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共 2792 条记录，以下是121-130 订阅

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MISA-MD: A New Design of Molecular Dynamics Software for GPU Architecture 24

MISA-MD: A New Design of Molecular Dynamics Software for GPU...

引用

24th IEEE international conference on High Performance Computing and Communications, 8th IEEE international conference on Data Science and Systems, 20th IEEE international conference on Smart City and 8th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Chu, Genshen Chen, Tianyi Chen, Dandan Bai, He Li, Guannan Ren, Shuai Li, Yang School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Beijing Research Center Zhejiang Lab Beijing China

ISBN: (纸本)9798350319934

Molecular dynamics is a significant method in computational material and many other fields, and is computationally intensive. In this paper, we present a new molecular dynamics software, MISA-MD, which is mainly designed for high computational performance on GPU architecture. the main contributions include a redesign of the atom data structure, communication optimizations, parallel strategies and a series of GPU optimizations on memory accessing. Compared to the CPU version, the presented version of MISA-MD can achieve more than 130 speedup when running on GPU hardware. Moreover, our MISAMD code also demonstrates 51 % performance improvement, when compared to the well-known software LAMMPS on GPU. © 2022 IEEE.

关键词： Graphics processing unit

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parallel Secure Inference for Multiple Models Based on CKKS 8th

Parallel Secure Inference for Multiple Models Based on CKKS

引用

8th international Joint conference on Web and Big Data and Web-Age Information Management (APWeb-WAIM)

作者： Wu, Weibin Wang, Ying Zhang, Yangpan Wang, Luyao Zhou, Lu Nanjing Univ Aeronaut & Astronaut Nanjing Peoples R China Peking Univ Beijing Peoples R China

ISBN: (纸本)9789819772407;9789819772414

Homomorphic encryption is utilized in machine learning to safeguard the privacy of user data and server's model parameters. CKKS is a homomorphic scheme that supports complex computation and has better performance than BFV. this gives CKKS an advantage when applied to machine learning. However, existing secure inference frameworks based on homomorphic encryption are mainly adopted in BFV or BGV, as these schemes have more batching slots than CKKS. In this paper, we propose two parallel inference methods based on CKKS to enhance the batching capabilities (called parallelism) of CKKS, model parallelism and sample parallelism. the model parallelism is facilitative to inference of two models at the same time and improves inference performance. this is the main method to mitigate the parallelism gap between BFV and CKKS. Meanwhile, sample parallelism allows multiple samples to be inference simultaneously to decrease the number of decrypt operations and communication. Subsequently, we apply the two parallel techniques to phenotypic inference from genetic data. Experimental results show that our method improves the performance by at least 47.8% compared to the method without parallel techniques.

关键词： Privacy Preserving Machine Learning CKKS Homomorphic Encryption Secure Inference parallel Inference

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2023 IEEE international conference on Rebooting Computing, ICRC 2023

2023 IEEE International Conference on Rebooting Computing, I...

引用

8th IEEE international conference on Rebooting Computing, ICRC 2023

ISBN: (纸本)9798350382044

the proceedings contain 26 papers. the topics discussed include: high-speed compilation of large-scale stochastic circuits;PimCity: a compute in memory substrate featuring both row and column parallel computing;clustering vehicle routing problems on specialized hardware;design considerations for 3D heterogeneous integration driven analog processing-in-pixel for extreme-edge intelligence;a memcomputing approach to prime factorization;performance comparison of memristor crossbar-based analog and FPGA-based digital weight-memory-less neural networks;accelerating VQE algorithm via parameters and measurement reuse;arithmetic primitives for efficient neuromorphic computing;and statistical characterization of ReRAM arrays for analog in-memory computing.

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A Study on the Data-Driven Learning Mode of College Spoken Language processing Based on Multimedia Corpus 23

A Study on the Data-Driven Learning Mode of College Spoken L...

引用

8th international conference on Distance Education and Learning, ICDEL 2023

作者： Wu, Minghai School of Foreign Languages Shenyang Jianzhu University China

ISBN: (纸本)9798400700422

this paper briefly introduces the research and development of data-driven learning at home and abroad, and emphatically discusses how to introduce the concept of data-driven learning, together with the use of multimedia corpus to assist college Spoken language processing. the study proposes a data-driven learning method based on a multimedia corpus for college English. then, it illustrates the specific process and advantages of the learning mode from the aspects of design purpose, construction ideas and methods, so as to provide learners with a real language environment and meet the needs of foreign language listening and speaking ability training. © 2023 ACM.

关键词： Learning systems

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Unsupervised STDP-based Radioisotope Identification Using Spiking Neural Networks Implemented on SpiNNaker 8

Unsupervised STDP-based Radioisotope Identification Using Sp...

引用

8th international conference on Event-Based Control, Communication and Signal processing (EBCCSP)

作者： Xie, Shouyu Jones, Edward Marsden, Edward Baistow, Ian Furber, Steve Mitra, Srinjoy Hamilton, Alister Univ Edinburgh Sch Engn Edinburgh Midlothian Scotland Univ Manchester Sch Engn Manchester Lancs England Kromek Grp Plc Durham England

ISBN: (数字)9781665453493

ISBN: (纸本)9781665453493

this paper presents a spiking neural network (SNN) implementation which employs unsupervised feature extraction using spike timing dependent plasticity (STDP) to classify 8 different radioisotopes. With the implementation, the accuracy could reach 80% during training and overall testing accuracy of 72%. the whole network was implemented on SpiNNaker, a spiking neural network emulation platform. this work shows that unsupervised STDP, an SNN native training method, can be applied to the classification task of RIID to provide event-based training as well as inference.

关键词： event-based processing spiking neural networks STDP radioisotope identification neuromorphic computing

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EgpuIP: An Embedded GPU Accelerated Library for Image processing 24

EgpuIP: An Embedded GPU Accelerated Library for Image Proces...

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作者： Wang, Luhan Jia, Haipeng Zhang, Yunquan Li, Kun Wei, Cunyang Institute of Computing Technology Chinese Academy of Sciences State Key Lab of Processors Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Microsoft Research China

ISBN: (纸本)9798350319934

With the advances of embedded GPUs' programming models like GLES and OpenCL, the mobile processor has gained more parallel computing capability, which enables real-time image processing on portable devices. GLES is an excellent option to implement high-performance image processing on embedded GPUs due to its low hardware overhead. However, most GLES studies only focus on porting specific algorithms to embedded GPUs without a general optimization guide. In order to address the pending problems, this paper presents effective performance optimization chains to guide the optimization of image processing algorithms by using GLES. the image processing algorithms can be divided into three modes including data-independent, data-sharing and data-related according to their memory access and calculation characteristics. Based on this classification, our optimization chains contain four optimization directions. 1) Optimizing access to off-chip memory for the memory-bound data-independent algorithm;2) Exploiting data locality by utilizing shared memory and cache for the data-sharing algorithm;3) Redesigning the algorithm to optimize the sharing of computational results between threads for the data-related algorithm;4) Making full use of computation resource for the above three algorithms. Based on these optimization chains, we design an embedded GPU accelerated image processing library, EgpuIP. To evaluate specific optimization methods and performance improvements, we employ histogram equalization, Gaussian pyramid and integral filter as the representative algorithm from EgpuIP and adequately optimize them guided by the proposed optimization chains. Compared to the OpenCV, experiments show that the three algorithms in EgpuIP provide up to 19×88×, and 3× speedup respectively. © 2022 IEEE.

关键词： Graphics processing unit

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Study of Natural Gamma Full Energy Spectral Observations in Soil 8th

Study of Natural Gamma Full Energy Spectral Observations in ...

引用

8th international conference on Mineral Resources, Geotechnology and Geological Exploration

作者： Han, Daobing Meng, Qingxin Hebei Geol Univ Shijiazhuang Hebei Peoples R China

ISBN: (纸本)9783031786921;9783031786907;9783031786891

Natural gamma survey technology is based on the differences in radioactivity (energy spectrum radiation) of the stratigraphic medium, through observation and study of the changing law of the gamma-ray energy spectrum to solve geological problems of a large class of exploration, detection and monitoring methods. Conventional natural gamma energy spectroscopy surveys are mainly applied in the fields of uranium mining, metal ore census, resource exploration, etc., with fewer applications in soil testing. Traditional soil testing generally requires steps such as sampling, air-drying, sieving, measuring and analysing, which is not only costly and time-consuming, but also consumes a lot of manpower and resources. To address this phenomenon, this study firstly used a portable nuclide meter to measure the soil quickly, and then used matlab to process the original whole gamma energy spectrum data with segmented sampling, which can achieve the effect of rapid qualitative analysis of the soil and improve the efficiency of traditional soil testing.

关键词： Soil testing Natural Gamma Full Spectrum Data processing

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PC-BNA: parallel Convolution Binary Neural Network Accelerator 24

PC-BNA: Parallel Convolution Binary Neural Network Accelerat...

引用

作者： Liu, Haihui Zhang, Yuang Zheng, Xiangwei Yu, Mengxin An, Baoxu Liu, Xiaojie School of Information Science and Engineering Shandong Normal University Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan China

ISBN: (纸本)9798350319934

Binary neural network (BNN) is widely used in speech recognition, image processing and other fields to save memory and speed up computing. However, the accuracy of the existing binarization scheme in the realistic dataset is obviously low, and the input layer uses 32-bit floating point to avoid excessive precision loss, which requires additional computing units and increases the computational burden. therefore, it is very important to improve the input layer, save computing resources and reduce precision loss. In this paper, we propose a parallel convolution binary neural network accelerator architecture (PC-BNA). Based on our proposed BNN model, we design an efficient field programmable gate array (FPGA) based accelerator. the input of the first layer is binarized, the traditional binary convolution layer is replaced by a parallel binary convolution, and the network building blocks are improved. the experimental results show that the proposed PC-BNA has higher accuracy and better performance on CIFAR-10. the image recognition accuracy is as high as 91.4%, which is superior to the state-of-art of the BNN accelerator. Compared to the state-of-the-art BNN model, when using the same model size, the use of look-up-table (LUT) saves 9.08%, and the digital signal processor (DSP) saves 27.7%. the results suggest that it is promising for PC-BNA in future high performance mobile artificial intelligence applications. © 2022 IEEE.

关键词： Convolution

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Classification of Transient Power Quality Disturbances Based on Digital Image processing Techniques 8

Classification of Transient Power Quality Disturbances Based...

引用

8th international conference on Power and Renewable Energy, ICPRE 2023

作者： Guo, Feng Li, Jian Xu, Xu Zhu, Yizhi Luo, Xiaoyuan Qian, Wangkai State Grid Zhejiang Electric Power Co. Ltd. Taizhou China State Grid Zhejiang Electric Power Co. Ltd. Taizhou Power Supply Company Taizhou China Nanjing Institute of Technology School of Electrical Engineering Nanjing China

ISBN: (纸本)9798350328813

With the advancement of technology and the transformation of energy systems, electrical energy has become an essential part of various industries. In modern active distribution networks, there have been new trends in the structure of distribution networks and loads. the sensitivity of devices has increased, and issues related to voltage oscillations and voltage sag have become increasingly important in terms of power quality. therefore, improving power grid quality requires rapid and efficient classification and detection of various disturbances. To achieve accurate classification and identification of disturbance signals, digital image processing methods such as gamma correction, edge detection, and local extremum analysis can be used. By extracting the morphological characteristics of disturbance signals, effective classification and recognition of disturbance types can be achieved. Subsequently, normalization processing is applied to the power quality disturbance data, generating new grayscale images. Analysis of experimental data indicates that the improved method for transient power quality disturbance classification has higher accuracy, making it a feasible and efficient approach. © 2023 IEEE.

关键词： active distribution network digital image processing disturbance classification power quality

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Poster: Automatic Compliance Analysis on Clinical Notes and Lifestyle Guidelines in Cancer Survivorship 8

Poster: Automatic Compliance Analysis on Clinical Notes and ...

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8th IEEE/ACM international conference on Connected Health - Applications, Systems and Engineering Technologies (CHASE)

作者： Hou, Yujia Mostafa, Javed Univ N Carolina Carolina Hlth Informat Program Chapel Hill NC 27515 USA

ISBN: (纸本)9798400701023

Maintaining a healthy lifestyle has been proven to have significant benefits in cancer survivorship. It is expected that clinicians have a comprehensive understanding of publicly published cancer lifestyle guidelines and can effectively convey the information to patients. the objective of this paper is to develop an automatic text analysis method to assess the compliance of lifestyle information provided during medical visits and publicly available guidelines. Preliminary results show that selected lifestyle keywords appear an average of 3.54 times per medical visit, and 7% of medical notes pertain to patients' lifestyle. Semantic analysis and word dictionary will be applied to evaluate the extent of information compliance and inform strategies for improving lifestyle recommendations for cancer survivors.

关键词： Textual analysis natural language processing compliance analysis lifestyle cancer survivorship

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