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DOE OSTI2021

New Orthophoto Generation Strategies from UAV and Ground Remote Sensing Platforms for High-Throughput Phenotyping

Remote sensing platforms have become an effective data acquisition tool for digital agriculture. Imaging sensors onboard unmanned aerial vehicles (UAVs) and tractors are providing unprecedented high-geometric-resolution data for several crop phenotyping activities (e.g., canopy cover estimation, plant localization, and flowering date identification). Among potential products, orthophotos play an important role in agricultural management. Traditional orthophoto generation strategies suffer from several artifacts (e.g., double mapping, excessive pixilation, and seamline distortions). The above problems are more pronounced when dealing with mid- to late-season imagery, which is often used for establishing flowering date (e.g., tassel and panicle detection for maize and sorghum crops, respectively). In response to these challenges, this paper introduces new strategies for generating orthophotos that are conducive to the straightforward detection of tassels and panicles. The orthophoto generation strategies are valid for both frame and push-broom imaging systems. The target function of these strategies is striking a balance between the improved visual appearance of tassels/panicles and their geolocation accuracy. The new strategies are based on generating a smooth digital surface model (DSM) that maintains the geolocation quality along the plant rows while reducing double mapping and pixilation artifacts. Moreover, seamline control strategies are applied to avoid having seamline distortions at locations where the tassels and panicles are expected. The quality of generated orthophotos is evaluated through visual inspection as well as quantitative assessment of the degree of similarity between the generated orthophotos and original images. Several experimental results from both UAV and ground platforms show that the proposed strategies do improve the visual quality of derived orthophotos while maintaining the geolocation accuracy at tassel/panicle locations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Accelerating network layouts using graph neural networks

Graph layout algorithms used in network visualization represent the first and the most widely used tool to unveil the inner structure and the behavior of complex networks. Current network visualization software relies on the force-directed layout (FDL) algorithm, whose high computational complexity makes the visualization of large real networks computationally prohibitive and traps large graphs into high energy configurations, resulting in hard-to-interpret “hairball” layouts. Here we use Graph Neural Networks (GNN) to accelerate FDL, showing that deep learning can address both limitations of FDL: it offers a 10 to 100 fold improvement in speed while also yielding layouts which are more informative. We analytically derive the speedup offered by GNN, relating it to the number of outliers in the eigenspectrum of the adjacency matrix, predicting that GNNs are particularly effective for networks with communities and local regularities. Finally, we use GNN to generate a three-dimensional layout of the Internet, and introduce additional measures to assess the layout quality and its interpretability, exploring the algorithm’s ability to separate communities and the link-length distribution. The novel use of deep neural networks can help accelerate other network-based optimization problems as well, with applications from reaction-diffusion systems to epidemics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Learning stochastic dynamics and predicting emergent behavior using transformers

We show that a neural network originally designed for language processing can learn the dynamical rules of a stochastic system by observation of a single dynamical trajectory of the system, and can accurately predict its emergent behavior under conditions not observed during training. We consider a lattice model of active matter undergoing continuous-time Monte Carlo dynamics, simulated at a density at which its steady state comprises small, dispersed clusters. We train a neural network called a transformer on a single trajectory of the model. The transformer, which we show has the capacity to represent dynamical rules that are numerous and nonlocal, learns that the dynamics of this model consists of a small number of processes. Forward-propagated trajectories of the trained transformer, at densities not encountered during training, exhibit motility-induced phase separation and so predict the existence of a nonequilibrium phase transition. Transformers have the flexibility to learn dynamical rules from observation without explicit enumeration of rates or coarse-graining of configuration space, and so the procedure used here can be applied to a wide range of physical systems, including those with large and complex dynamical generators.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

LLVM Infrastructure and Tools Project Summary

This project works with the open source LLVM Compiler Infrastructure (http://llvm.org) to provide tools and capabilities that address needs and challenges faced by ECP community (applications, libraries, and other components of the software stack). Our focus is on providing a more productive development environment that enables (i) improved compilation times and code generation for parallelism, (ii) additional features/capabilities within the design and implementations of LLVM components for improved platform/performance portability and (iii) improved aspects related to composition of the underlying implementation details of the programming environment, capturing resource utilization, overheads, etc. -- including runtime systems that are often not easily addressed by application and library developers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

LANL ARM Benchmarking Efforts

Overview of LANL ARM benchmarking efforts; ASC application performance on current ARM systems; ARM future technologies investigations; and external collaborations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

SU-E-J-100: The Combination of Deformable Image Registration and Regions-Of-Interest Mapping Technique to Accomplish Accurate Dose Calculation On Cone Beam Computed Tomography for Esophageal Cancer

Purpose: We introduce a new method combined with the deformable image registration (DIR) and regions-of-interest mapping (ROIM) technique to accurately calculate dose on daily CBCT for esophageal cancer. Methods: Patients suffered from esophageal cancer were enrolled in the study. Prescription was set to 66 Gy/30 F and 54 Gy/30 F to the primary tumor (PTV66) and subclinical disease (PTV54) . Planning CT (pCT) were segmented into 8 substructures in terms of their differences in physical density, such as gross target volume (GTV), venae cava superior (SVC), aorta, heart, spinal cord, lung, muscle and bones. The pCT and its substructures were transferred to the MIM software to readout their mean HU values. Afterwards, a deformable planning CT to daily KV-CBCT image registration method was then utilized to acquire a new structure set on CBCT. The newly generated structures on CBCT were then transferred back to the treatment planning system (TPS) and its HU information were overridden manually with mean HU values obtained from pCT. Finally, the treatment plan was projected onto the CBCT images with the same beam arrangements and monitor units (MUs) to accomplish dose calculation. Planning target volume (PTV) and organs at risk (OARs) from both of the pCT and CBCT were compared to evaluate the dose calculation accuracy. Results: It was found that the dose distribution in the CBCT showed little differences compared to the pCT, regardless of whether PTV or OARs were concerned. Specifically, dose variation in GTV, PTV54, PTV66, SVC, lung and heart were within 0.1%. The maximum dose variation was presented in the spinal cord, which was up to 2.7% dose difference. Conclusion: The proposed method combined with DIR and ROIM technique to accurately calculate dose distribution on CBCT for esophageal cancer is feasible.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

A Performance Study of Quantum ESPRESSO’s PWscf Code on Multi-core and GPU Systems

We describe the porting of PWscf (Plane-Wave Self Consistent Field), a key component of the Quantum ESPRESSO open-source suite of codes for materials modeling, to GPU systems using CUDA Fortran. Kernel loop directives (CUF kernels) have been extensively used in order to have a single source code for both CPU and GPU implementations. The results of the GPU version have been carefully validated and the performance of the code on several GPU systems (both x86 and POWER8 based) has been compared with traditional Intel multi-core (CPU only) systems. This current GPU version can reduce the time-to-solution by an average factor of 2–3 running two different input cases widely used as benchmarks on small and large high performance computing systems.

CUDA Fortran↗

DOE OSTI2023

High-dimensional multi-fidelity Bayesian optimization for quantum control

Abstract We present the first multi-fidelity Bayesian optimization (BO) approach for solving inverse problems in the quantum control of prototypical quantum systems. Our approach automatically constructs time-dependent control fields that enable transitions between initial and desired final quantum states. Most importantly, our BO approach gives impressive performance in constructing time-dependent control fields, even for cases that are difficult to converge with existing gradient-based approaches. We provide detailed descriptions of our machine learning methods as well as performance metrics for a variety of machine learning algorithms. Taken together, our results demonstrate that BO is a promising approach to efficiently and autonomously design control fields in general quantum dynamical systems.

Computer Science↗

DOE OSTI2015

SU-E-P-59: A Graphical Interface for XCAT Phantom Configuration, Generation and Processing

Purpose: To design a comprehensive open-source, publicly available, graphical user interface (GUI) to facilitate the configuration, generation, processing and use of the 4D Extended Cardiac-Torso (XCAT) phantom. Methods: The XCAT phantom includes over 9000 anatomical objects as well as respiratory, cardiac and tumor motion. It is widely used for research studies in medical imaging and radiotherapy. The phantom generation process involves the configuration of a text script to parameterize the geometry, motion, and composition of the whole body and objects within it, and to generate simulated PET or CT images. To avoid the need for manual editing or script writing, our MATLAB-based GUI uses slider controls, drop-down lists, buttons and graphical text input to parameterize and process the phantom. Results: Our GUI can be used to: a) generate parameter files; b) generate the voxelized phantom; c) combine the phantom with a lesion; d) display the phantom; e) produce average and maximum intensity images from the phantom output files; f) incorporate irregular patient breathing patterns; and f) generate DICOM files containing phantom images. The GUI provides local help information using tool-tip strings on the currently selected phantom, minimizing the need for external documentation. The DICOM generation feature is intended to simplify the process of importing the phantom images into radiotherapy treatment planning systems or other clinical software. Conclusion: The GUI simplifies and automates the use of the XCAT phantom for imaging-based research projects in medical imaging or radiotherapy. This has the potential to accelerate research conducted with the XCAT phantom, or to ease the learning curve for new users. This tool does not include the XCAT phantom software itself. We would like to acknowledge funding from MRA, Varian Medical Systems Inc.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-A-304-00: Imaging, Treatment Planning, and QA for Stereotactic Body Radiation Therapy (SBRT)

Increased use of SBRT and hypo fractionation in radiation oncology practice has posted a number of challenges to medical physicist, ranging from planning, image-guided patient setup and on-treatment monitoring, to quality assurance (QA) and dose delivery. This symposium is designed to provide updated knowledge necessary for the safe and efficient implementation of SBRT in various linac platforms, including the emerging digital linacs equipped with high dose rate FFF beams. Issues related to 4D CT, PET and MRI simulations, 3D/4D CBCT guided patient setup, real-time image guidance during SBRT dose delivery using gated/un-gated VMAT or IMRT, and technical advancements in QA of SBRT (in particular, strategies dealing with high dose rate FFF beams) will be addressed. The symposium will help the attendees to gain a comprehensive understanding of the SBRT workflow and facilitate their clinical implementation of the state-of-art imaging and planning techniques. Learning Objectives: Present background knowledge of SBRT, describe essential requirements for safe implementation of SBRT, and discuss issues specific to SBRT treatment planning and QA. Update on the use of multi-dimensional (3D and 4D) and multi-modality (CT, beam-level X-ray imaging, pre- and on-treatment 3D/4D MRI, PET, robotic ultrasound, etc.) for reliable guidance of SBRT. Provide a comprehensive overview of emerging digital linacs and summarize the key geometric and dosimetric features of the new generation of linacs for substantially improved SBRT. Discuss treatment planning and quality assurance issues specific to SBRT. Research grant from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-PIS-Exhibit Hall-5: Use of the Enterprise-wide Dose Tracking Software Radimetrics In an Academic Medical System

The current clinical standard of organ respiratory imaging, 4D-CT, is fundamentally limited by poor soft-tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose-volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft-tissue contrast. MRI-based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR-based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D-MRI and MRI hybrid treatment machines (i.e. MR-linac or MR-Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI-based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR-based motion management methods and technologies, the state-of-the-art concerning MRI development and clinical application and the barriers to more widespread adoption. Learning Objectives: Discuss the need of MR-based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-201-00: Practical Guidelines for Commissioning Advanced Brachytherapy Dose Calculation Algorithms

With the recent introduction of heterogeneity correction algorithms for brachytherapy, the AAPM community is still unclear on how to commission and implement these into clinical practice. The recently-published AAPM TG-186 report discusses important issues for clinical implementation of these algorithms. A charge of the AAPM-ESTRO-ABG Working Group on MBDCA in Brachytherapy (WGMBDCA) is the development of a set of well-defined test case plans, available as references in the software commissioning process to be performed by clinical end-users. In this practical medical physics course, specific examples on how to perform the commissioning process are presented, as well as descriptions of the clinical impact from recent literature reporting comparisons of TG-43 and heterogeneity-based dosimetry. Learning Objectives: Identify key clinical applications needing advanced dose calculation in brachytherapy. Review TG-186 and WGMBDCA guidelines, commission process, and dosimetry benchmarks. Evaluate clinical cases using commercially available systems and compare to TG-43 dosimetry.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-D-209-03: Alignment of the Patient Graphic Model Using Fluoroscopic Images for Skin Dose Mapping

Purpose: The Dose Tracking System (DTS) was developed to provide realtime feedback of skin dose and dose rate during interventional fluoroscopic procedures. A color map on a 3D graphic of the patient represents the cumulative dose distribution on the skin. Automated image correlation algorithms are described which use the fluoroscopic procedure images to align and scale the patient graphic for more accurate dose mapping. Methods: Currently, the DTS employs manual patient graphic selection and alignment. To improve the accuracy of dose mapping and automate the software, various methods are explored to extract information about the beam location and patient morphology from the procedure images. To match patient anatomy with a reference projection image, preprocessing is first used, including edge enhancement, edge detection, and contour detection. Template matching algorithms from OpenCV are then employed to find the location of the beam. Once a match is found, the reference graphic is scaled and rotated to fit the patient, using image registration correlation functions in Matlab. The algorithm runs correlation functions for all points and maps all correlation confidences to a surface map. The highest point of correlation is used for alignment and scaling. The transformation data is saved for later model scaling. Results: Anatomic recognition is used to find matching features between model and image and image registration correlation provides for alignment and scaling at any rotation angle with less than onesecond runtime, and at noise levels in excess of 150% of those found in normal procedures. Conclusion: The algorithm provides the necessary scaling and alignment tools to improve the accuracy of dose distribution mapping on the patient graphic with the DTS. Partial support from NIH Grant R01-EB002873 and Toshiba Medical Systems Corp.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Scalable molecular dynamics with NAMD on the Summit system

According to the article, NAnoscale Molecular Dynamics (NAMD) is a parallel molecular dynamics application that has been used to make breakthroughs in understanding the structure and dynamics of large biomolecular complexes, such as viruses like HIV and various types of influenza. State-of-the-art biomolecular simulations often require integration of billions of timesteps, computing all interatomic forces for each femtosecond timestep. Molecular dynamics simulation of large biomolecular systems and long-timescale biological phenomena requires tremendous computing power. NAMD harnesses the power of thousands of heterogeneous processors to meet this demand. In this paper, we present algorithmic improvements and performance optimizations that enable NAMD to achieve high performance on the IBM Newell platform (with IBM POWER9 processors and NVIDIA Volta V100 GPUs), which underpins the Oak Ridge National Laboratory's Summit and Lawrence Livermore National Laboratory's Sierra supercomputers. The Top-500 supercomputers November 2018 list shows Summit at the number one spot, with 200 petaflop/s peak performance, and Sierra second with 125 petaflop/s. Optimizations for NAMD on Summit include: data layout changes for GPU acceleration and CPU vectorization, improving GPU offload efficiency, increasing performance with Parallel Active Messaging Interface support in Charm++, improving efficiency of fast Fourier transform calculations, improving load balancing, enabling better CPU vectorization and cache performance, and providing an alternative thermostat through stochastic velocity rescaling. We also present performance scaling results on early Newell systems.

Computer Science↗

DOE OSTI2018

MPAS-Seaice Model User's Guide

The MPAS Framework provides the foundation for a generalized geophysical fluid dynamics model on unstructured spherical and planar meshes. On top of the framework, implementations specific to the modeling of a particular physical system (e.g., land ice, ocean) are created as MPAS cores.

58 GEOSCIENCES↗

DOE OSTI2020

Molecular Optoelectronics (Final Technical Report)

The project developed new theoretical tools for analysis of nanodevices subjected to external optical and bias driving. Traditional theoretical techniques for molecular optoelectronics are either based on kinetic schemes or utilize quasiparticle description. The former fails to account for quantum mechanics of the system-bath interface and may fail qualitatively when used in open interacting systems. The latter is inconvenient in (usual for molecular optical spectroscopy) many body states description of the system. We developed a new technique - the Hubbard nonequilibrium Green's functions method - which allows to avoid shortcomings of standard theoretical approaches. The Hubbard NEGF was applied to analysis of experimental measurements of photoinduced current and bias-induced electroluminescence in STM molecular junctions. We also demonstrated practical usefulness of the Hubbard NEGF within newly proposed universal theory of current-induced forces for nonadiabatic molecular dynamics which generalizes celebrated Head-Gordon and Tully expression for electronic friction. Finally, following latest trends in laser techniques we studied local responses (local fluxes and local noise spectroscopy) of biased junctions as a source of information not accessible by total responses (total fluxes and noises) of the system.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2021

Deep Learning for Hydro-Biogeochemistry Processes

Focal Area(s): The white paper focuses on areas 2 and 3. The proposed deep learning modeling approach can provide forecasting capabilities and mechanism-based understanding of terrestrial and aquatic hydro- biogeochemical processes at watershed and river basin scales. Knowledge gleaned here can also provide insights for Earth System Models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Applying computationally efficient schemes for biogeochemical cycles (ACES4BGC)

NCAR contributed to the ACES4BGC project through software engineering work on aerosol model implementation, build system and script changes, coupler enhancements for biogeochemical tracers, improvements to the Community Land Model (CLM) code and testing infrastructure, and coordinating and integrating code changes from the various project participants.

54 ENVIRONMENTAL SCIENCES↗