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DOE OSTI2015

TU-F-201-03: Applications in Brachytherapy

Since the introduction of radiochromic films (RCF) for radiation dosimetry, the scope of RCF dosimetry has expanded steadily to include many medical applications, such as radiation therapy and diagnostic radiology. The AAPM Task Group (TG) 55 published a report on the recommendations for RCF dosimetry in 1998. As the technology is advancing rapidly, and its routine clinical use is expanding, TG 235 has been formed to provide an update to TG-55 on radiochromic film dosimetry. RCF dosimetry applications in clinical radiotherapy have become even more widespread, expanding from primarily brachytherapy and radiosurgery applications, and gravitating towards (but not limited to) external beam therapy (photon, electron and protons), such as quality assurance for IMRT, VMAT, Tomotherapy, SRS/SRT, and SBRT. In addition, RCF applications now extend to measurements of radiation dose in particle beams and patients undergoing medical exams, especially fluoroscopically guided interventional procedures and CT. The densitometers/scanners used for RCF dosimetry have also evolved from the He-Ne laser scanner to CCD-based scanners, including roller-based scanner, light box-based digital camera, and flatbed color scanner. More recently, multichannel RCF dosimetry introduced a new paradigm for external beam dose QA for its high accuracy and efficiency. This course covers in detail the recent advancements in RCF dosimetry. Learning Objectives: Introduce the paradigm shift on multichannel film dosimetry Outline the procedures to achieve accurate dosimetry with a RCF dosimetry system Provide comprehensive guidelines on RCF dosimetry for various clinical applications One of the speakers has a research agreement from Ashland Inc., the manufacturer of Gafchromic film.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-F-201-04: Applications in Small Fields and Proton Beams

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Technical Note: Dosimetry of Leipzig and Valencia applicators without the plastic cap

Purpose: High dose rate (HDR) brachytherapy for treatment of small skin lesions using the Leipzig and Valencia applicators is a widely used technique. These applicators are equipped with an attachable plastic cap to be placed during fraction delivery to ensure electronic equilibrium and to prevent secondary electrons from reaching the skin surface. The purpose of this study is to report on the dosimetric impact of the cap being absent during HDR fraction delivery, which has not been explored previously in the literature. Methods: GEANT4 Monte Carlo simulations (version 10.0) have been performed for the Leipzig and Valencia applicators with and without the plastic cap. In order to validate the Monte Carlo simulations, experimental measurements using radiochromic films have been done. Results: Dose absorbed within 1 mm of the skin surface increases by a factor of 1500% for the Leipzig applicators and of 180% for the Valencia applicators. Deeper than 1 mm, the overdosage flattens up to a 10% increase. Conclusions: Differences of treating with or without the plastic cap are significant. Users must check always that the plastic cap is in place before any treatment in order to avoid overdosage of the skin. Prior to skin HDR fraction delivery, the timeout checklist should include verification of the cap placement.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-80: A Mobile Application for Intra-Operative Electron Radiotherapy Treatment Planning

Purpose: Intraoperative electron radiotherapy (IORT) poses a unique set of challenges for treatment planning. Planning must be performed in a busy operating room environment over a short timeframe often with little advance knowledge of the treatment depth or applicator size. Furthermore, IORT accelerators can have a large number of possible applicators, requiring extensive databooks that must be searched for the appropriate dosimetric parameters. The goal of this work is to develop a software tool to assist in the planning process that is suited to the challenges faced in the IORT environment. Methods: We developed a mobile application using HTML5 and Javascript that can be deployed to tablet devices suitable for use in the operating room. The user selects the desired treatment parameters cone diameter, bevel angle, and energy (a total of 141 datasets) and desired bolus. The application generates an interactive display that allows the user to dynamically select points on the depth-dose curve and to visualize the shape of the corresponding isodose contours. The user can indicate a prescription isodose line or depth. The software performs a monitor unit calculation and generates a PDF report. Results: We present our application, which is now used routinely in our IORT practice. It has been employed successfully in over 23 cases. The interactivity of the isodose distributions was found to be of particular use to physicians who are less-frequent IORT users, as well as for the education of residents and trainees. Conclusion: This software has served as a useful tool in IORT planning, and demonstrates the need for treatment planning tools that are designed for the specialized challenges encountered in IORT. This software is the subject of a license agreement with the IntraOp Medical Corporation. This software is the subject of a license agreement between Massachusetts General Hospital / Partners Healthcare and the IntraOp Medical Corporation. CLW is consulting on software development with the IntraOp Medical Corporation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-A-BRC-00: TG167: Clinical Recommendations for Innovative Brachytherapy Devices and Applicators

Although a multicenter, Phase III, prospective, randomized trial is the gold standard for evidence-based medicine, it is rarely used to evaluate innovative radiotherapy devices because of many practical and ethical reasons. It is usually sufficient to compare the dose distributions and dose rates for determining equivalence of the innovative device to an existing one. Thus, quantitative evaluation of the dosimetric characteristics of an innovative brachytherapy device or application is a critical part in which physicists are actively involved. The physicist’s role, along with physician colleagues, in this process is highlighted for innovative products or applications and includes evaluation of 1) dosimetric considerations for clinical implementation (including calibrations, dose calculations, and radiobiological aspects) to comply with existing societal dosimetric prerequisites for sources in routine clinical use, 2) risks and benefits from regulatory and safety perspectives, and 3) resource assessment and preparedness. Further, calibration methods should be traceable to a primary standards dosimetry laboratory such as NIST in the U.S. or to other primary standards dosimetry laboratory located elsewhere. Clinical users should follow standards as approved by their country’s regulatory agencies that approved such a brachytherapy device. Integration of this system into the medical source calibration infrastructure of secondary standard dosimetry laboratories such as the ADCLs is encouraged before a source is introduced into widespread routine clinical use. The AAPM and GEC-ESTRO have developed guidelines for the safe and consistent application of brachytherapy using innovative brachytherapy devices and applications. The current report covers regulatory approvals, calibration, dose calculations, radiobiological issues, and overall safety concerns that should be addressed during the commissioning stage preceding clinical use. These guidelines are based on review of requirements of the U.S. NRC, FDA, Department of Transportation, International Electrotechnical Commission Medical Electrical Equipment Standard 60601, European Commission for CE Marking, and institutional review boards and radiation safety committees. Learning Objectives: Understand the necessary dosimetric considerations for clinical implementation (including calibrations, dose calculations, and radiobiological aspects) to comply with existing societal dosimetric prerequisites for sources in routine clinical use. Evaluate risks and benefits from regulatory and safety perspectives. Identify necessary resources and create a plan for clinical introduction of innovative brachytherapy device or applications. Consultant for Theragenics Corp.; R. Nath, Consultant to Theragenics Corp.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-AB-207A-03: Image Quality, Dose, and Clinical Applications

Practicing medical physicists are often time charged with the tasks of evaluating and troubleshooting complex image quality issues related to CT scanners. This course will equip them with a solid and practical understanding of common CT imaging chain and its major components with emphasis on acquisition physics and hardware, reconstruction, artifacts, image quality, dose, and advanced clinical applications. The core objective is to explain the effects of these major system components on the image quality. This course will not focus on the rapid-changing advanced technologies given the two-hour time limit, but the fundamental principles discussed in this course may facilitate better understanding of those more complicated technologies. The course will begin with an overview of CT acquisition physics and geometry. X-ray tube and CT detector are important acquisition hardware critical to the overall image quality. Each of these two subsystems consists of several major components. An in-depth description of the function and failure modes of these components will be provided. Examples of artifacts related to these failure modes will be presented: off-focal radiation, tube arcing, heel effect, oil bubble, offset drift effect, cross-talk effect, and bad pixels. The fundamentals of CT image reconstruction will first be discussed on an intuitive level. Approaches that do not require rigorous derivation of mathematical formulations will be presented. This is followed by a detailed derivation of the Fourier slice theorem: the foundation of the FBP algorithm. FBP for parallel-beam, fan-beam, and cone-beam geometries will be discussed. To address the issue of radiation dose related to x-ray CT, recent advances in iterative reconstruction, their advantages, and clinical applications will also be described. Because of the nature of fundamental physics and mathematics, limitations in data acquisition, and non-ideal conditions of major system components, image artifact often arise in the reconstructed images. Because of the limited scope of this course, only major imaging artifacts, their appearance, and possible mitigation and corrections will be discussed. Assessment of the performance of a CT scanner is a complicated subject. Procedures to measure common image quality metrics such as high contrast spatial resolution, low contrast detectability, and slice profile will be described. The reason why these metrics used for FBP may not be sufficient for statistical iterative reconstruction will be explained. Optimizing radiation dose requires comprehension of CT dose metrics. This course will briefly describe various dose metrics, and interaction with acquisition parameters and patient habitus. CT is among the most frequently used imaging tools due to its superior image quality, easy to operate, and a broad range of applications. This course will present several interesting CT applications such as a mobile CT unit on an ambulance for stroke patients, low dose lung cancer screening, and single heartbeat cardiac CT. Learning Objectives: Understand the function and impact of major components of X-ray tube on the image quality. Understand the function and impact of major components of CT detector on the image quality. Be familiar with the basic procedure of CT image reconstruction. Understand the effect of image reconstruction on CT image quality and artifacts. Understand the root causes of common CT image artifacts. Be familiar with image quality metrics especially high and low contrast resolution, noise power spectrum, slice sensitivity profile, etc. Understand why basic image quality metrics used for FBP may not be sufficient to characterize the performance of advanced iterative reconstruction. Be familiar with various CT dose metrics and their interaction with acquisition parameters. New development in advanced CT clinical applications. JH: Employee of GE Healthcare. FD: No disclosure.; J. Hsieh, Jiang Hsieh is an employee of GE Healthcare.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Investigating applications portability with the Uintah DAG-based runtime system on PetaScale supercomputers

Present trends in high performance computing present formidable challenges for applications code using multicore nodes possibly with accelerators and/or co-processors and reduced memory while still attaining scalability. Software frameworks that execute machine-independent applications code using a runtime system that shields users from architectural complexities offer a possible solution. The Uintah framework for example, solves a broad class of large-scale problems on structured adaptive grids using fluid-flow solvers coupled with particle-based solids methods. Uintah executes directed acyclic graphs of computational tasks with a scalable asynchronous and dynamic runtime system for CPU cores and/or accelerators/co-processors on a node. Uintah's clear separation between application and runtime code has led to scalability increases of 1000x without significant changes to application code. This methodology is tested on three leading Top500 machines; OLCF Titan, TACC Stampede and ALCF Mira using three diverse and challenging applications problems. This investigation of scalability with regard to the different processors and communications performance leads to the overall conclusion that the adaptive DAG-based approach provides a very powerful abstraction for solving challenging multi-scale multi-physics engineering problems on some of the largest and most powerful computers available today.

Meng, Qingyu↗

DOE OSTI2015

A Case for Application Oblivious Energy-Efficient MPI Runtime

Power has become the major impediment in designing large scale high-end systems. Message Passing Interface (MPI) is the {\em de facto} communication interface used as the back-end for designing applications, programming models and runtime for these systems. Slack --- the time spent by an MPI process in a single MPI call --- provides a potential for energy and power savings, if an appropriate power reduction technique such as core-idling/Dynamic Voltage and Frequency Scaling (DVFS) can be applied without perturbing application's execution time. Existing techniques that exploit slack for power savings assume that application behavior repeats across iterations/executions. However, an increasing use of adaptive, data-dependent workloads combined with system factors (OS noise, congestion) makes this assumption invalid. This paper proposes and implements Energy Aware MPI (EAM) --- an application-oblivious energy-efficient MPI runtime. EAM uses a combination of communication models of common MPI primitives (point-to-point, collective, progress, blocking/non-blocking) and an online observation of slack for maximizing energy efficiency. Each power lever incurs time overhead, which must be amortized over slack to minimize degradation. When predicted communication time exceeds a lever overhead, the lever is used {\em as soon as possible} --- to maximize energy efficiency. When mis-prediction occurs, the lever(s) are used automatically at specific intervals for amortization. We implement EAM using MVAPICH2 and evaluate it on ten applications using up to 4096 processes. Our performance evaluation on an InfiniBand cluster indicates that EAM can reduce energy consumption by 5--41\% in comparison to the default approach, with negligible (less than 4\% in all cases) performance loss.

Venkatesh, Akshay↗

DOE OSTI2017

Python in the NERSC Exascale Science Applications Program for Data

We describe a new effort at the National Energy Re- search Scientific Computing Center (NERSC) in performance analysis and optimization of scientific Python applications targeting the Intel Xeon Phi (Knights Landing, KNL) many- core architecture. The Python-centered work outlined here is part of a larger effort called the NERSC Exascale Science Applications Program (NESAP) for Data. NESAP for Data focuses on applications that process and analyze high-volume, high-velocity data sets from experimental/observational science (EOS) facilities supported by the US Department of Energy Office of Science. We present three case study applications from NESAP for Data that use Python. These codes vary in terms of “Python purity” from applications developed in pure Python to ones that use Python mainly as a convenience layer for scientists without expertise in lower level programming lan- guages like C, C++ or Fortran. The science case, requirements, constraints, algorithms, and initial performance optimizations for each code are discussed. Our goal with this paper is to contribute to the larger conversation around the role of Python in high-performance computing today and tomorrow, highlighting areas for future work and emerging best practices

Ronaghi, Zahra↗

DOE OSTI2018

Sensalert: A Real-time Group and Individual Health Tracking Application

Sensalert is a wearable health tracking application that enables monitoring of a target population’s health status in real-time. The application integrates health monitoring parameters from wearable sensors, e.g., temperature and heart rate, with relevant environmental parameters, e.g., weather and topography, and calculates the corresponding physiological strain index for each point in time. The objective of this application is to provide early warning, support decision making, and increase situational awareness by displaying comprehensive information and providing alerts at the right time and place. This application is the first of its kind being developed for integration into the Defense Threat Reduction Agencies Bio Surveillance Ecosystem (BSVE). We present the user requirements and design principles for developing this type of application. We hope this work helps and inspires future research in the area of wearable technologies for surveillance.

Huang, Zhuanyi↗

DOE OSTI2021

Reconfigurable Framework for Resilient Semantic Segmentation for Space Applications

Deep learning (DL) presents new opportunities for enabling spacecraft autonomy, onboard analysis, and intelligent applications for space missions. However, DL applications are computationally intensive and often infeasible to deploy on radiation-hardened (rad-hard) processors, which traditionally harness a fraction of the computational capability of their commercial-off-the-shelf counterparts. Commercial FPGAs and system-on-chips present numerous architectural advantages and provide the computation capabilities to enable onboard DL applications; however, these devices are highly susceptible to radiation-induced single-event effects (SEEs) that can degrade the dependability of DL applications. In this article, we propose Reconfigurable ConvNet (RECON), a reconfigurable acceleration framework for dependable, high-performance semantic segmentation for space applications. In RECON, we propose both selective and adaptive approaches to enable efficient SEE mitigation. In our selective approach, control-flow parts are selectively protected by triple-modular redundancy to minimize SEE-induced hangs, and in our adaptive approach, partial reconfiguration is used to adapt the mitigation of dataflow parts in response to a dynamic radiation environment. Combined, both approaches enable RECON to maximize system performability subject to mission availability constraints. We perform fault injection and neutron irradiation to observe the susceptibility of RECON and use dependability modeling to evaluate RECON in various orbital case studies to demonstrate a 1.5–3.0× performability improvement in both performance and energy efficiency compared to static approaches.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Exploring the Use of Novel Spatial Accelerators in Scientific Applications

Driven by the need to find alternative accelerators which can viably replace GPUs in next-generation Supercomputing systems, this paper proposes a methodology to enable agile application/hardware co-design. The application-first methodology provides the ability to come up with design of accelerators while working with real-world workloads, available accelerators, and system software. The iterative design process targets a set of kernels in a workload for performance estimates that can prune the design space for later phases of detailed architectural evaluations. To this effect, in this paper, a novel data-parallel device model is introduced that simulates the latency of performance-sensitive operations in an accelerator including data transfers and kernel computation using multi-core CPUs. The use of off-the-shelf simulators, such as pre-RTL simulator Aladdin or multiple tools available for exploring the design of deep neural network accelerators (e.g., Timeloop) is demonstrated for evaluation of various accelerator designs using applications with realistic inputs. Examples of multiple device configurations that are instantiable in a system are explored to evaluate the performance benefit of deploying novel accelerators. The proposed device is integrated with a programming model and system software to potentially explore the impacts of high-level programming languages/compilers and low-level effects such as task scheduling on multiple accelerators. We analyze our methodology for a set of applications that represent high-performance computing (HPC) and graph analytics. The applications include a computational chemistry kernel realized using tensor contractions, triangle counting, GraphSAGE and Breadth-first Search. These applications include kernels such as dense matrix-dense matrix multiplication, sparse matrix-spare matrix multiplication, and sparse matrix-dense vector multiplication. Our results indicate potential performance benefits and insights for system design by including accelerators that realize these kernels along-side general purpose accelerators.

AI, codesign, Accelerated Computing, Modeling and ↗

DOE OSTI2023

Is Knowledge about Running Applications Helping Improve Runtime Prediction of HPC Jobs?

High-performance computing systems rely upon scheduling algorithms to achieve high utilization. These schedulers rely upon user estimates of job resource requirements, such as runtime, to determine optimal scheduling of incoming jobs. These user estimates, however, are prone to error. To mitigate this error, significant research has been directed at providing better estimates of job runtime, usually employing machine learning techniques. These techniques are dependent upon the input features selected. Among the possible features is the primary application used by the job. In a survey of more than 20 papers directed at improving runtime prediction, only four included primary application as an input feature. We focus this investigation specifically on the value of adding primary application as an input feature, and find that it does improve model performance, especially for jobs with longer runtimes, though this improvement varies based on the application used. We recommend further research to determine the cause of this variability as well as an optimal strategy for employing a mixture of models both including and not including primary application as a feature.

MATHEMATICS AND COMPUTING↗

DOE OSTI2023

SeeQ: A Programming Model for Portable Data-Driven Building Applications

This paper introduces SeeQ, a programming model and an abstraction framework that facilitates the development of portable data- driven building applications. Data-driven approaches can provide insights into building operations and guide decision-making to achieve operational objectives. Yet the configuration of such applications per building requires extensive effort and tacit knowledge. In SeeQ, we propose a portable programming model and build a software system that enables self-configuration and execution across diverse buildings. The configuration of each building is captured in a unified data model - in this paper, we work with the Brick ontology without loss of generality. SeeQ focuses on the distinction between the application logic and the configuration of an application against building-specific data inputs and systems. We test the proposed approach by configuring and deploying a diverse range of applications across five heterogeneous real-world buildings. The analysis shows the potential of SeeQ to significantly reduce the efforts associated with the delivery of building analytics.

analytics↗

DOE OSTI2024

Studying CPU and memory utilization of applications on Fujitsu A64FX and Nvidia Grace Superchip

ARM-based manycore CPU architectures are well-positioned to provide the rising memory throughput requirements of modern data intensive scientific applications in High Performance Computing (HPC). The Fujitsu A64FX CPU platform is based on the ARM v8.2A architecture, and is the processor of the flagship Japanese supercomputer - "Fugaku", which was previously ranked as the #1 supercomputer in the world according to the Top500 list. The Nvidia Grace superchip features 144 Neoverse V2 cores based on the ARMv9 architecture with 4x128b SVE2, providing exceptional computational power. The chip supports up to 480GB of memory, making it ideal for AI, machine learning, and scientific computing workloads. In this paper, we conduct a thorough performance exploration of a variety of parallel bandwidth-sensitive benchmarks and applications compiled with the native Fujitsu compiler on a Fugaku A64FX compute node and ARM (LLVM) Compiler on an NVIDIA Grace superchip compute node, engaging all the computational cores per cluster using OpenMP multithreading (assuming the cores can drive the available bandwidth). Our ultimate goals are to study the resource utilization of scientific applications and benchmarks on A64FX and Grace superchip, considering graph application scenarios ( GAP Benchmark suite) and eleven appli- cation proxies from the Rodinia heterogeneous benchmark suite (considering domains such as Data Mining, Bioinformatics, Fluid Dynamics, Pattern Recognition, etc.). Through exhaustive performance monitoring, we quantify the resource utilization of diverse OpenMP-based HPC applications on both the Fujitsu A64FX and the Nvidia Grace Superchip platforms.

benchmarking, Performance Analysis, High performan↗

DOE OSTI2018

Critical Review of Fluid Flow Physics at Micro‐ to Nano‐scale Porous Media Applications in the Energy Sector

While there is a consensus in the literature that embracing nanodevices and nanomaterials helps in improving the efficiency and performance, the reason for the better performance is mostly subscribed to the nanosized material/structure of the system without sufficiently acknowledging the role of fluid flow mechanisms in these systems. This is evident from the literature review of fluid flow modeling in various energy‐related applications, which reveals that the fundamental understanding of fluid transport at micro‐ and nanoscale is not adequately adapted in models. Incomplete or insufficient physics for the fluid flow can lead to untapped potential of these applications that can be used to increase their performance. This paper reviews the current state of research for the physics of gas and liquid flow at micro‐ and nanoscale and identified critical gaps to improve fluid flow modeling in four different applications related to the energy sector. The review for gas flow focuses on fundamentals of gas flow at rarefied conditions, the velocity slip, and temperature jump conditions. The review for liquid flow provides fundamental flow regimes of liquid flow, and liquid slip models as a function of key modeling parameters. The four porous media applications from energy sector considered in this review are (i) electrokinetic energy conversion devices, (ii) membrane‐based water desalination through reverse osmosis, (iii) shale reservoirs, and (iv) hydrogen storage, respectively. Review of fluid flow modeling literature from these applications reveals that further improvements can be made by (i) modeling slip length as a function of key parameters, (ii) coupling the dependency of wettability and slip, (iii) using a reservoir‐on‐chip approach that can enable capturing the subcontinuum effects contributing to fluid flow in shale reservoirs, and (iv) including Knudsen diffusion and slip in the governing equations of hydrogen gas storage.

Singh, Harpreet (ORCID:0000000276185764)↗

DOE OSTI2013

Multiphysics Application Coupling Toolkit

This particular consortium implementation of the software integration infrastructure will, in large part, refactor portions of the Rocstar multiphysics infrastructure. Development of this infrastructure originated at the University of Illinois DOE ASCI Center for Simulation of Advanced Rockets (CSAR) to support the center's massively parallel multiphysics simulation application, Rocstar, and has continued at IllinoisRocstar, a small company formed near the end of the University-based program. IllinoisRocstar is now licensing these new developments as free, open source, in hopes to help improve their own and others' access to infrastructure which can be readily utilized in developing coupled or composite software systems; with particular attention to more rapid production and utilization of multiphysics applications in the HPC environment. There are two major pieces to the consortium implementation, the Application Component Toolkit (ACT), and the Multiphysics Application Coupling Toolkit (MPACT). The current development focus is the ACT, which is (will be) the substrate for MPACT. The ACT itself is built up from the components described in the technical approach. In particular, the ACT has the following major components: 1.The Component Object Manager (COM): The COM package provides encapsulation of user applications, and their data. COM also provides the inter-component function call mechanism. 2.The System Integration Manager (SIM): The SIM package provides constructs and mechanisms for orchestrating composite systems of multiply integrated pieces.

Campbell, MichaelT.↗

DOE OSTI2023

Inl Open Ondemand Applications

Open OnDemand is a software tool that is used to access HPC resources. It provides a framework for organizations to create apps and other additional functionality that may be useful to the organization. This code expands upon the pre-existing INL applications, including the NEAMS Workbench application, MOOSE Herd applications, and others. These changes significantly expand upon the functionality originally provided. Due to the extensive functionality that we added, these changes would not be added to the original application but would function as a standalone application that other organizations would be able to utilize on their own systems.

Biggs, BrandonS.↗