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At least 199 records · Page 11

Adaptive Spatially Aware I/O for Multiresolution Particle Data Layouts

Large-scale simulations on nonuniform particle distributions that evolve over time are widely used in cosmology, molecular dynamics, and engineering. Such data are often saved in an unstructured format that neither preserves spatial locality nor provides metadata for accelerating spatial or attribute subset queries, leading to poor performance of visualization tasks. Furthermore, the parallel I/O strategy used typically writes a file per process or a single shared file, neither of which is portable or scalable across different HPC systems. We present a portable technique for scalable, spatially aware adaptive aggregation that preserves spatial locality in the output. We evaluate our approach on two supercomputers, Stampede2 and Summit, and demonstrate that it outperforms prior approaches at scale, achieving up to 2.5× faster writes and reads for nonuniform distributions. Furthermore, the layout written by our method is directly suitable for visual analytics, supporting low-latency reads and attribute-based filtering with little overhead.

Usher, Will↗

SU-F-T-256: 4D IMRT Planning Using An Early Prototype GPU-Enabled Eclipse Workstation

Purpose: True 4D IMRT planning, based on simultaneous spatiotemporal optimization has been shown to significantly improve plan quality in lung radiotherapy. However, the high computational complexity associated with such planning represents a significant barrier to widespread clinical deployment. We introduce an early prototype GPU-enabled Eclipse workstation for inverse planning. To our knowledge, this is the first GPUintegrated Eclipse system demonstrating the potential for clinical translation of GPU computing on a major commercially-available TPS. Methods: The prototype system comprised of four NVIDIA Tesla K80 GPUs, with a maximum processing capability of 8.5 Tflops per K80 card. The system architecture consisted of three key modules: (i) a GPU-based inverse planning module using a highly-parallelizable, swarm intelligence-based global optimization algorithm, (ii) a GPU-based open-source b-spline deformable image registration module, Elastix, and (iii) a CUDA-based data management module. For evaluation, aperture fluence weights in an IMRT plan were optimized over 9 beams,166 apertures and 10 respiratory phases (14940 variables) for a lung cancer case (GTV = 95 cc, right lower lobe, 15 mm cranio-caudal motion). Sensitivity of the planning time and memory expense to parameter variations was quantified. Results: GPU-based inverse planning was significantly accelerated compared to its CPU counterpart (36 vs 488 min, for 10 phases, 10 search agents and 10 iterations). The optimized IMRT plan significantly improved OAR sparing compared to the original internal target volume (ITV)-based clinical plan, while maintaining prescribed tumor coverage. The dose-sparing improvements were: Esophagus Dmax 50%, Heart Dmax 42% and Spinal cord Dmax 25%. Conclusion: Our early prototype system demonstrates that through massive parallelization, computationally intense tasks such as 4D treatment planning can be accomplished in clinically feasible timeframes. With further optimization, such systems are expected to enable the eventual clinical translation of higher-dimensional and complex treatment planning strategies to significantly improve plan quality. This work was partially supported through research funding from National Institutes of Health (R01CA169102) and Varian Medical Systems, Palo Alto, CA, USA.

60 APPLIED LIFE SCIENCES↗

Stochastic Vector Techniques in Ground-State Electronic Structure

Herein we review a suite of stochastic vector computational approaches for studying the electronic structure of extended condensed matter systems. These techniques help reduce algorithmic complexity, facilitate efficient parallelization, simplify computational tasks, accelerate calculations, and diminish memory requirements. While their scope is vast, we limit our study to ground-state and finite temperature density functional theory (DFT) and second-order many-body perturbation theory. More advanced topics, such as quasiparticle (charge) and optical (neutral) excitations and higher-order processes, are covered elsewhere. We start by explaining how to use stochastic vectors in computations, characterizing the associated statistical errors. Next, we show how to estimate the electron density in DFT and discuss effective techniques to reduce statistical errors. Finally, we review the use of stochastic vectors for calculating correlation energies within the second-order Møller-Plesset perturbation theory and its finite temperature variational form. Example calculation results are presented and used to demonstrate the efficacy of the methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Regulatory Technology Development Plan - Sodium Fast Reactor: Mechanistic Source Term – Trial Calculation

The potential release of radioactive material during a plant incident, referred to as the source term, is a vital design metric and will be a major focus of advanced reactor licensing. The U.S. Nuclear Regulatory Commission has stated an expectation for advanced reactor vendors to present a mechanistic assessment of the potential source term in their license applications. The mechanistic source term presents an opportunity for vendors to realistically assess the radiological consequences of an incident, and may allow reduced emergency planning zones and smaller plant sites. However, the development of a mechanistic source term for advanced reactors is not without challenges, as there are often numerous phenomena impacting the transportation and retention of radionuclides. This project sought to evaluate U.S. capabilities regarding the mechanistic assessment of radionuclide release from core damage incidents at metal fueled, pool-type sodium fast reactors (SFRs). The purpose of the analysis was to identify, and prioritize, any gaps regarding computational tools or data necessary for the modeling of radionuclide transport and retention phenomena. To accomplish this task, a parallel-path analysis approach was utilized. One path, led by Argonne and Sandia National Laboratories, sought to perform a mechanistic source term assessment using available codes, data, and models, with the goal to identify gaps in the current knowledge base. The second path, performed by an independent contractor, performed sensitivity analyses to determine the importance of particular radionuclides and transport phenomena in regards to offsite consequences. The results of the two pathways were combined to prioritize gaps in current capabilities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Scalable Second Order Optimization for Machine Learning

Many machine learning (ML) training tasks are essentially optimization processes that would at first glance appear eminently parallelizable and scalable. However, effective acceleration of these tasks with scalable parallel hardware has proven to be elusive. While standard methods for machine learning, e.g., stochastic gradient descent (SGD) for DNNs, tend to be resource efficient, they appear to be fundamentally sequential in nature.

97 MATHEMATICS AND COMPUTING↗

Integrated aerodynamic-structural design of a forward-swept transport wing

The introduction of composite materials is having a profound effect on aircraft design. Since these materials permit the designer to tailor material properties to improve structural, aerodynamic and acoustic performance, they require an integrated multidisciplinary design process. Futhermore, because of the complexity of the design process, numerical optimization methods are required. The utilization of integrated multidisciplinary design procedures for improving aircraft design is not currently feasible because of software coordination problems and the enormous computational burden. Even with the expected rapid growth of supercomputers and parallel architectures, these tasks will not be practical without the development of efficient methods for cross-disciplinary sensitivities and efficient optimization procedures. The present research is part of an on-going effort which is focused on the processes of simultaneous aerodynamic and structural wing design as a prototype for design integration. A sequence of integrated wing design procedures has been developed in order to investigate various aspects of the design process.

Haftka, Raphael T.↗

Computational simulation of transition to turbulence through inverse modeling

The present investigation has focused on a computational methodology for the fundamental case of transition in channel flow, in which recently published experimental data are utilized both as a stimulus and as a measure of merit of the method. The research has proceeded along three avenues in parallel. The first task has consisted of the development and verification of a computer code which calculates the mean evolution of flow in a channel similar to the one employed experimentally by Blair and Anderson. An analytical test case was created for the dual purposes of code verification and of highlighting the interactions between the Reynolds stress and the mean velocity profile. This test case generated a Reynolds stress by the residue in the momentum equation which is produced by a typical analytical velocity profile. By a substitution of this Reynolds stress into the appropriate code module, the correctness of the code may be verified, along with the accuracy of the computational method. The second task pursued has involved the development of a triple layer model for the Reynolds stress profile, which was suggested and derived from experimental velocity profiles. It is demonstrated that the innermost length scale is based on the local friction velocity, the intermediate layer corresponds to the usual logarithmic law of the wall region in which the normalized Reynolds stress is approximately unity, and the outermost layer is represented by a closed mathematical form depending explicitly on the velocity profile in the wake region. The third task was comprised of scrutiny of the excellent databases developed by Blair and others, and the planning of its incorporation into the transition analysis. These extensive measurements indicate that turbulent statistics in the transition regime may be considered to alternate between laminar and fully turbulent types, the proportions of which are quantified by a measured intermittency function.

Sepri, Paavo↗

SHARED VIRTUAL ENVIRONMENTS FOR COLLECTIVE TRAINING

Historically NASA has trained teams of astronauts by bringing them to the Johnson Space Center in Houston to undergo generic training, followed by mission-specific training. This latter training begins after a crew has been selected for a mission (perhaps two years before the launch of that mission). While some Space Shuttle flights have included an astronaut from a foreign country, the International Space Station will be consistently crewed by teams comprised of astronauts from two or more of the partner nations. The cost of training these international teams continues to grow in both monetary and personal terms. Thus, NASA has been seeking alternative training approaches for the International Space Station program. Since 1994 we have been developing, testing, and refining shared virtual environments for astronaut team training, including the use of virtual environments for use while in or in transit to the task location. In parallel with this effort, we have also been preparing applications for training teams of military personnel engaged in peacekeeping missions. This paper will describe the applications developed to date, some of the technological challenges that have been overcome in their development, and the research performed to guide the development and to measure the efficacy of these shared environments as training tools.

Loftin, R. Bowen↗

Grid Task Execution

IPG Execution Service is a framework that reliably executes complex jobs on a computational grid, and is part of the IPG service architecture designed to support location-independent computing. The new grid service enables users to describe the platform on which they need a job to run, which allows the service to locate the desired platform, configure it for the required application, and execute the job. After a job is submitted, users can monitor it through periodic notifications, or through queries. Each job consists of a set of tasks that performs actions such as executing applications and managing data. Each task is executed based on a starting condition that is an expression of the states of other tasks. This formulation allows tasks to be executed in parallel, and also allows a user to specify tasks to execute when other tasks succeed, fail, or are canceled. The two core components of the Execution Service are the Task Database, which stores tasks that have been submitted for execution, and the Task Manager, which executes tasks in the proper order, based on the user-specified starting conditions, and avoids overloading local and remote resources while executing tasks.

Hu, Chaumin↗

Exploring Asynchronous Many-Task Runtime Systems toward Extreme Scales

Major exascale computing reports indicate a number of software challenges to meet the dramatic change of system architectures in near future. While several-orders-of-magnitude increase in parallelism is the most commonly cited of those, hurdles also include performance heterogeneity of compute nodes across the system, increased imbalance between computational capacity and I/O capabilities, frequent system interrupts, and complex hardware architectures. Asynchronous task-parallel programming models show a great promise in addressing these issues, but are not yet fully understood nor developed su ciently for computational science and engineering application codes. We address these knowledge gaps through quantitative and qualitative exploration of leading candidate solutions in the context of engineering applications at Sandia. In this poster, we evaluate MiniAero code ported to three leading candidate programming models (Charm++, Legion and UINTAH) to examine the feasibility of these models that permits insertion of new programming model elements into an existing code base.

97 MATHEMATICS AND COMPUTING↗

Performance analysis and acceleration of explicit integration for large kinetic networks using batched GPU computations

Abstract—We demonstrate the systematic implementation of recently-developed fast explicit kinetic integration algorithms that solve efficiently N coupled ordinary differential equations (subject to initial conditions) on modern GPUs. We take representative test cases (Type Ia supernova explosions) and demonstrate two or more orders of magnitude increase in efficiency for solving such systems (of realistic thermonuclear networks coupled to fluid dynamics). This implies that important coupled, multiphysics problems in various scientific and technical disciplines that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible. As examples of such applications we present the computational techniques developed for our ongoing deployment of these new methods on modern GPU accelerators. We show that similarly to many other scientific applications, ranging from national security to medical advances, the computation can be split into many independent computational tasks, each of relatively small-size. As the size of each individual task does not provide sufficient parallelism for the underlying hardware, especially for accelerators, these tasks must be computed concurrently as a single routine, that we call batched routine, in order to saturate the hardware with enough work.

Haidar Ahmad, Azzam↗

Classic and Quantum Task-Based Intelligent Runtime for QIRs Running on Multiple QPUs

High-performance computing systems are rapidly evolving into heterogeneous platforms that fuse quantum accelerators with traditional classical processing units (CPUs) and graphical processing units (GPUs). This convergence calls for runtimes capable of managing both classical and quantum workloads in a unified manner. We introduce an intelligent, task-based runtime that marries the Intelligent RuntIme System (IRIS) asynchronous scheduler with a quantum programming stack through the Quantum Intermediate Representation Execution Engine (QIR-EE). Our design allows programs written in the quantum intermediate representation (QIR) to be dispatched concurrently to a variety of back-ends, including multiple quantum simulators and nascent quantum processors, enabling genuine hybrid execution on a single node. To illustrate its practicality, we partition a 4-qubit and 20-qubit circuit into three sub-circuits using quantum circuit cutting via the QCut library. Each sub-circuit is simulated independently by the QIR-EE driver within IRIS, after which a classical post-processing step merges the simulation results to recover the outcome of the original full-circuit computation. This case study demonstrates how finer task granularity can enable the parallel execution and lower the simulation burden per quantum task while preserving overall accuracy, highlighting the feasibility of our hybrid approach.

Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗

Development of 3D electromagnetic modeling tools for airborne vehicles

The main goal of this report is to advance the development of methodologies for scattering by airborne composite vehicles. Although the primary focus continues to be the development of a general purpose computer code for analyzing the entire structure as a single unit, a number of other tasks are also being pursued in parallel with this effort. One of these tasks discussed within is on new finite element formulations and mesh termination schemes. The goal here is to decrease computation time while retaining accuracy and geometric adaptability.The second task focuses on the application of wavelets to electromagnetics. Wavelet transformations are shown to be able to reduce a full matrix to a band matrix, thereby reducing the solutions memory requirements. Included within this document are two separate papers on finite element formulations and wavelets.

Volakis, John L.↗

Mobile Thread Task Manager

The Mobile Thread Task Manager (MTTM) is being applied to parallelizing existing flight software to understand the benefits and to develop new techniques and architectural concepts for adapting software to multicore architectures. It allocates and load-balances tasks for a group of threads that migrate across processors to improve cache performance. In order to balance-load across threads, the MTTM augments a basic map-reduce strategy to draw jobs from a global queue. In a multicore processor, memory may be "homed" to the cache of a specific processor and must be accessed from that processor. The MTTB architecture wraps access to data with thread management to move threads to the home processor for that data so that the computation follows the data in an attempt to avoid L2 cache misses. Cache homing is also handled by a memory manager that translates identifiers to processor IDs where the data will be homed (according to rules defined by the user). The user can also specify the number of threads and processors separately, which is important for tuning performance for different patterns of computation and memory access. MTTM efficiently processes tasks in parallel on a multiprocessor computer. It also provides an interface to make it easier to adapt existing software to a multiprocessor environment.

Clement, Bradley J.↗

A Lanczos eigenvalue method on a parallel computer

Eigenvalue analyses of complex structures is a computationally intensive task which can benefit significantly from new and impending parallel computers. This study reports on a parallel computer implementation of the Lanczos method for free vibration analysis. The approach used here subdivides the major Lanczos calculation tasks into subtasks and introduces parallelism down to the subtask levels such as matrix decomposition and forward/backward substitution. The method was implemented on a commercial parallel computer and results were obtained for a long flexible space structure. While parallel computing efficiency for the Lanczos method was good for a moderate number of processors for the test problem, the greatest reduction in time was realized for the decomposition of the stiffness matrix, a calculation which took 70 percent of the time in the sequential program and which took 25 percent of the time on eight processors. For a sample calculation of the twenty lowest frequencies of a 486 degree of freedom problem, the total sequential computing time was reduced by almost a factor of ten using 16 processors.

Bostic, Susan W.↗

A Lanczos eigenvalue method on a parallel computer

Eigenvalue analyses of complex structures is a computationally intensive task which can benefit significantly from new and impending parallel computers. This study reports on a parallel computer implementation of the Lanczos method for free vibration analysis. The approach used here subdivides the major Lanczos calculation tasks into subtasks and introduces parallelism down to the subtask levels such as matrix decomposition and forward/backward substitution. The method was implemented on a commercial parallel computer and results were obtained for a long flexible space structure. While parallel computing efficiency is problem and computer dependent, the efficiency for the Lanczos method was good for a moderate number of processors for the test problem. The greatest reduction in time was realized for the decomposition of the stiffness matrix, a calculation which took 70 percent of the time in the sequential program and which took 25 percent of the time on eight processors. For a sample calculation of the twenty lowest frequencies of a 486 degree of freedom problem, the total sequential computing time was reduced by almost a factor of ten using 16 processors.

Bostic, Susan W.↗

Parallel solution of sparse one-dimensional dynamic programming problems

Parallel computation offers the potential for quickly solving large computational problems. However, it is often a non-trivial task to effectively use parallel computers. Solution methods must sometimes be reformulated to exploit parallelism; the reformulations are often more complex than their slower serial counterparts. We illustrate these points by studying the parallelization of sparse one-dimensional dynamic programming problems, those which do not obviously admit substantial parallelization. We propose a new method for parallelizing such problems, develop analytic models which help us to identify problems which parallelize well, and compare the performance of our algorithm with existing algorithms on a multiprocessor.

Nicol, David M.↗