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At least 91 records · Page 5

An implementation of a tree code on a SIMD, parallel computer

We describe a fast tree algorithm for gravitational N-body simulation on SIMD parallel computers. The tree construction uses fast, parallel sorts. The sorted lists are recursively divided along their x, y and z coordinates. This data structure is a completely balanced tree (i.e., each particle is paired with exactly one other particle) and maintains good spatial locality. An implementation of this tree-building algorithm on a 16k processor Maspar MP-1 performs well and constitutes only a small fraction (approximately 15%) of the entire cycle of finding the accelerations. Each node in the tree is treated as a monopole. The tree search and the summation of accelerations also perform well. During the tree search, node data that is needed from another processor is simply fetched. Roughly 55% of the tree search time is spent in communications between processors. We apply the code to two problems of astrophysical interest. The first is a simulation of the close passage of two gravitationally, interacting, disk galaxies using 65,636 particles. We also simulate the formation of structure in an expanding, model universe using 1,048,576 particles. Our code attains speeds comparable to one head of a Cray Y-MP, so single instruction, multiple data (SIMD) type computers can be used for these simulations. The cost/performance ratio for SIMD machines like the Maspar MP-1 make them an extremely attractive alternative to either vector processors or large multiple instruction, multiple data (MIMD) type parallel computers. With further optimizations (e.g., more careful load balancing), speeds in excess of today's vector processing computers should be possible.

Olson, Kevin M.↗

Parallel implementation of an algorithm for Delaunay triangulation

This work concerns the theory and practice of implementing Tanemura's algorithm for 3D Delaunay triangulation on Intel's Gamma prototype, a 128 processor MIMD computer. Tanemura's algorithm does not vectorize to any significant degree and requires indirect addressing. Efficient implementation on a conventional, vector processing, supercomputer is problematic. Efficient implementation on a parallel architecture is possible, however. In this work, speeds in excess of 8 times a single processor Cray Y-mp are realized on 128 processors of the Intel Gamma prototype.

Merriam, Marshall L.↗

WARP3D-Release 10.8: Dynamic Nonlinear Analysis of Solids using a Preconditioned Conjugate Gradient Software Architecture

This report describes theoretical background material and commands necessary to use the WARP3D finite element code. WARP3D is under continuing development as a research code for the solution of very large-scale, 3-D solid models subjected to static and dynamic loads. Specific features in the code oriented toward the investigation of ductile fracture in metals include a robust finite strain formulation, a general J-integral computation facility (with inertia, face loading), an element extinction facility to model crack growth, nonlinear material models including viscoplastic effects, and the Gurson-Tver-gaard dilatant plasticity model for void growth. The nonlinear, dynamic equilibrium equations are solved using an incremental-iterative, implicit formulation with full Newton iterations to eliminate residual nodal forces. The history integration of the nonlinear equations of motion is accomplished with Newmarks Beta method. A central feature of WARP3D involves the use of a linear-preconditioned conjugate gradient (LPCG) solver implemented in an element-by-element format to replace a conventional direct linear equation solver. This software architecture dramatically reduces both the memory requirements and CPU time for very large, nonlinear solid models since formation of the assembled (dynamic) stiffness matrix is avoided. Analyses thus exhibit the numerical stability for large time (load) steps provided by the implicit formulation coupled with the low memory requirements characteristic of an explicit code. In addition to the much lower memory requirements of the LPCG solver, the CPU time required for solution of the linear equations during each Newton iteration is generally one-half or less of the CPU time required for a traditional direct solver. All other computational aspects of the code (element stiffnesses, element strains, stress updating, element internal forces) are implemented in the element-by- element, blocked architecture. This greatly improves vectorization of the code on uni-processor hardware and enables straightforward parallel-vector processing of element blocks on multi-processor hardware.

Koppenhoefer, Kyle C.↗

Some Problems and Solutions in Transferring Ecosystem Simulation Codes to Supercomputers

Many computer codes for the simulation of ecological systems have been developed in the last twenty-five years. This development took place initially on main-frame computers, then mini-computers, and more recently, on micro-computers and workstations. Recent recognition of ecosystem science as a High Performance Computing and Communications Program Grand Challenge area emphasizes supercomputers (both parallel and distributed systems) as the next set of tools for ecological simulation. Transferring ecosystem simulation codes to such systems is not a matter of simply compiling and executing existing code on the supercomputer since there are significant differences in the system architectures of sequential, scalar computers and parallel and/or vector supercomputers. To more appropriately match the application to the architecture (necessary to achieve reasonable performance), the parallelism (if it exists) of the original application must be exploited. We discuss our work in transferring a general grassland simulation model (developed on a VAX in the FORTRAN computer programming language) to a Cray Y-MP. We show the Cray shared-memory vector-architecture, and discuss our rationale for selecting the Cray. We describe porting the model to the Cray and executing and verifying a baseline version, and we discuss the changes we made to exploit the parallelism in the application and to improve code execution. As a result, the Cray executed the model 30 times faster than the VAX 11/785 and 10 times faster than a Sun 4 workstation. We achieved an additional speed-up of approximately 30 percent over the original Cray run by using the compiler's vectorizing capabilities and the machine's ability to put subroutines and functions "in-line" in the code. With the modifications, the code still runs at only about 5% of the Cray's peak speed because it makes ineffective use of the vector processing capabilities of the Cray. We conclude with a discussion and future plans.

Skiles, J. W.↗

NASA's Earth Observing System (EOS): Observing the Atmosphere, Land, Oceans, and Ice from Space

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, the last of the first series of EOS missions, Aura, was launched. Aura is designed exclusively to conduct research on the composition, chemistry, and dynamics of the Earth's upper and lower atmosphere, employing multiple instruments on a single spacecraft. Aura is the third in a series of major Earth observing satellites to study the environment and climate change and is part of NASA's Earth Science Enterprise. The first and second missions, Terra and Aqua, are designed to study the land, oceans, atmospheric constituents (aerosols, clouds, temperature, and water vapor), and the Earth's radiation budget. The other seven EOS spacecraft include satellites to study (i) land cover & land use change, (ii) solar irradiance and solar spectral variation, (iii) ice volume, (iv) ocean processes (vector wind and sea surface topography), and (v) vertical variations of clouds, water vapor, and aerosols up to and including the stratosphere. Aura's chemistry measurements will also follow up on measurements that began with NASA's Upper Atmosphere Research Satellite and continue the record of satellite ozone data collected from the TOMS missions. In this presentation I will describe how scientists are using EOS data to examine the health of the earth's atmosphere, including atmospheric chemistry, aerosol properties, and cloud properties, with a special but not exclusive look at the latest earth observing mission, Aura.

King, Michael D.↗

NASA's Earth Observing System (EOS): Observing the Atmosphere, Land, Oceans, and Ice from Space

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by whch scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, the last of the first series of EOS missions, Aura, was launched. Aura is designed exclusively to conduct research on the composition, chemistry, and dynamics of the Earth's upper and lower atmosphere, employing multiple instruments on a single spacecraft. Aura is the third in a series of major Earth observing satellites to study the environment and climate change and is part of NASA's Earth Science Enterprise. The first and second missions, Terra and Aqua, are designed to study the land, oceans, atmospheric constituents (aerosols, clouds, temperature, and water vapor), and the Earth's radiation budget. The other seven EOS spacecraft include satellites to study (i) land cover & land use change, (ii) solar irradiance and solar spectral variation, (iii) ice volume, (iv) ocean processes (vector wind and sea surface topography), and (v) vertical variations of clouds, water vapor, and aerosols up to and including the stratosphere. Aura's chemistry measurements will also follow up on measurements that began with NASA's Upper Atmosphere Research Satellite and continue the record of satellite ozone data collected from the TOMS missions. In this presentation I will describe how scientists are using EOS data to examine the health of the earth's atmosphere, including atmospheric chemistry, aerosol properties, and cloud properties, with a special look at the latest earth observing mission, Aura.

King, Michael D.↗

Parallel Subconvolution Filtering Architectures

These architectures are based on methods of vector processing and the discrete-Fourier-transform/inverse-discrete- Fourier-transform (DFT-IDFT) overlap-and-save method, combined with time-block separation of digital filters into frequency-domain subfilters implemented by use of sub-convolutions. The parallel-processing method implemented in these architectures enables the use of relatively small DFT-IDFT pairs, while filter tap lengths are theoretically unlimited. The size of a DFT-IDFT pair is determined by the desired reduction in processing rate, rather than on the order of the filter that one seeks to implement. The emphasis in this report is on those aspects of the underlying theory and design rules that promote computational efficiency, parallel processing at reduced data rates, and simplification of the designs of very-large-scale integrated (VLSI) circuits needed to implement high-order filters and correlators.

Gray, Andrew A.↗

Search for New Bosons in Gluon-Gluon and Vector Boson Fusion Processes at the LHC and Development of Silicon Module Assembly Techniques for the CMS High Granularity Calorimeter

A search for heavy resonances decaying to a pair of vectors bosons is presented which utilizes events in which a hadronically decaying Z or W boson is identified using jet substructure techniques and large missing transverse momentum is found. Data analyzed were recorded by the Compact Muon Solenoid experiment at the CERN Large Hadron Collider in 2016, 2017, and 2018, and correspond to 137 fb$^{-1}$ . The events are categorized as having arisen from Vector Boson Fusion process or not, and are characterized by their transverse mass distribution. The standard model backgrounds are estimated based on observed yields in control regions. No excess of events above the expected SM background are observed and limits are placed on the production cross section of Radion (spin-0), Wprime (spin-1) and Bulk graviton (spin2) particles. In adiditon, the high luminosity LHC and the CMS HGCAL upgrade are also presented. The assembly techniques and various tests for the Silicon module and the cassette are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for a Neutral Gauge Boson with Nonuniversal Fermion Couplings in Vector Boson Fusion Processes in Proton-Proton Collisions at $\sqrt{𝑠}$ = 13 TeV

The first search for a heavy neutral spin-1 gauge boson (𝑍′) with nonuniversal fermion couplings produced via vector boson fusion processes and decaying to tau leptons or 𝑊 bosons is presented. The analysis is performed using LHC data at $\sqrt{𝑠}$ = 13 TeV, collected from 2016 to 2018 with the CMS experiment and corresponding to an integrated luminosity of 138 fb −1 . The data are consistent with the standard model predictions. Upper limits are set on the product of the cross section for production of the 𝑍′ boson and its branching fraction to 𝜏⁢𝜏 or 𝑊⁢𝑊. The presence of a 𝑍′ boson decaying to 𝜏 + ⁢𝜏 − (𝑊 + ⁢𝑊 − ) is excluded for masses up to 2.45(1.60) TeV, depending on the 𝑍′ boson coupling to standard model weak bosons, and assuming a 𝑍′→𝜏 + ⁢𝜏 − (𝑊 + ⁢𝑊 − ) branching fraction of 50%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Robust Vector BOTDA Signal Processing with Probabilistic Machine Learning

This paper presents a novel probabilistic machine learning (PML) framework to estimate the Brillouin frequency shift (BFS) from both Brillouin gain and phase spectra of a vector Brillouin optical time-domain analysis (VBOTDA). The PML framework is used to predict the Brillouin frequency shift (BFS) along the fiber and to assess its predictive uncertainty. We compare the predictions obtained from the proposed PML model with a conventional curve fitting method and evaluate the BFS uncertainty and data processing time for both methods. The proposed method is demonstrated using two BOTDA systems: (i) a BOTDA system with a 10 km sensing fiber and (ii) a vector BOTDA with a 25 km sensing fiber. The PML framework provides a pathway to enhance the VBOTDA system performance.

47 OTHER INSTRUMENTATION↗

A low-cost vector processor boosting compute-intensive image processing operations

Low-cost vector processing (VP) is within reach of everyone seriously engaged in scientific computing. The advent of affordable add-on VP-boards for standard workstations complemented by mathematical/statistical libraries is beginning to impact compute-intensive tasks such as image processing. A case in point in the restoration of distorted images from the Hubble Space Telescope. A low-cost implementation is presented of the standard Tarasko-Richardson-Lucy restoration algorithm on an Intel i860-based VP-board which is seamlessly interfaced to a commercial, interactive image processing system. First experience is reported (including some benchmarks for standalone FFT's) and some conclusions are drawn.

Adorf, Hans-Martin↗

Iterative techniques to estimate signature vectors for mixture processing of multispectral data

Two methods for obtaining the required spectral signatures for a particular mixture model are considered. For the model considered, the spectral signatures become signature vectors. The first method is based upon determination of the signature vectors in such a way that a measure of the inconsistency between the mixture model and the observed data is minimized. The second method is based upon determination of the signature vectors in such a way that the estimated mean percentage coverage of individual species matches apriori or ground truth estimates. The two methods proposed are applied to actual multispectral data in order to verify the concepts presented.

Salvato, P., Jr.↗

Erratum to: Search for the HH → $ b\overline{b}b\overline{b} $ process via vector-boson fusion production using proton-proton collisions at $ \sqrt{s} $ = 13 TeV with the ATLAS detector

One correction is noted for the paper. A wrong cross-section was used for the theory prediction in figure 6 due to not taking into account the VHH contamination properly in the rescaling formula for the signal samples. The change in the theory prediction leads to stricter exclusion limits on the di-vector-boson–di-Higgs-boson coupling modifier κ 2V . The observed excluded region corresponds to κ 2V < –0.43 and κ 2V > 2.56, while the expected exclusion is κ 2V < –0.55 and κ 2V > 2.72. Erratum JHEP 01 (2021) 145 fixed the description in the text but contains the uncorrected figure. The correct figure is shown in the new erratum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for the HH → $ b\overline{b}b\overline{b} $ process via vector-boson fusion production using proton-proton collisions at $ \sqrt{s} $ = 13 TeV with the ATLAS detector

A search for Higgs boson pair production via vector-boson fusion (VBF) in the $ b\overline{b}b\overline{b} $ final state is carried out with the ATLAS experiment using 126 fb –1 of proton- proton collision data delivered at $ \sqrt{s} $ = 13 by the Large Hadron Collider. This search is sensitive to VBF production of additional heavy bosons that may decay into Higgs boson pairs, and in a non-resonant topology it can constrain the quartic coupling between the Higgs bosons and vector bosons. No significant excess relative to the Standard Model expectation is observed, and limits on the production cross-section are set at the 95% confidence level for a heavy scalar resonance in the context of an extended Higgs sector, and for non-resonant Higgs boson pair production. Interpretation in terms of the coupling between a Higgs boson pair and two vector bosons is also provided: coupling values normalised to the Standard Model expectation of κ 2V < –0.76 and κ 2V > 2.90 are excluded at the 95% confidence level in data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Mapping Pixel Windows To Vectors For Parallel Processing

Mapping performed by matrices of transistor switches. Arrays of transistor switches devised for use in forming simultaneous connections from square subarray (window) of n x n pixels within electronic imaging device containing np x np array of pixels to linear array of n(sup2) input terminals of electronic neural network or other parallel-processing circuit. Method helps to realize potential for rapidity in parallel processing for such applications as enhancement of images and recognition of patterns. In providing simultaneous connections, overcomes timing bottleneck or older multiplexing, serial-switching, and sample-and-hold methods.

Duong, Tuan A.↗