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Self-energy Feynman Diagrams with Four Loops and 11 Internal Lines 21st

Self-energy Feynman Diagrams with Four Loops and 11 Internal...

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21st International conference on Computational Science and Its Applications (ICCSA)

作者： de Doncker, Elise Yuasa, Fukuko Western Michigan Univ Kalamazoo MI 49008 USA High Energy Accelerator Res Org KEK 1-1 OHO Tsukuba Ibaraki 3050801 Japan

ISBN: (纸本)9783030869762;9783030869755

We consider 4-loop Feynman diagrams with 11 internal lines. The associated 10-dimensional loop integrals are calculated for four diagrams with massive internal lines, and we further handle the massless case of the diagram referenced in the literature as M61. The computations are performed with double exponential (DE), Quasi-Monte Carlo (lattice and embedded lattice rules) and adaptive integration algorithms, which do not require any user input regarding the integrand behavior. The lattice rule methods are combined with a transformation to help alleviate boundary singularities. The embedded lattice rules are implemented in CUDA C and their execution is accelerated using an NviDIA Quadro GV100 GPU, whereas DE is parallelized over MPI and executed on an AMD cluster. Adaptive integration is performed with the ParInt multivariate integration package, which is also layered over MPI. For the massless M61 diagram we use a dimensional regularization approach and extrapolation. The results will be compared with respect to accuracy and efficiency, and verified with pySecDec.

关键词： Feynman loop diagrams Lattice rules Adaptive integration high performance computing Dimensional regularization

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The Pangeo Ecosystem: Interactive computing Tools for the geosciences: Benchmarking on HPC 6th

The Pangeo Ecosystem: Interactive Computing Tools for the Ge...

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6th Annual Workshop on HPC User Support Tools, HUST 2019, International Workshop on Software Engineering for HPC-Enabled Research, SE-HER 2019, and 3rd Workshop on Interactive high-performance computing, WIHPC 2019, held in conjunction with the International conference for high performance computing, Networking, Storage, and Analysis, SC 2019

作者： Odaka, Tina Erica Banihirwe, Anderson Eynard-Bontemps, Guillaume Ponte, Aurelien Maze, Guillaume Paul, Kevin Baker, Jared Abernathey, Ryan Laboratory for Ocean Physics and Satellite Remote Sensing UMR LOPS Ifremer Univ. Brest CNRS IRD IUEM Brest France National Center for Atmospheric Research BoulderCO United States CNES Computing Center Team Centre National d’Etudes Spatiales Toulouse France Lamont Doherty Earth Observatory Columbia University New York United States

ISBN: (纸本)9783030447274

The Pangeo ecosystem is an interactive computing software stack for HPC and public cloud infrastructures. In this paper, we show benchmarking results of the Pangeo platform on two different HPC systems. Four different geoscience operations were considered in this benchmarking study with varying chunk sizes and chunking schemes. Both strong and weak scaling analyses were performed. Chunk sizes between 64 MB to 512 MB were considered, with the best scalability obtained for 512 MB. Compared to certain manual chunking schemes, the auto chunking scheme scaled well. © 2020, Springer Nature Switzerland AG.

关键词： Benchmarking

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Polarization remote sensing of atmospheric coated-spherical aerosol based on optical vortex and parallel acceleration 8

Polarization remote sensing of atmospheric coated-spherical ...

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conference on high-performance computing in geoscience and remote sensing viII

作者： Guo, Lixin Shi, Chen-ge Huang, Qingqing Cheng, Mingjian Li, Jiangting Xidian Univ Sch Phys & Optoelect Engn Xian 710071 Shaanxi Peoples R China State Key Lab Pulsed Power Laser Technol Hefei 230037 Anhui Peoples R China

ISBN: (数字)9781510621688

ISBN: (纸本)9781510621688

Based on the scattering effect of vortex beams, the remote sensing for aerosol particles in different atmosphere environments is investigated. In this paper we regard the aerosol particle to a coated-spherical particle other than an uniform single particle as it's more consistent with the way it exists in the actual atmosphere. The influences of orbital angular momentum (OAM) mode, the beam width of vortex beams, the outer and inner radius on the performance on the remote sensing for coated-spherical particles in marine atmosphere are analyzed numerically. Results indicated that the runtime will sharply increase when the number of the orbital angular momentum modes is large enough. Therefore, the parallel acceleration technology is used by us in this paper to solve this problem.

关键词： topological charge coated-spherical vortex beam aerosol particles Mie scattering

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Gobal Forest Cover Mapping using Landsat and Google Earth Engine cloud computing 8

Gobal Forest Cover Mapping using Landsat and Google Earth En...

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8th International conference on Agro-Geoinformatics (Agro-Geoinformatics)

作者： Zhang, Xiaomei Long, Tengfei He, Guojin Guo, Yantao Chinese Acad Sci Aerosp Informat Res Inst Beijing Peoples R China Chinese Acad Sci Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781728121161

Nowadays, the access of Landsat data-sets and the ever-lowering costs of computing make it feasible to monitor the Earth's land cover at Landsat resolutions of 30 meter. However, the rapid forest-covered products on a large scale, such as intercontinental or global, is still challenging. By utilizing the huge catalog of satellite imagery as well as the high-performance computing capacity of Google Earth Engine, we proposed an automated pipeline for generating 30-meter resolution global-scale forest map from time-series of Landsat images, and a novel 30-meter resolution global forest map of 2018 is released. In this paper, we describe the methods to create products of forest cover at Landsat resolutions. First, we partitioned the landscapes into sub-regions of similar forest type and spatial continuity, thus maximizing spectral differentiation, simplifying classifier model and improving classification accuracy. Then, with the existing forest cover, which come from a variety of sources, a multi-source forest/non-forest sample set was established for machine algorithm learning training. Finally, a machine learning algorithm was used to obtain samples automatically, extract the characteristics of satellite images and establish the forest / non-forest classifier models. Taking the Landsat8 images in 2018 as a case, selecting satellite image features based on the study of forest reflectance, including on-board reflectivity, the index of forest vegetation and the texture features of each hand, using established forest eco-zoning and multi-source forest / non-forest sample points, we realized automated learning and classification of forest cover for three initial zones. The accuracy verification of forest cover products in the three region was carried on two aspects: collecting verification points on high resolution satellite imagery (e.g. google earth), and cross-validating the current globally disclosed forest cover products. These two methods will illustrate the accuracy

关键词： Google Earth Engine Global Forest Eco-zoning Forest Cover Products Random Forest (RF)

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A Hierarchical Model for Embedded Real-time Stereo Imaging 8

A Hierarchical Model for Embedded Real-time Stereo Imaging

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conference on high-performance computing in geoscience and remote sensing viII

作者： He, Wenjing Hu, Jian Zhou, Chuncheng Li, Chuanrong Li, Wei Han, Yalan Chinese Acad Sci Key Lab Quantitat Remote Sensing Informat Technol Acad Optoelect Beijing 100094 Peoples R China

ISBN: (数字)9781510621688

ISBN: (纸本)9781510621688

The special features of Stereo Imaging for LiDAR and hyperspectral sensor are multi-source data and complex algorithm, which will bring huge challenges to embedded real-time processing. To improve system performance, efficient software design is important. In this paper, based on the hardware platform with FPGA+2C6678, a hierarchical parallel model for software design is studied. In intermediate layer, an adaptive dynamic scheduling strategy and a two-stage pipeline parallel architecture based on message transmission are presented, which provide efficient connection between the top application design and the bottom hardware environment. The results indicate that this model is strongly supportive for the high-performance of embedded system, and is beneficial for the open and universal design.

关键词： stereo imaging real-time hierarchical model embedded system

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ScOSA - Application Development for a high-performance Space Qualified Onboard computing Platform 8

ScOSA - Application Development for a High-Performance Space...

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conference on high-performance computing in geoscience and remote sensing viII

作者： Schwenk, Kurt Ulmer, Moritz Peng, Ting German Aerosp Ctr DLR GSOC Munchner Str 20 D-82234 Wessling Germany German Aerosp Ctr DLR Simulat & Software Technol Lilienthalpl 7 D-38108 Braunschweig Germany

ISBN: (数字)9781510621688

ISBN: (纸本)9781510621688

Future onboard computing applications require signi ficantly greater computing performance than is currently provided by standard space qualified onboard computers. Examples of such applications include onboard data analysis and (rendezvous) navigation tasks. Therefore, the German Aerospace Center is currently developing Scalable On-board computing for Space Avionics (ScOSA). The aim of the ScOSA onboard computing platform is to deliver high performance, reliability, scalability and cost-efficiency. To reach these properties, a distributed computing platform approach is used, by which reliable radiation hardened computing nodes (LEON3's) are combined with several high performance computing nodes (Xilinx Zynq), connected over a high-bandwidth SpaceWire network. The execution platform consists of a distributed task-based framework. In this paper, the architecture, features and capabilities of the ScOSA onboard computing platform are presented from an application developer's view. A brief summary of the design goals and the general hardware and software architecture of the ScOSA system will be introduced. This is followed by a description of the programming model and the application interface, with a focus on how the distributed nature of the ScOSA system is handled. It will also be shown how an existing application can be integrated in the ScOSA system. The main part of this paper will focus on the computing performance attainable from the ScOSA platform. There will be a comparison of the computing performance of an example application executed on the ScOSA system versus a standard PC. It will also be demonstrated how the performance of an application can be improved by adapting it to the distributed computing architecture of the ScOSA platform. Furthermore, a short overview of the failure detection and recovery features of the ScOSA platform are described and how they can be integrated into an application.

关键词： computing systems Distributed computing Commercial off the shelf technology Software development Standards development Computer architecture Space operations Data processing Field programmable gate arrays Reliability

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performance of Global 3D model retrievals of the Martian surface using the UCL CASP-GO system on CTX stereo images on Linux clusters and Microsoft Azure® cloud computing platforms 8

Performance of Global 3D model retrievals of the Martian sur...

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conference on high-performance computing in geoscience and remote sensing viII

作者： Tao, Y. Muller, J-P. Univ Coll London Imaging Grp Mullard Space Sci Lab Dorking RH5 6NT Surrey England

ISBN: (数字)9781510621688

ISBN: (纸本)9781510621688

In this paper we introduce the Mars planet-wide 3D surface modelling work performed within the EU FP-7 iMars project which completed last year. In this report, we describe a fully automated multi-resolution DTM processing chain developed by the Imaging Group at UCL-MSSL, called CASP-GO based upon the heritage NASA Ames Stereo Pipeline (ASP) and the Gotcha image matcher. The CASP-GO system has been integrated into the Microsoft Azure cloud computing environment and successfully processed similar to 5,300 unique CTX DTMs covering similar to 19% of the Martian surface at 18m resolution.

关键词： 3D model DTM CASP-GO cloud computing Mars stereo CTX

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Multiclass Change Detection for Multidimensional Images in the Presence of Noise 8

Multiclass Change Detection for Multidimensional Images in t...

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conference on high-performance computing in geoscience and remote sensing viII

作者： Lopez-Fandino, Javier Heras, Dora B. Arguello, Francisco Univ Santiago de Compostela Ctr Singular Invest Tecnoloxias Informac CiTIUS Santiago De Compostela Spain Univ Santiago de Compostela Dept Elect & Computac Santiago De Compostela Spain

ISBN: (数字)9781510621688

ISBN: (纸本)9781510621688

Change Detection (CD) techniques applied over multitemporal multispectral or hyperspectral remote sensing images allow monitoring changes in the land use or catastrophe tracking, among other applications. A multiclass CD technique for multidimensional images that is robust in the presence of noise is presented in this paper. The technique combines fusion at feature level to perform a first change/no change labeling (binary CD) and a later stage with fusion at decision level that performs a supervised multidate classification of the changed pixels (multiclass CD) obtaining the final from-to change map. The acquisition of multidimensional images usually corrupts the original signal by adding noise. This noise can be related with natural random processes or it can be produced during the sensor operation. Additive White Gaussian Noise (AWGN) and speckle noise simulate these effects. In this paper the robustness of the proposed CD technique in noisy scenarios for these two types of noise of varying intensity is evaluated. The experimental results show that the proposed technique is more robust than other alternatives, achieving accuracies close to those obtained in the absence of noise. The proposed technique is designed to be efficiently computed in GPU, thus dealing with the high computational cost of the processing of multidimensional images.

关键词： Multiclass change detection remote sensing noise classification GPU

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Hyperspectral Compressive sensing - A Low Power Consumption Approach 8

Hyperspectral Compressive Sensing - A Low Power Consumption ...

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conference on high-performance computing in geoscience and remote sensing viII

作者： Nascimento, Jose M. P. V'estias, Mario Duarte, Rui Inst Telecomunicacoes Lisbon Portugal IPL Inst Super Engn Lisboa Lisbon Portugal INESC ID Lisbon Portugal Univ Lisbon Inst Super Tecn Lisbon Portugal

ISBN: (数字)9781510621688

ISBN: (纸本)9781510621688

Hyperspectral imaging instruments allow data collection in hundreds of spectral bands for the same area on the surface of the Earth. The resulting multidimensional data cube typically comprises several GBs per light. Due to the extremely large volumes of data collected by imaging spectrometers, hyperspectral data compression, dimensionality reduction and Compressive sensing (CS) techniques has received considerable interest in recent years. These data are usually acquired by a satellite or an airbone instrument and sent to a ground station on Earth for subsequent processing. Usually the bandwidth connection between the satellite/airborne platform and the ground station is reduced, which limits the amount of data that can be transmitted. As a result, there is a clear need for (either lossless or lossy) hyperspectral data compression techniques that can be applied on-board the imaging instrument. This paper, presents a study of the power and time consumption and accuracy of a parallel implementation for a spectral compressive acquisition method on a Jetson TX2 platform, which is well suited to perform vector operations such as dot products. This implementation exploits the architecture at low level, using shared memory and coalesced accesses to memory. The conducted experiments have been performed to demonstrate the applicability, in terms of accuracy, time consuming and power consumption of these methods for onboard processing. The results show that by using this low power consumption GPU is it possible to obtain real-time performance with a very limited power requirement.

关键词： Hyperspectral imaging Compressed sensing Data modeling Image compression Reconstruction algorithms Satellites Sensors

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Radar & Additive Manufacturing Technologies: the Future of Internet of Things (IoT)

Radar & Additive Manufacturing Technologies: the Future of I...

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IEEE Radar conference

作者： Hester, Jimmy G. D. Kimionis, John Bahr, Ryan Su, Wenjing Tehrani, Bijan Tentzeris, Manos M. Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

ISBN: (纸本)9781538641675

The authors make a case for a soon-to-be preponderance of radar technologies for communications with devices of the IoT. First, the tag architectures enabling these communications are presented. Novel 24 GHz and mm-wave flexible low-cost chip less RFID and backscatter/reflectarray-based node approaches demonstrating a record measured range of 80m, with a potential maximum range in excess of 1 km, zero to low W power consumption, and Gbps communications rates are presented. In a second part, recent advances in additive-manufacturing technologies enabling large cost reductions for the next generation of integrated radar ICs are reported. Specifically, the combination of 3D and inkjet printing enables the development of fully 3D compact low-cost integrated modules along with high-performance interconnects. These innovations, simultaneously empowering and empowered by radar technologies, present a compelling avenue for the emergence of dense constellations of flexible smart skin nodes for ubiquitous sensing, identification, and localization.

关键词： remote sensing mm-wave Chipless RFID Inkjet printing Flexible electronics Internet of Things Smart Skin

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