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At least 469 records · Page 26

HERCULES: A Pattern Driven Code Transformation System

New parallel computers are emerging, but developing efficient scientific code for them remains difficult. A scientist must manage not only the science-domain complexity but also the performance-optimization complexity. HERCULES is a code transformation system designed to help the scientist to separate the two concerns, which improves code maintenance, and facilitates performance optimization. The system combines three technologies, code patterns, transformation scripts and compiler plugins, to provide the scientist with an environment to quickly implement code transformations that suit his needs. Unlike existing code optimization tools, HERCULES is unique in its focus on user-level accessibility. In this paper we discuss the design, implementation and an initial evaluation of HERCULES.

Computer Science↗

An X-ray Intensity Operations Monitor (AXIOM) (Final LDRD Project Report)

The Saturn accelerator has historically lacked the capability to measure time-resolved spectra for its 3-ring bremsstrahlung x-ray source. This project aimed to create a spectrometer called AXIOM to provide this capability. The project had three major development pillars: hardware, simulation, and unfold code. The hardware consists of a ring of 24 detectors around an existing x-ray pinhole camera. The diagnostic was fielded on two shots at Saturn and over 100 shots at the TriMeV accelerator at Idaho Accelerator Center. A new Saturn x-ray environment simulation was created using measured data to validate. This simulation allows for timeresolved spectra computation to compare the experimental results. The AXIOM-Unfold code is a new parametric unfold code using modern global optimizers and uncertainty quantification. The code was written in Python, uses Gitlab version control and issue tracking, and has been developed with long term code support and maintenance in mind.

43 PARTICLE ACCELERATORS↗

A Subsonic Aircraft Design Optimization With Neural Network and Regression Approximators

The Flight-Optimization-System (FLOPS) code encountered difficulty in analyzing a subsonic aircraft. The limitation made the design optimization problematic. The deficiencies have been alleviated through use of neural network and regression approximations. The insight gained from using the approximators is discussed in this paper. The FLOPS code is reviewed. Analysis models are developed and validated for each approximator. The regression method appears to hug the data points, while the neural network approximation follows a mean path. For an analysis cycle, the approximate model required milliseconds of central processing unit (CPU) time versus seconds by the FLOPS code. Performance of the approximators was satisfactory for aircraft analysis. A design optimization capability has been created by coupling the derived analyzers to the optimization test bed CometBoards. The approximators were efficient reanalysis tools in the aircraft design optimization. Instability encountered in the FLOPS analyzer was eliminated. The convergence characteristics were improved for the design optimization. The CPU time required to calculate the optimum solution, measured in hours with the FLOPS code was reduced to minutes with the neural network approximation and to seconds with the regression method. Generation of the approximators required the manipulation of a very large quantity of data. Design sensitivity with respect to the bounds of aircraft constraints is easily generated.

Patnaik, Surya N.↗

Fast optimization and dose calculation in scanned ion beam therapy

Purpose: Particle therapy (PT) has advantages over photon irradiation on static tumors. An increased biological effectiveness and active target conformal dose shaping are strong arguments for PT. However, the sensitivity to changes of internal geometry complicates the use of PT for moving organs. In case of interfractionally moving objects adaptive radiotherapy (ART) concepts known from intensity modulated radiotherapy (IMRT) can be adopted for PT treatments. One ART strategy is to optimize a new treatment plan based on daily image data directly before a radiation fraction is delivered [treatment replanning (TRP)]. Optimizing treatment plans for PT using a scanned beam is a time consuming problem especially for particles other than protons where the biological effective dose has to be calculated. For the purpose of TRP, fast optimization and fast dose calculation have been implemented into the GSI in-house treatment planning system (TPS) TRiP98. Methods: This work reports about the outcome of a code analysis that resulted in optimization of the calculation processes as well as implementation of routines supporting parallel execution of the code. To benchmark the new features, the calculation time for therapy treatment planning has been studied. Results: Compared to the original version of the TPS, calculation times for treatment planning (optimization and dose calculation) have been improved by a factor of 10 with code optimization. The parallelization of the TPS resulted in a speedup factor of 12 and 5.5 for the original version and the code optimized version, respectively. Hence the total speedup of the new implementation of the authors' TPS yielded speedup factors up to 55. Conclusions: The improved TPS is capable of completing treatment planning for ion beam therapy of a prostate irradiation considering organs at risk in this has been overseen in the review process. Also see below 6 min.

60 APPLIED LIFE SCIENCES↗

Combined coding and delay-throughput analysis for fading channels of mobile satellite communications

This paper presents the analysis of using the punctured convolutional code with Viterbi decoding to improve communications reliability. The punctured code rate is optimized so that the average delay is minimized. The coding gain in terms of the message delay is also defined. Since using punctured convolutional code with interleaving is still inadequate to combat the severe fading for short packets, the use of multiple copies of assignment and acknowledgment packets is suggested. The performance on the average end-to-end delay of this protocol is analyzed. It is shown that a replication of three copies for both assignment packets and acknowledgment packets is optimum for the cases considered.

Wang, C. C.↗

Study of reference burnup steps optimization in fuel segment data file generation for NEXUS/ANC9 code system

For any two-step core design code system, the cross-section files are the primary factor to determine the accuracy of the system prediction. For a once-through cross-section system to cover all potential applicable conditions, the system may need to perform tens of thousands state points of lattice calculations. These calculations take a significant amount of CPU times and computing power, especially when a fine or ultra-fine energy group library is used. As computer power increases, so does the calculational complexity. Therefore, it is important to make the lattice calculations effective and efficient. Based on the Westinghouse core design code system NEXUS/ANC9, this work focuses on the reference burnup steps used by the lattice code when performing the calculations. Following the fundamental cross-section methodology and analyzing the contribution of each individual terms, this study provides an applicable solution of the optimized reference burnup steps. The test results show that, with the existing cross-section methodology, it is possible to significantly reduce the lattice calculation cases and cross-section file generation time without sacrificing the accuracy of system prediction. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Performance modeling of microsecond scale biological molecular dynamics simulations on heterogeneous architectures

Performance improvements in biomolecular simulations based on molecular dynamics (MD) codes are widely desired. Unfortunately, the factors, which allowed past performance improvements, particularly the microprocessor clock frequencies, are no longer increasing. Hence, novel software and hardware solutions are being explored for accelerating performance of widely used MD codes. In this paper, we describe our efforts on porting, optimizing and tuning of Large-scale Atomic/Molecular Massively Parallel Simulator, a popular MD framework, on heterogeneous architectures: multi-core processors with graphical processing unit (GPU) accelerators. Our implementation is based on accelerating the most computationally expensive non-bonded interaction terms on the GPUs and overlapping the computation on the CPU and GPUs. This functionality is built on top of message passing interface that allows multi-level parallelism to be extracted even at the workstation level with the multi-core CPUs and allows extension of the implementation on GPU-enabled clusters. We hypothesize that the optimal benefit of heterogeneous architectures for applications will come by utilizing all possible resources (for example, CPU-cores and GPU devices on GPU-enabled clusters). Benchmarks for a range of biomolecular system sizes are provided, and an analysis is performed on four generations of NVIDIA's GPU devices. On GPU-enabled Linux clusters, by overlapping and pipelining computation and communication, we observe up to 10-folds application acceleration in multi-core and multi-GPU environments illustrating significant performance improvements. Detailed analysis of the implementation is presented that allows identification of bottlenecks in algorithm, indicating that code optimization and improvements on GPUs could allow microsecond scale simulation throughput on workstations and inexpensive GPU clusters, putting widely desired biologically relevant simulation time-scales within reach of a large user community. In order to systematically optimize simulation throughput and to enable performance prediction, we have developed a parameterized performance model that will allow developers and users to explore the performance potential of future heterogeneous systems for biological simulations.

Agarwal, Pratul K.↗

Low-complexity wavelet filter design for image compression

Image compression algorithms based on the wavelet transform are an increasingly attractive and flexible alternative to other algorithms based on block orthogonal transforms. While the design of orthogonal wavelet filters has been studied in significant depth, the design of nonorthogonal wavelet filters, such as linear-phase (LP) filters, has not yet reached that point. Of particular interest are wavelet transforms with low complexity at the encoder. In this article, we present known and new parameterizations of the two families of LP perfect reconstruction (PR) filters. The first family is that of all PR LP filters with finite impulse response (FIR), with equal complexity at the encoder and decoder. The second family is one of LP PR filters, which are FIR at the encoder and infinite impulse response (IIR) at the decoder, i.e., with controllable encoder complexity. These parameterizations are used to optimize the subband/wavelet transform coding gain, as defined for nonorthogonal wavelet transforms. Optimal LP wavelet filters are given for low levels of encoder complexity, as well as their corresponding integer approximations, to allow for applications limited to using integer arithmetic. These optimal LP filters yield larger coding gains than orthogonal filters with an equivalent complexity. The parameterizations described in this article can be used for the optimization of any other appropriate objective function.

Majani, E.↗

Image gathering, coding, and processing: End-to-end optimization for efficient and robust acquisition of visual information

Researchers are concerned with the end-to-end performance of image gathering, coding, and processing. The applications range from high-resolution television to vision-based robotics, wherever the resolution, efficiency and robustness of visual information acquisition and processing are critical. For the presentation at this workshop, it is convenient to divide research activities into the following two overlapping areas: The first is the development of focal-plane processing techniques and technology to effectively combine image gathering with coding, with an emphasis on low-level vision processing akin to the retinal processing in human vision. The approach includes the familiar Laplacian pyramid, the new intensity-dependent spatial summation, and parallel sensing/processing networks. Three-dimensional image gathering is attained by combining laser ranging with sensor-array imaging. The second is the rigorous extension of information theory and optimal filtering to visual information acquisition and processing. The goal is to provide a comprehensive methodology for quantitatively assessing the end-to-end performance of image gathering, coding, and processing.

Huck, Friedrich O.↗

Results of a WINGDES2/AERO2S Flap Optimization for the TCA

The codes WINGDES2 and AERO2S were easy to obtain, and technical help was readily available. The codes have a long, well-documented history of successful optimizations of various aircraft configurations. The codes were easy to use, although specification of input data was time-consuming. The Run times were short, allowing the many runs necessary for the Suction Parameter matrix to be accomplished within a day or two. The results of the optimization appear to be reasonable.

Yaros, Steven F.↗

Fitting Nonlinear Curves by use of Optimization Techniques

MULTIVAR is a FORTRAN 77 computer program that fits one of the members of a set of six multivariable mathematical models (five of which are nonlinear) to a multivariable set of data. The inputs to MULTIVAR include the data for the independent and dependent variables plus the user s choice of one of the models, one of the three optimization engines, and convergence criteria. By use of the chosen optimization engine, MULTIVAR finds values for the parameters of the chosen model so as to minimize the sum of squares of the residuals. One of the optimization engines implements a routine, developed in 1982, that utilizes the Broydon-Fletcher-Goldfarb-Shanno (BFGS) variable-metric method for unconstrained minimization in conjunction with a one-dimensional search technique that finds the minimum of an unconstrained function by polynomial interpolation and extrapolation without first finding bounds on the solution. The second optimization engine is a faster and more robust commercially available code, denoted Design Optimization Tool, that also uses the BFGS method. The third optimization engine is a robust and relatively fast routine that implements the Levenberg-Marquardt algorithm.

Hill, Scott A.↗

Element Load Data Processor (ELDAP) Users Manual

Often, the shear and tensile forces and moments are extracted from finite element analyses to be used in off-line calculations for evaluating the integrity of structural connections involving bolts, rivets, and welds. Usually the maximum forces and moments are desired for use in the calculations. In situations where there are numerous structural connections of interest for numerous load cases, the effort in finding the true maximum force and/or moment combinations among all fasteners and welds and load cases becomes difficult. The Element Load Data Processor (ELDAP) software described herein makes this effort manageable. This software eliminates the possibility of overlooking the worst-case forces and moments that could result in erroneous positive margins of safety and/or selecting inconsistent combinations of forces and moments resulting in false negative margins of safety. In addition to forces and moments, any scalar quantity output in a PATRAN report file may be evaluated with this software. This software was originally written to fill an urgent need during the structural analysis of the Ares I-X Interstage segment. As such, this software was coded in a straightforward manner with no effort made to optimize or minimize code or to develop a graphical user interface.

Ramsey, John K., Jr.↗

Diffusion Codes: Self-Correction from Small(er)-Set Expansion with Tunable Non-locality

Optimal constructions of classical LDPC codes can be obtained by choosing the Tanner graph uniformly at random among biregular graphs. We introduce a class of codes that we call ``diffusion codes'', defined by placing each edge connecting bits and checks on some graph, and acting on that graph with a random SWAP network. By tuning the depth of the SWAP network, we can tune a tradeoff between the amount of randomness -- and hence the optimality of code parameters -- and locality with respect to the underlying graph. For diffusion codes defined on the cycle graph, if the SWAP network has depth $\sim Tn$ with $T> n^{2β}$ for arbitrary $β>0$, then we prove that almost surely the Tanner graph is a lossless ``smaller set'' vertex expander for small sets up size $δ\sim \sqrt T \sim n^β$, with bounded bit and check degree. At the same time, the geometric size of the largest stabilizer is bounded by $\sqrt T$ in graph distance. We argue, based on physical intuition, that this result should hold more generally on arbitrary graphs. By taking hypergraph products of these classical codes we obtain quantum LDPC codes defined on the torus with smaller-set boundary and co-boundary expansion and the same expansion/locality tradeoffs as for the classical codes. These codes are self-correcting and admit single-shot decoding, while having the geometric size of the stabilizer growing as an arbitrarily small power law. Our proof technique establishes mixing of a random SWAP network on small subsystems at times scaling with only the subsystem size, which may be of independent interest.

Combinatorics (math.CO)↗

Can search algorithms save large-scale automatic performance tuning?

Empirical performance optimization of computer codes using autotuners has received significant attention in recent years. Given the increased complexity of computer architectures and scientific codes, evaluating all possible code variants is prohibitively expensive for all but the simplest kernels. One way for autotuners to overcome this hurdle is through use of a search algorithm that finds high-performing code variants while examining relatively few variants. In this paper we examine the search problem in autotuning from a mathematical optimization perspective. As an illustration of the power and limitations of this optimization, we conduct an experimental study of several optimization algorithms on a number of linear algebra kernel codes. We find that the algorithms considered obtain performance gains similar to the optimal ones found by complete enumeration or by large random searches but in a tiny fraction of the computation time.

97 MATHEMATICS AND COMPUTING↗

Optimal Grouping and Matching for Network-Coded Cooperative Communications

Network-coded cooperative communications (NC-CC) is a new advance in wireless networking that exploits network coding (NC) to improve the performance of cooperative communications (CC). However, there remains very limited understanding of this new hybrid technology, particularly at the link layer and above. This paper fills in this gap by studying a network optimization problem that requires joint optimization of session grouping, relay node grouping, and matching of session/relay groups. After showing that this problem is NP-hard, we present a polynomial time heuristic algorithm to this problem. Using simulation results, we show that our algorithm is highly competitive and can produce near-optimal results.

97 MATHEMATICS AND COMPUTING↗

A comprehensive method for preliminary design optimization of axial gas turbine stages. II - Code verification

The present effort represents an extension of previous work wherein a calculation model for performing rapid pitchline optimization of axial gas turbine geometry, including blade profiles, is developed. The model requires no specification of geometric constraints. Output includes aerodynamic performance (adiabatic efficiency), hub-tip flow-path geometry, blade chords, and estimates of blade shape. Presented herein is a verification of the aerodynamic performance portion of the model, whereby detailed turbine test-rig data, including rig geometry, is input to the model to determine whether tested performance can be predicted. An array of seven (7) NASA single-stage axial gas turbine configurations is investigated, ranging in size from 0.6 kg/s to 63.8 kg/s mass flow and in specific work output from 153 J/g to 558 J/g at design (hot) conditions; stage loading factor ranges from 1.15 to 4.66.

Jenkins, R. M.↗

PAYCOS: A new multidisciplinary analysis program for hypersonic vehicle design

The Payload Conceptual Sizing Code (PAYCOS), a new multidisciplinary computer program for use in the conceptual development phase of hypersonic lifting vehicles (HV's), is described. The program allows engineers to rapidly determine the feasibility of an HV concept and then improve upon the concept by means of optimization theory. The code contains analysis modules for aerodynamics, thermodynamics, mass properties, flight stability, controls, loads, structures, and packaging. Motivation for the code lies with the increased complexity of HV's over their body-of-revolution ballistic predecessors. With these new shapes, the need to rapidly screen out poor concepts and actively develop new and better concepts is an even more crucial part of the early design process. Preliminary results are given which demonstrate the optimization capabilities of the code.

Stubbe, J. R.↗