accordance with manufacturer-recommended protocols. Dose rates of 10, 20, 35 & 50mm applicators were normalized to the reference (20mm) applicator. The data in Figure 1 indicates that the normalized dose rate variation for each applicator for all 200 sources is better than ±3%. The average output ratios are 1.11, 1.02 and 0.49 for the 10 mm,35 mm and 50 mm applicators, respectively, which are in good agreement with the manufacturer’s published output ratios of 1.13, 1.02 and 0.49. Conclusion: Our measurements successfully demonstrate the accuracy of a new calibration method using a single surface applicator for Xoft EBT sources and deriving the dose rates of other applicators. The accuracy of the calibration is improved as this method minimizes the source position variation inside the applicator during individual source calibrations. The new method significantly reduces the calibration time to less than one third of the current calibration time while improving efficacy.
Efficient parallel implementations of scientific applications on multi-core CPUs with accelerators such as GPUs and Xeon Phis is challenging. This requires - exploiting the data parallel architecture of the accelerator along with the vector pipelines of modern x86 CPU architectures, load balancing, and efficient memory transfer between different devices. It is relatively easy to meet these requirements for highly structured scientific applications. In contrast, a number of scientific and engineering applications are unstructured. Getting performance on accelerators for these applications is extremely challenging because many of these applications employ irregular algorithms which exhibit data-dependent control-ow and irregular memory accesses. Furthermore, these applications are often iterative with dependency between steps, and thus making it hard to parallelize across steps. As a result, parallelism in these applications is often limited to a single step. Numerical simulation of charged particles beam dynamics is one such application where the distribution of work and memory access pattern at each time step is irregular. Applications with these properties tend to present significant branch and memory divergence, load imbalance between different processor cores, and poor compute and memory utilization. Prior research on parallelizing such irregular applications have been focused around optimizing the irregular, data-dependent memory accesses and control-ow during a single step of the application independent of the other steps, with the assumption that these patterns are completely unpredictable. We observed that the structure of computation leading to control-ow divergence and irregular memory accesses in one step is similar to that in the next step. It is possible to predict this structure in the current step by observing the computation structure of previous steps. In this dissertation, we present novel machine learning based optimization techniques to address the parallel implementation challenges of such irregular applications on different HPC architectures. In particular, we use supervised learning to predict the computation structure and use it to address the control-ow and memory access irregularities in the parallel implementation of such applications on GPUs, Xeon Phis, and heterogeneous architectures composed of multi-core CPUs with GPUs or Xeon Phis. We use numerical simulation of charged particles beam dynamics simulation as a motivating example throughout the dissertation to present our new approach, though they should be equally applicable to a wide range of irregular applications. The machine learning approach presented here use predictive analytics and forecasting techniques to adaptively model and track the irregular memory access pattern at each time step of the simulation to anticipate the future memory access pattern. Access pattern forecasts can then be used to formulate optimization decisions during application execution which improves the performance of the application at a future time step based on the observations from earlier time steps. In heterogeneous architectures, forecasts can also be used to improve the memory performance and resource utilization of all the processing units to deliver a good aggregate performance. We used these optimization techniques and anticipation strategy to design a cache-aware, memory efficient parallel algorithm to address the irregularities in the parallel implementation of charged particles beam dynamics simulation on different HPC architectures. Experimental result using a diverse mix of HPC architectures shows that our approach in using anticipation strategy is effective in maximizing data reuse, ensuring workload balance, minimizing branch and memory divergence, and in improving resource utilization.
The objective of the Next Generation Internet (NGI) Federal program is threefold, encompassing development of networking technologies, high-performance network testbeds, and revolutionary applications. There have been notable advances in emerging network technologies and several nationwide testbeds have been established, but the integration of emerging technologies into applications is lagging. To help bridge this gap between developers of NGI networking technologies and developers of NGI applications, the NASA Research and Education Network (NREN) project hosted a two-day workshop at NASA Ames Research Center in August 1999. This paper presents a summary of the results of this workshop and also describes some of the challenges NREN is facing while incorporating new technologies into HPCC and other NASA applications. The workshop focused on three technologies - Quality of Service (QoS), advanced multicast, and security-and five major NGI application areas - telemedicine, digital earth, digital video, distributed data-intensive applications, and computational infrastructure applications. Network technology experts, application developers, and NGI testbed representatives came together at the workshop to promote cross-fertilization between the groups. Presentations on the first day, including an overview of the three technologies, application case studies and testbed status reports, laid the foundation for discussions on the second day. The objective of these latter discussions, held within smaller breakout groups, was to establish a coherent picture of the current status of the various pieces of each of the three technologies, to create a roadmap outlining future technology development, and to offer technological guidance to application developers. In this paper we first present a brief overview of the NGI applications that were represented at the workshop, focusing on the identification of technological advances that have successfully been incorporated in each application and technological challenges that remain. Next we present the technology roadmaps that were created at the workshop, summarizing the status of various mechanisms that are currently under development and forecasting when various advances are likely to occur within the next one-to-three-year time span. Then we identify issues that were raised at the workshop that might hinder technology development or that might impede integration into NGI applications. We also report some specific guidelines that were offered at the workshop to enable application developers to integrate and effectively use emerging NGI technology building blocks. Finally, we describe NREN activities to incorporate emerging technologies into NASA applications. These activities include support for other NASA High-Performance Computing and Communications Program areas such as IPG (Information Power Grid), support for NASA science enterprises such as Earth science and Mars program prototyping activities, support for satellite/terrestrial networking applications such as the TransAtlantic and TransPacific demonstrations and the Interplanetary Internet, support for NASA telemedicine applications such as the Virtual Collaborative Clinic, and participation in NGI advanced technology testbed initiatives such as the QBone and the NTON/Supernet. For each activity we highlight the primary technological challenge that is associated with it.
Application packaging and distribution are the final steps for delivering software to end-users; both are frequently neglected when creating scientific software. Commercial businesses rely on electronic distribution systems that have rendered disk drives obsolete. Still, national laboratories continue to rely heavily on removable media to distribute and limit access to controlled applications. With increasing concerns of unauthorized copying of sensitive applications, a modern distribution system that utilizes cryptographically secure communication and authentication protocols has been developed. This new distribution system will secure the chain of custody for nuclear software while simultaneously simplifying access to these tools. This report summarizes four primary advancements made toward the secure distribution of Nuclear Energy Advanced Modeling and Simulation (NEAMS)-developed, Multiphysics Object Oriented Simulation Environment (MOOSE)-based applications: application installation, package distribution, automated package building, and distribution of documentation. NEAMS is currently developing more than ten separate applications based on the open-source MOOSE Framework. Distribution of these applications has primarily been accomplished by distributing source code, with end-users compiling the applications themselves. This work created a mechanism where MOOSE applications can be installed in a similar way to any other software. This allows both administrators and end-users simplified access to runnable executables. With this new installation capability, it was then possible to rethink distribution. A new, secure capability for delivering MOOSE-based applications over the internet has been created. This system requires unique cryptographic tokens for authentication, greatly securing the custody chain for software. Once granted access, installation of any NEAMS code can be accomplished with these terminal commands: "conda install ncrc" "ncrc install ncrc-bison." After these two commands (and authenticating) the BISON application will be securely down- loaded from Idaho National Laboratory (INL)’s servers, installed, and ready to use. To enable this new distribution capability to be successful, the open-source Continuous Integration, Verification, Enhancement, and Testing (CIVET) Continuous Integration (CI) capability was augmented to add Continuous Delivery (CD). CD enables the automated building and packaging of MOOSE-based applications as they are modified by development teams, ensuring that our customers can obtain up-to-date versions of the software at any time. The need for instruction on how to use these applications was addressed through modifications to the MOOSE documentation system. The MooseDocs capability, which enables robust documentation of MOOSE-based applications, has been extended to allow both for the installation of documentation and the packaging of documentation with installed applications. Together, these enhancements form the core of a new, secure distribution mechanism for nuclear simulation tools. In concert with the Nuclear Computational Resource Center (NCRC), NEAMS- developed applications will now be straightforward to obtain securely.
In this article, we present an approach to streaming collection of application performance data. Practical application performance tuning and troubleshooting in production high-performance computing (HPC) environments requires an understanding of how applications interact with the platform, including (but not limited to) parallel programming libraries such as Message Passing Interface (MPI). Several profiling and tracing tools exist that collect heavy runtime data traces either in memory (released only at application exit) or on a file system (imposing an I/O load that may interfere with the performance being measured). Although these approaches are beneficial in development stages and post-run analysis, a systemwide and low-overhead method is required to monitor deployed applications continuously. This method must be able to collect information at both the application and system levels to yield a complete performance picture. In our approach, an application profiler collects application event counters. A sampler uses an efficient inter-process communication method to periodically extract the application counters and stream them into an infrastructure for performance data collection. We implement a tool-set based on our approach and integrate it with the Lightweight Distributed Metric Service (LDMS) system, a monitoring system used on large-scale computational platforms. LDMS provides the infrastructure to create and gather streams of performance data in a low overhead manner. We demonstrate our approach using applications implemented with MPI, as it is one of the most common standards for the development of large-scale scientific applications. We utilize our tool-set to study the impact of our approach on an open source HPC application, Nalu. Our tool-set enables us to efficiently identify patterns in the behavior of the application without source-level knowledge. We leverage LDMS to collect system-level performance data and explore the correlation between the system and application events. Finally, we demonstrate how our tool-set can help detect anomalies with a low latency. We run tests on two different architectures: a system enabled with Intel Xeon Phi and another system equipped with Intel Xeon processor. Our overhead study shows our method imposes at most 0.5% CPU usage overhead on the application in realistic deployment scenarios.
Madan M. Rehani, Massachusetts General Hospital and Harvard Medical School, Boston Methods for Eye Lens Dosimetry and Studies On Lens Opacities with Interventionalists Radiation induced cataract is a major threat among staff working in interventional suites. Nearly 16 million interventional procedures are performed annually in USA. Recent studies by the principal investigator’s group, primarily among interventional cardiologists, on behalf of the International Atomic Energy Agency, show posterior subcapsular (PSC) changes in the eye lens in 38–53% of main operators and 21–45% of support staff. These changes have potential to lead to cataract in future years, as per information from A-Bomb survivors. The International Commission on Radiological Protection has reduced dose limit for staff by a factor of 7.5 (from 150 mSv/y to 20 mSv/y). With increasing emphasis on radiation induced cataracts and reduction in threshold dose for eye lens, there is a need to implement strategies for estimating eye lens dose. Unfortunately eye lens dosimetry is at infancy when it comes to routine application. Various approaches are being tried namely direct measurement using active or passive dosimeters kept close to eyes, retrospective estimations and lastly correlating patient dose in interventional procedures with staff eye dose. The talk will review all approaches available and ongoing active research in this area, as well as data from surveys done in Europe on status of eye dose monitoring in interventional radiology and nuclear medicine. The talk will provide update on how good is Hp(10) against Hp(3), estimations from CTDI values, Monte Carlo based simulations and current status of eye lens dosimetry in USA and Europe. The cataract risk among patients is in CT examinations of the head. Since radiation induced cataract predominantly occurs in posterior sub-capsular (PSC) region and is thus distinguishable from age or drug related cataracts and is also preventable, actions on awareness can lead to avoidance or even prevention. Learning Objectives: To understand recent changes in eye lens dose limits and thresholds for tissue reactions To understand different approaches to dose estimation for eye lens To learn about challenges in eye lens opacities among staff in interventional fluoroscopy Di Zhang, Toshiba America Medical Systems, Tustin, CA, USA Eye lens radiation dose from brain perfusion CT exams CT perfusion imaging requires repeatedly exposing one location of the head to monitor the uptake and washout of iodinated contrast. The accumulated radiation dose to the eye lens can be high, leading to concerns about potential radiation injury from these scans. CTDIvol assumes continuous z coverage and can overestimate eye lens dose in CT perfusion scans where the table do not increment. The radiation dose to the eye lens from clinical CT brain perfusion studies can be estimated using Monte Carlo simulation methods on voxelized patient models. MDCT scanners from four major manufacturers were simulated and the eye lens doses were estimated using the AAPM posted clinical protocols. They were also compared to CTDIvol values to evaluate the overestimation from CTDIvol. The efficacy of eye lens dose reduction techniques such as tilting the gantry and moving the scan location away from the eyelens were also investigated. Eye lens dose ranged from 81 mGy to 279 mGy, depending on the scanner and protocol used. It is between 59% and 63% of the CTDIvol values reported by the scanners. The eye lens dose is significantly reduced when the eye lenses were not directly irradiated. CTDIvol should not be interpreted as patient dose; this study has shown it to overestimate dose to the eye lens. These results may be used to provide more accurate estimates of actual dose to ensure that protocols are operated safely below thresholds. Tilting the gantry or moving the scanning region further away from the eyes are effective for reducing lens dose in clinical practice. These actions should be considered when they are consistent with the clinical task and patient anatomy. Learning Objectives: To become familiar with method of eye dose estimation for patient in specific situation of brain perfusion CT To become familiar with level of eye lens radiation doses in patients undergoing brain perfusion MDCT To understand methods for reducing eye lens dose to patient Jong Min Park, Department of Radiation Oncology, Seoul National University Hospital, Seoul, Korea Eye lens dosimetry in radiotherapy using contact lens-shaped applicator Dose calculation accuracy of commercial treatment planning systems is relatively low at shallow depths. Therefore, in-vivo measurements are often performed in the clinic to verify delivered doses to eye lens which are located at shallow depth. Current in-vivo dosimetry for eye lens during radiotherapy is generally performed with small in-vivo dosimeters on the surface of patient eyelid. Since this procedure potentially contains considerable uncertainty, a contact lens-shaped applicator made of acrylic (lens applicator) was developed for in-vivo measurements of eye lens dose during radiotherapy to reduce uncertainty. The lens applicator allows the insertion of commercially available metal oxide semiconductor field effect transistor (MOSFET) dosimeters. Computed tomography (CT) images of an anthropomorphic phantom with and without the lens applicator were acquired. A total of 20 VMAT plans were delivered to an anthropomorphic phantom and the doses with the lens applicator and the doses at the surface of the eyelid were measured using both micro and standard MOSFET dosimeters. The differences in measured dose at the surface of the eyelid from the calculated lens dose were acquired. The differences between the measured and the calculated doses at the lens applicator, as well as the differences between the measured and the calculated doses at the surface of the eyelid were acquired. The statistical significance of the differences was analyzed. The average difference between the measured and the calculated dose with the lens applicator was 16.8 % ± 10.4 % with a micro MOSFET dosimeter and 16.6 % ± 10.9% with a standard MOSFET dosimeter. The average difference without the lens applicator was 35.9% ± 41.5% with micro MOSFET dosimeter and 42.9% ± 52.2% with standard MOSFET dosimeter. The maximum difference with micro MOSFET dosimeter was 46% with the applicator and 188.4% without the applicator. For the standard MOSFET dosimeter, the maximum difference was 44.4% with the applicator and 246.4% without the applicator. The lens applicator allowed reduction of the differences between the calculated and the measured dose during in-vivo measurement for the eye lens as compared to in-vivo measurement at the surface of the eyelid. Learning Objectives: To understand limitations of dose calculation with commercial treatment planning system for eye lens during radiotherapy To learn about current in-vivo dosimetry methods for eye lens in the clinic To understand limitations of in-vivo dosimetry for eye lens during radiotherapy Di Zhang is an employee of Toshiba America Medical Systems.
The complexity of petascale and exascale machines makes it increasingly difficult to develop applications that can take advantage of them. Future systems are expected to feature billion-way parallelism, complex heterogeneous compute nodes and poor availability of memory (Peter Kogge, 2008). This new challenge for application development is motivating a significant amount of research and development on new programming models and runtime systems designed to simplify large-scale application development. Unfortunately, DoE has significant multi-decadal investment in a large family of mission-critical scientific applications. Scaling these applications to exascale machines will require a significant investment that will dwarf the costs of hardware procurement. A key reason for the difficulty in transitioning today's applications to exascale hardware is their reliance on explicit programming techniques, such as the Message Passing Interface (MPI) programming model to enable parallelism. MPI provides a portable and high performance message-passing system that enables scalable performance on a wide variety of platforms. However, it also forces developers to lock the details of parallelization together with application logic, making it very difficult to adapt the application to significant changes in the underlying system. Further, MPI's explicit interface makes it difficult to separate the application's synchronization and communication structure, reducing the amount of support that can be provided by compiler and run-time tools. This is in contrast to the recent research on more implicit parallel programming models such as Chapel, OpenMP and OpenCL, which promise to provide significantly more flexibility at the cost of reimplementing significant portions of the application. We are developing CoMPI, a novel compiler-driven approach to enable existing MPI applications to scale to exascale systems with minimal modifications that can be made incrementally over the application's lifetime. It includes: (1) New set of source code annotations, inserted either manually or automatically, that will clarify the application's use of MPI to the compiler infrastructure, enabling greater accuracy where needed; (2) A compiler transformation framework that leverages these annotations to transform the original MPI source code to improve its performance and scalability; (3) Novel MPI runtime implementation techniques that will provide a rich set of functionality extensions to be used by applications that have been transformed by our compiler; and (4) A novel compiler analysis that leverages simple user annotations to automatically extract the application's communication structure and synthesize most complex code annotations.
Several tools have emerged in recent years to increase data exchange and transparency in the distributed generation interconnection process with the goal of reducing interconnection costs. One example is pre-application reports. These reports are generated by a utility at the request of prospective interconnection applicants to provide technical information about a specific point of interconnection. Formal pre-application report processes have been established in 12 states at the distribution system level as well as at the transmission level by the Federal Energy Regulatory Commission. These reports are a relatively low-cost method of informing applicants of grid conditions and potential interconnection limitations early in the interconnection process. Thus, this information may encourage interconnection in locations with little to no detrimental impact to the grid and low interconnection costs. Increasing transparency of these grid conditions may also enable applicants to better plan for interconnection costs and requirements, such as system modifications and complex engineering studies. By providing these benefits, pre-application reports are expected to reduce the number of canceled interconnection applications. This report evaluates this hypothesis by quantifying the impact pre-application report processes have on application approval rate. To evaluate this hypothesis this analysis uses utility-reported distributed generation interconnection data from four utilities in Massachusetts. The analysis considers a four-year time period before and a five-year period after pre-application report process were implemented. The results indicate that once pre-application reports were required for projects 500 kilowatts and larger the approval rate of applications increased by 24%. This suggests that pre-application reports may decrease the percentage of canceled projects. However, due to data and other limitations, these results do not necessarily connote causation. This analysis is an important first step and a prerequisite for future analyses regarding the impact of pre-application reports. Other potential impacts also recognized during this analysis included reducing sunk costs and reducing the number of projects requiring a complex review. Collection of additional data would allow for forming more robust conclusions about these impacts in the future. Such data include circuit-level data, interconnection cost data, policy and regulatory background, national-level data, and utility and developer attributes. These data provide necessary context to account for interrelated factors while evaluating pre-application reports. Filling such knowledge gaps ultimately aids regulators in applying best practices within the industry. As more and more distributed energy resources are interconnected, these best practices will become an integral aspect of efficiently transitioning to an electric grid capable of meeting the needs of the 21st century.
Purpose: To develop a High Dose Rate Brachytherapy (HDR-BT) quality assurance (QA) tool for verification of source position with Oncentra applicator modeling, and to report the results of radiation source positions with this tool. Methods: We developed a HDR-BT QA phantom and automated analysis software for verification of source position with Oncentra applicator modeling for the Fletcher applicator used in the MicroSelectron HDR system. This tool is intended for end-to-end tests that mimic the clinical 3D image-guided brachytherapy (3D-IGBT) workflow. The phantom is a 30x30x3 cm cuboid phantom with radiopaque markers, which are inserted into the phantom to evaluate applicator tips and reference source positions; positions are laterally shifted 10 mm from the applicator axis. The markers are lead-based and scatter radiation to expose the films. Gafchromic RTQA2 films are placed on the applicators. The phantom includes spaces to embed the applicators. The source position is determined as the distance between the exposed source position and center position of two pairs of the first radiopaque markers. We generated a 3D-IGBT plan with applicator modeling. The first source position was 6 mm from the applicator tips, and the second source position was 10 mm from the first source position. Results: All source positions were consistent with the exposed positions within 1 mm for all Fletcher applicators using in-house software. Moreover, the distance between source positions was in good agreement with the reference distance. Applicator offset, determined as the distance from the applicator tips at the first source position in the treatment planning system, was accurate. Conclusion: Source position accuracy of applicator modeling used in 3D-IGBT was acceptable. This phantom and software will be useful as a HDR-BT QA tool for verification of source position with Oncentra applicator modeling.
Objective: The Wearable Sensor Application developed by Pacific Northwest National Laboratory (PNNL) provides an early warning system for stressors to individual and group health using physiologic and environmental indicators. The application integrates health monitoring parameters from wearable sensors, e.g., temperature and heart rate, with relevant environmental parameters, e.g., weather and landscape data, and calculates the corresponding physiological strain index. The information is presented to the analyst in a group and individual view with real-time alerting of abnormal health parameters. This application is the first of its kind being developed for integration into the Defense Threat Reduction Agency's Biosurveillance Ecosystem (BSVE).Introduction: Wearable devices are a low cost, minimally invasive way to monitor health. Sensor data provides real-time physiological indictors of an individual’s health status without the requirement of health care professionals or facilities. Information gleamed from wearable sensors can be used to better understand physiological stressors and prodromal symptoms. In addition, this data can be used to monitor individuals that are in high risk of health-related problems.However, raw data from wearable sensors can be overwhelming to process and laborious to monitor for an individual and, even more so, for a group of individuals. Often specific combination of ranges of sensor readings are indicative of changes to health status and need to be evaluated together or used to calculate specific signal parameters. In addition, the environment surrounding the individual needs to be considered when interpreting the data. To address these issues, PNNL has developed an application that collects, analyzes, and integrates wearable sensor data with geographic landscape and weather information to provide a real-time early alert and situational awareness tool for monitoring the health of groups and individuals.Methods: The prototype application described here was a product of PNNL’s BSVE Application Development Competition. The final product that will be deployed in the BSVE is currently under development by PNNL and will vary slightly in the exact design and architecture described.Data. Wearable sensor data was collected from the Rim2Rim (R2R) Watch Study of individuals hiking the Grand Canyon in Arizona [1]. Weather information was obtained from nearby weather stations and mapping features were derived from Google Maps.Calculations. A physiological Strain Index (PSI) was calculated using core temperature estimates derived through a Kalman Filter approach and heart rate [2,3].Application. The prototype backend application development was based in Python with a MongoDB. The front-end development was built using a scalable architecture and modular approach with components in React and D3.Results: A prototype application was developed this past summer through the PNNL BSVE App Competition (Fig 1). The application was aimed at visualizing wearable sensor data from the Grand Canyon R2R hike dataset. Simulated real-time analysis was used to calculate health status of individuals hiking based on measured physiological parameters and to alert to individuals with signs of physiologic health stress. Visualization tools were incorporated to enable sensor data for individuals and the group to be viewed simultaneously along with pertinent weather, geographic, and elevation data.Many features described in the prototype application will be incorporated into the final BSVE application. The key changes will be 1) the ability to select given time periods for viewing historical data as well as the real-time data collection, 2) environmental data and map view will come from BSVE internal data sources, and 3) the alerts will provide more information and have their own page for reviewing.Conclusions: The Wearable Sensor Application developed by PNNL for integration into the BSVE provides an early warning system for individual and group health using physiologic and environmental parameters. The application highlights health status from wearable sensors and relevant environmental parameters while monitoring a calculated physiological strain index. With this tool, an analyst can easily monitor the health of individuals and groups with the aid of real-time alerting tool for early detection of abnormal health parameters.
Modern scientific applications are complicated and require coordination of several components. Proxy application driven software-hardware co-design plays a vital role in driving innovation among the developments of applications, software infrastructure and hardware architecture. Proxy applications are self-contained and simplified codes that are intended to model the performance-critical computations within applications. Applications executing on modern High Performance Computing (HPC) systems are susceptible to network congestion, insufficient memory bandwidth within and across compute nodes, and inadvertent loss of performance due to bugs and unoptimized programming models. Modern numerical simulations and machine learning models play a critical role in studying physical phenomenon under myriad uncertainties. Such applications often exhibit irregular computation and memory accesses at specific regions of the application code, which can contribute to various performance bottlenecks at scale. To mitigate such issues and prepare the next generation hardware for a variety of computation and data movement contingencies, a well-known practice is to consider "proxy" applications as representative motifs for various classes of scientific applications. While there is disagreement in the HPC community on the mechanisms of construction of the proxy applications, there is a strong consensus on their positive impact in co-design. Proxy Applications for Converged Workloads (PACER) is about facilitating software-hardware co-design through proxy applications with the goal of improving the performance of converged science workflows on heterogeneous systems.
Purpose: To examine CT metal image artifact from a novel direction-modulated brachytherapy (DMBT) tandem applicator (95% tungsten) for cervical cancer using a commercially available orthopedic metal artifact reduction (O-MAR) algorithm. Comparison to a conventional stainless steel applicator is also performed. Methods: Each applicator was placed in a water-filled phantom resembling the female pelvis and scanned in a Philips Brilliance 16-slice CT scanner using two pelvis protocols: a typical clinical protocol (120kVp, 16×0.75mm collimation, 0.692 pitch, 1.0s rotation, 350mm field of view (FOV), 600mAs, 1.5mm slices) and a protocol with a higher kVp and mAs setting useful for larger patients (140kVp, 16×0.75mm collimation, 0.688 pitch, 1.5s rotation, 350mm FOV, 870mAs, 1.5mm slices). Images of each tandem were acquired with and without the application of the O-MAR algorithm. Baseline scans of the phantom (no applicator) were also collected. CT numbers were quantified at distances from 5 to 30 mm away from the applicator’s edge (in increments of 5mm) using measurements at eight angles around the applicator, on three consecutive slices. Results: While the presence of both applicators degraded image quality, the DMBT applicator resulted in larger streaking artifacts and dark areas in the image compared to the stainless steel applicator. Application of the O-MAR algorithm improved all acquired images, both visually and quantitatively. The use of low and high kVp and mAs settings (120 kVp/600mAs and 140 kVp/870mAs) in conjunction with the O-MAR algorithm lead to similar CT numbers in the vicinity of the applicator and a similar reduction of the induced metal artifact. Conclusion: This work indicated that metal artifacts induced by the DMBT and the stainless steel applicator are greatly reduced when using the O-MAR algorithm, leading to better quality phantom images. The use of a high dose protocol provided similar improvements in metal artifacts compared to the clinical protocol.