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At least 1,153 records · Page 64

Too dim, too bright, and just right: Systems analysis of the Chlamydomonas diurnal program under limiting and excess light

Photosynthetic organisms coordinate their metabolism and growth with diurnal light, which can range in intensity from limiting to excessive. Little is known about how light intensity impacts the diurnal program in Chlamydomonas reinhardtii, or how diurnal rhythms in gene expression and metabolism shape photoprotective responses at different times of day. To address these questions, we performed a systems analysis of synchronized Chlamydomonas populations acclimated to low, moderate, and high diurnal light. Transcriptomic and proteomic data revealed that the Chlamydomonas rhythmic gene expression program is resilient to limiting and excess light: genome-wide, waves of transcripts, and proteins peak at the same times in populations acclimated to stressful light intensities as in populations acclimated to moderate light. Yet, diurnal photoacclimation gives rise to hundreds of gene expression changes, even at night. Time course measurements of photosynthetic efficiency and pigments responsive to excess light showed that high light-acclimated cells partially overcome photodamage in the latter half of the day prior to cell division. Although gene expression and photodamage are dynamic over the diurnal cycle, Chlamydomonas populations acclimated to low and high diurnal light maintain altered photosystem abundance, thylakoid architecture, and non-photochemical quenching capacity through the night phase. This suggests that cells remember or anticipate the light intensities that they have typically encountered during the day. The integrated data constitute an excellent resource for understanding photoacclimation in eukaryotes under environmentally relevant conditions.

Dupuis, Sunnyjoy↗

Accurate macromolecular crystallographic refinement: incorporation of the linear scaling, semiempirical quantum-mechanics program DivCon into the PHENIX refinement package

Semiempirical quantum-chemical X-ray macromolecular refinement using the program DivCon integrated with PHENIX is described. Macromolecular crystallographic refinement relies on sometimes dubious stereochemical restraints and rudimentary energy functionals to ensure the correct geometry of the model of the macromolecule and any covalently bound ligand(s). The ligand stereochemical restraint file (CIF) requires a priori understanding of the ligand geometry within the active site, and creation of the CIF is often an error-prone process owing to the great variety of potential ligand chemistry and structure. Stereochemical restraints have been replaced with more robust functionals through the integration of the linear-scaling, semiempirical quantum-mechanics (SE-QM) program DivCon with the PHENIX X-ray refinement engine. The PHENIX/DivCon package has been thoroughly validated on a population of 50 protein–ligand Protein Data Bank (PDB) structures with a range of resolutions and chemistry. The PDB structures used for the validation were originally refined utilizing various refinement packages and were published within the past five years. PHENIX/DivCon does not utilize CIF(s), link restraints and other parameters for refinement and hence it does not make as many a priori assumptions about the model. Across the entire population, the method results in reasonable ligand geometries and low ligand strains, even when the original refinement exhibited difficulties, indicating that PHENIX/DivCon is applicable to both single-structure and high-throughput crystallography.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

WinPSSP : a revamp of the computer program PSSP and its performance solving the crystal structures of small organic compounds and solids of biological and pharmaceutical interest

The direct-space methods software Powder Structure Solution Program ( PSSP ) [Pagola & Stephens (2010). J. Appl. Cryst. 43 , 370–376] has been migrated to the Windows OS and the code has been optimized for fast runs. WinPSSP is a user-friendly graphical user interface that allows the input of preliminary crystal structure information, integrated intensities of the reflections and FWHM, the definition of structural parameters and a simulated annealing schedule, and the visualization of the calculated and experimental diffraction data overlaid for each individual solution. The solutions are reported as filename.cif files, which can be used to analyze packing motifs and chemical bonding, and to input the atomic coordinates into the Rietveld analysis software GSAS. WinPSSP performance in straightforward crystal structure determinations has been evaluated using 18 molecular solids with 6–20 degrees of freedom. The free-distribution program as well as multimedia tutorials can be accessed at http://users.uoi.gr/nkourkou/winpssp/.

60 APPLIED LIFE SCIENCES↗

Equitable Design of Behind-the-Meter Energy Storage Programs: A Customer Perspective

Utility deployment of energy storage is done as a utility-scale asset connected directly to the grid (front of meter) or in partnership with a customer on the customer’s premises (behind the meter). By offering incentives for customers to install behind-the-meter storage, utilities can gain operational control of the assets and operate them in a manner that benefits all customers. Some states have also begun providing increased incentive levels to low-income customers to ensure that they can equitably share in the benefits of behind-the-meter energy storage programs. This paper evaluates different approaches to energy storage procurement from the customer’s perspective and evaluates how behind-the-meter programs can be equitably structured while keeping customers financially indifferent between front-of-meter and behind-the-meter energy storage procurements.

Twitchell, Jeremy B.↗

Integrating External Resources with a Task-Based Programming Model

Accessing external resources (e.g., loading input data, checkpointing snapshots, and out-of-core processing) can have a significant impact on the performance of supercomputer applications. However, no existing programming systems for high-performance computing directly manage and optimize these external accesses. As a result, users must explicitly manage external accesses alongside their computation at the application level, which can result in both correctness and performance issues. We address this limitation by introducing Iris, a task-based programming model with semantics for external resources. Iris allows applications to describe their access requirements to external resources and the relationship of those accesses to the computation. Iris incorporates external I/O into a deferred execution model, reschedules external I/O to overlap I/O with computation, and reduces external I/O when possible. We evaluate Iris on three microbenchmarks representative of important workloads in HPC and a full combustion simulation, S3D. We demonstrate that the Iris implementation of S3D reduces the external I/O overhead by up to 20×, compared to the Legion and the Fortran implementations.

97 MATHEMATICS AND COMPUTING↗

Sparse Deep Neural Network Inference using different Programming Models

Sparse deep neural networks have gained increasing attention recently in achieving speedups on inference with reduced memory footprints. However, the real-world applications are little shown with specialized optimizations, yet a wide variety of DNN tasks remain dense without exploiting the advantages of sparsity in networks. Recent work presented by MIT/IEEE/Amazon GraphChallenge has demonstrated significant speedups and various techniques. Still, we find that there is limited investigation of the impact of various Python and C\slash C++ based programming models to explore new opportunities in general cases. In this work, we provide performance evaluation through different programming models using CuPy, cuSPARSE, and OpenMP to discuss the advantages and disadvantages of our sparse implementations on single-GPU and multiple GPUs of NVIDIA DGX-A100 40GB/80GB platforms.

machine learning, HPC↗

Investigating Resilience of Loops in HPC Programs: A Semantic Approach with LLMs

Soft errors have become one of the major concerns for the error resilience of the HPC applications as those errors may cause HPC applications to generate serious outcomes such as silent data corruptions (SDCs). Protecting the applications from soft errors is an essential while challenging task. Among different approaches, obtaining a profound understanding of the resilience proneness of an application is very important to devise efficient error detection and recovery strategies. Given the scale of the HPC applications both in the code size and execution time, there are often cases that the error propagation analysis on such applications would produce a massive volume of unstructured data, which requires a significant amount of efforts, to process and to obtain indicating actions towards error protection. In this paper, we present a control-flow based visual analysis framework to help the users conduct error propagation analysis and identify the critical sections of a program that may have a higher likelihood of leading to erroneous outcomes when affected by the control flow related errors. We also design and implement the scalable visualization framework - ResilienceVis that efficiently and effectively visualizes the affected program states under errors and the propagation traces for an application in a user-friendly manner, and eventually, we combine the analysis and visualization to exhibit the error-proneness of the different sections of applications.

Jiang, Hailong↗

Localized Fault Recovery for Nested Fork-Join Programs

Nested fork-join programs scheduled using work stealing can automatically balance load and adapt to changes in the execution environment. In this paper, we design an approach to efficiently recover from faults encountered by these programs. Specifically, we focus on localized recovery of the task space in the presence of fail-stop failures. We present an approach to efficiently track, under work stealing, the relationships between the work executed by various threads. This information is used to identify and schedule the tasks to be re-executed without interfering with normal task execution. The algorithm precisely computes the work lost, incurs minimal re-execution overhead, and can recover from an arbitrary number of failures. Experimental evaluation demonstrates low overheads in the absence of failures, recovery overheads on the same order as the lost work, and much lower recovery costs than alternative strategies.

Kestor, Gokcen↗

Scenario Decomposition for 0-1 Stochastic Programs: Improvements and Asynchronous Implementation

We recently proposed scenario decomposition algorithm for stochastic 0-1 programs finds an optimal solution by evaluating and removing individual solutions that are discovered by solving scenario subproblems. In our work, we develop an asynchronous, distributed implementation of the algorithm which has computational advantages over existing synchronous implementations of the algorithm. Improvements to both the synchronous and asynchronous algorithm are proposed. We also test the results on well known stochastic 0-1 programs from the SIPLIB test library and is able to solve one previously unsolved instance from the test set.

97 MATHEMATICS AND COMPUTING↗

Evaluating performance and portability of high-level programming models: Julia, Python/Numba, and Kokkos on exascale nodes

We explore the performance and portability of the high-level programming models: the LLVM-based Julia and Python/Numba, and Kokkos on high-performance computing (HPC) nodes: AMD Epyc CPUs and MI250X graphical processing units (GPUs) on Frontier’s test bed Crusher system and Ampere’s Arm-based CPUs and NVIDIA’s A100 GPUs on the Wombat system at the Oak Ridge Leadership Computing Facilities. We compare the default performance of a hand-rolled dense matrix multiplication algorithm on CPUs against vendor-compiled C/OpenMP implementations, and on each GPU against CUDA and HIP. Rather than focusing on the kernel optimization per-se, we select this naive approach to resemble exploratory work in science and as a lower-bound for performance to isolate the effect of each programming model. Julia and Kokkos perform comparably with C/OpenMP on CPUs, while Julia implementations are competitive with CUDA and HIP on GPUs. Performance gaps are identified on NVIDIA A100 GPUs for Julia’s single precision and Kokkos, and for Python/Numba in all scenarios. We also comment on half-precision support, productivity, performance portability metrics, and platform readiness. We expect to contribute to the understanding and direction for high-level, high-productivity languages in HPC as the first-generation exascale systems are deployed.

Godoy, William↗

A General Framework for Bounding Approximate Dynamic Programming Schemes

For years, there has been interest in approximation methods for solving dynamic programming problems, because of the inherent complexity in computing optimal solutions characterized by Bellman’s principle of optimality. A wide range of approximate dynamic programming (ADP) methods now exists. It is of great interest to guarantee that the performance of an ADP scheme be at least some known fraction, say ß , of optimal. This letter introduces a general approach to bounding the performance of ADP methods, in this sense, in the stochastic setting. The approach is based on new results for bounding greedy solutions in string optimization problems, where one has to choose a string (ordered set) of actions to maximize an objective function. This bounding technique is inspired by submodularity theory, but submodularity is not required for establishing bounds. Instead, the bounding is based on quantifying certain notions of curvature of string functions; the smaller the curvatures the better the bound. The key insight is that any ADP scheme is a greedy scheme for some surrogate string objective function that coincides in its optimal solution and value with those of the original optimal control problem. The ADP scheme then yields to the bounding technique mentioned above, and the curvatures of the surrogate objective determine the value ß of the bound. The surrogate objective and its curvatures depend on the specific ADP.

discrete event systems↗

The Early Years and Evolution of the DOE Computational Science Graduate Fellowship Program

The U.S. Department of Energy Computational Graduate Fellowship Program, celebrating 30 years of existence in 2021, is one of the most successful graduate fellowships in the world as well as one of the longest running programs in the U.S. Department of Energy. Furthermore, this article discusses the conception, early years and evolution of the fellowship over the past thirty years.

97 MATHEMATICS AND COMPUTING↗

Status of the 16 T Dipole Development Program for a Future Hadron Collider

A next step of energy increase of hadron colliders beyond the LHC requires high-field superconducting magnets capable of providing a dipolar field in the range of 16 T in a 50-mm aperture with accelerator quality. These elements could meet the requirements for an upgrade of the LHC to twice the present beam energy or for a 100-TeV center of mass energy future circular collider. Here, we summarize the activities and plans for the development of these magnets, in particular within the 16 T Magnet Technology Program, the WP5 of the EuroCirCol, and the U.S. Magnet Development Program.

43 PARTICLE ACCELERATORS↗

Ordering Traces Logically to Identify Lateness in Message Passing Programs

Event traces are valuable for understanding the behavior of parallel programs. However, automatically analyzing a large parallel trace is difficult, especially without a specific objective. We aid this endeavor by extracting a trace's logical structure, an ordering of trace events derived from happened-before relationships, while taking into account developer intent. Using this structure, we can calculate an operation's delay relative to its peers on other processes. The logical structure also serves as a platform for comparing and clustering processes as well as highlighting communication patterns in a trace visualization. We present an algorithm for determining this idealized logical structure from traces of message passing programs, and we develop metrics to quantify delays and differences among processes. We implement our techniques in Ravel, a parallel trace visualization tool that displays both logical and physical timelines. Rather than showing the duration of each operation, we display where delays begin and end, and how they propagate. As a result, we apply our approach to the traces of several message passing applications, demonstrating the accuracy of our extracted structure and its utility in analyzing these codes.

97 MATHEMATICS AND COMPUTING↗

Generation Expansion Planning With Large Amounts of Wind Power via Decision-Dependent Stochastic Programming

Power generation expansion planning needs to deal with future uncertainties carefully, given that the invested generation assets will be in operation for a long time. Many stochastic programming models have been proposed to tackle this challenge. However, most previous works assume predetermined future uncertainties (i.e., fixed random outcomes with given probabilities). In several recent studies of generation assets' planning (e.g., thermal versus renewable), new findings show that the investment decisions could affect the future uncertainties as well. To this end, this paper proposes a multistage decision-dependent stochastic optimization model for long-term large-scale generation expansion planning, where large amounts of wind power are involved. In the decision-dependent model, the future uncertainties are not only affecting but also affected by the current decisions. In particular, the probability distribution function is determined by not only input parameters but also decision variables. To deal with the nonlinear constraints in our model, a quasi-exact solution approach is then introduced to reformulate the multistage stochastic investment model to a mixed-integer linear programming model. The wind penetration, investment decisions, and the optimality of the decision-dependent model are evaluated in a series of multistage case studies. The results show that the proposed decision-dependent model provides effective optimization solutions for long-term generation expansion planning.

Zhan, Yiduo↗

SU-C-BRD-05: Implementation of Incident Learning in the Safety and Quality Management of Radiotherapy: The Primary Experience in a New Established Program with Advanced Techniques

Purpose: To explore the implementation and effectiveness of incident learning for the safety and quality of radiotherapy in a new established radiotherapy program with advanced technology. Methods: Reference to the consensus recommendations by American Association of Physicist in Medicine, an incident learning system was specifically designed for reporting, investigating, and learning of individual radiotherapy incidents in a new established radiotherapy program, with 4D CBCT, Ultrasound guided radiotherapy, VMAT, gated treatment delivered on two new installed linacs. The incidents occurring in external beam radiotherapy from February, 2012 to January, 2014 were reported. Results: A total of 33 reports were analyzed, including 28 near misses and 5 incidents. Among them, 5 originated in imaging for planning, 25 in planning, 1 in plan transfer, 1 in commissioning and 1 in treatment delivery. Among them, three near misses originated in the safety barrier of the radiotherapy process. In terms of error type, 1 incident was classified as wrong patient, 7 near misses/incidents as wrong site, 6 as wrong laterality, 5 as wrong dose, 7 as wrong prescription, and 7 as suboptimal plan quality. 5 incidents were all classified as grade 1/2 of dosimetric severity, 1 as grade 0, and the other 4 as grade 1 of medical severity. For the causes/contributory factors, negligence, policy not followed, inadequate training, failure to develop an effective plan, and communication contributed to 19, 15, 12, 5 and 3 near misses/incidents, respectively. The average incident rate per 100 patients treated was 0.4; this rate fell to 0.28% in the second year from 0.56% in the first year. The rate of near miss fell to 1.24% from 2.22%. Conclusion: Effective incident learning can reduce the occurrence of near miss/incidents, enhance the culture of safety. Incident learning is an effective proactive method for improving the quality and safety of radiotherapy.

07 ISOTOPE AND RADIATION SOURCES↗

SU-C-BRD-01: Multi-Centre Collaborative Quality Assurance Program for IMRT Planning and Delivery: Year 3 Results

Purpose: A multi-centre quality assurance program was developed to enable quality improvement by coupling measurement of intensity modulated radiotherapy (IMRT) planning and delivery performance for site-specific planning exercises with diagnostic testing. The third year of the program specifically assessed the quality of spine stereotactic body radiotherapy (SBRT) planning and delivery amongst the participating centres. Methods: A spine SBRT planning exercise (24 Gy in 2 fractions) was created and completed by participants prior to an on-site visit. The delivery portion of the on-site visit included spine SBRT plan delivery and diagnostic testing, which included portal image acquisition for quantification of phantom positioning error and multi-leaf collimator (MLC) calibration accuracy. The measured dose was compared to that calculated in the treatment planning system (TPS) using 3%/2mm composite analysis and 3%/3mm gamma analysis. Results: Fourteen institutions participated, creating 17 spine SBRT plans (15 VMAT and 2 IMRT). Three different TPS, two beam energies (6 MV and 6 MV FFF), and four MLC designs from two linac vendors were tested. Large variation in total monitor units (MU) per plan (2494–6462 MU) and dose-volume parameters was observed. The maximum point dose in the plans ranged from 116–149% and was dependent upon the TPS used. Pass rates for measured to planned dose comparison ranged from 89.4–100% and 97.3–100% for 3%/2mm and 3%/3mm criteria respectively. The largest measured MLC error did Result in one of the poorer pass rates. No direct correlation between phantom positioning error and pass rates overall. Conclusion: Significant differences were observed in the planning exercise for some plan and dose-volume parameters based on the TPS used. Standard evaluation criteria showed good agreement between planned and measured dose for all participants, however on an individual plan basis, diagnostic tests were able to identify contributing factors for poorer results, when using more stringent evaluation criteria. Funding from Cancer Care Ontario is acknowledged.

60 APPLIED LIFE SCIENCES↗

TU-AB-201-02: An Automated Treatment Plan Quality Assurance Program for Tandem and Ovoid High Dose-Rate Brachytherapy

Purpose: For tandem and ovoid (T&O) HDR brachytherapy in our clinic, it is required that the planning physicist manually capture ∼10 images during planning, perform a secondary dose calculation and generate a report, combine them into a single PDF document, and upload it to a record- and-verify system to prove to an independent plan checker that the case was planned correctly. Not only does this slow down the already time-consuming clinical workflow, the PDF document also limits the number of parameters that can be checked. To solve these problems, we have developed a web-based automatic quality assurance (QA) program. Methods: We set up a QA server accessible through a web- interface. A T&O plan and CT images are exported as DICOMRT files and uploaded to the server. The software checks 13 geometric features, e.g. if the dwell positions are reasonable, and 10 dosimetric features, e.g. secondary dose calculations via TG43 formalism and D2cc to critical structures. A PDF report is automatically generated with errors and potential issues highlighted. It also contains images showing important geometric and dosimetric aspects to prove the plan was created following standard guidelines. Results: The program has been clinically implemented in our clinic. In each of the 58 T&O plans we tested, a 14- page QA report was automatically generated. It took ∼45 sec to export the plan and CT images and ∼30 sec to perform the QA tests and generate the report. In contrast, our manual QA document preparation tooks on average ∼7 minutes under optimal conditions and up to 20 minutes when mistakes were made during the document assembly. Conclusion: We have tested the efficiency and effectiveness of an automated process for treatment plan QA of HDR T&O cases. This software was shown to improve the workflow compared to our conventional manual approach.

60 APPLIED LIFE SCIENCES↗