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检索条件"任意字段=Conference on High Performance Computer Modernization Program"

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Advancing Matrix Decomposition Efficiency: A Study on FT-Matrix DSP Based SVD Optimization 10

Advancing Matrix Decomposition Efficiency: A Study on FT-Mat...

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10th IEEE International conference on Cyber Security and Cloud Computing and 9th IEEE International conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Xie, Anxing Hu, Yonghua Cheng, Aobo Tang, Zhuoyou Liu, Peng Zhang, Xin Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan China

ISBN: (纸本)9798350312461

Matrix decomposition is a fundamental operation in linear algebra, and it has various applications in machine learning, signal processing, edge computing, and many other fields. Singular Value Decomposition (SVD) is a matrix decomposition method that can break down a matrix into three matrices: two orthogonal matrices and a diagonal matrix. With the development of domestic high-performance Digital Signal Value Processors (DSP), the demand for matrix computation based on DSP platforms is increasing. The research of SVD implemented based on DSP is important and meaningful. However, accessing the high-performance algorithm requires developers who are familiar with the hardware characteristics, in order to combine the unique features of the algorithm with the limited hardware resources. To reduce the cost of computing the SVD in matrix, we implement a vectorization mapping method for the SVD algorithm on the FT-M7002. The single instruction multiple data (SIMD) instructions embedded in the FT-M7002 processor were utilized to exploit the data-level parallelism in the SVD algorithm. Instead of using data movement and a scalar processing unit (SPU), we compute with a single vector processing element (VPE). Additionally, DMA transfer algorithm is designed to implement matrix transposition and resolve the issue of discontinuous data access. Experimental results show that the optimized SVD algorithm improves execution performance relative to the original SVD algorithm on FT by up to 5.0 ×. Furthermore, we demonstrate that the optimized SVD algorithm on the FT-M7002 performs 1.0-2.0× faster than the optimized SVD algorithm on TMS320C6678 processor. © 2023 IEEE.

关键词： Singular value decomposition

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SEMIREWARD: A GENERAL REWARD MODEL FOR SEMI-SUPERVISED LEARNING 12

SEMIREWARD: A GENERAL REWARD MODEL FOR SEMI-SUPERVISED LEARN...

引用

12th International conference on Learning Representations, ICLR 2024

作者： Li, Siyuan Jin, Weiyang Wang, Zedong Wu, Fang Liu, Zicheng Tan, Cheng Li, Stan Z. Zhejiang University College of Computer Science and Technology China Westlake University China

Semi-supervised learning (SSL) has witnessed great progress with various improvements in the self-training framework with pseudo labeling. The main challenge is how to distinguish high-quality pseudo labels against the confirmation bias. However, existing pseudo-label selection strategies are limited to pre-defined schemes or complex hand-crafted policies specially designed for classification, failing to achieve high-quality labels, fast convergence, and task versatility simultaneously. To these ends, we propose a Semi-supervised Reward framework (SemiReward) that predicts reward scores to evaluate and filter out high-quality pseudo labels, which is pluggable to mainstream SSL methods in wide task types and scenarios. To mitigate confirmation bias, SemiReward is trained online in two stages with a generator model and subsampling strategy. With classification and regression tasks on 13 standard SSL benchmarks across three modalities, extensive experiments verify that SemiReward achieves significant performance gains and faster convergence speeds upon Pseudo Label, FlexMatch, and Free/SoftMatch. Code and models are available at https://***/Westlake-AI/SemiReward. © 2024 12th International conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Benchmarking

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A Plug-and-Play Method for Rare Human-Object Interactions Detection by Bridging Domain Gap 24

A Plug-and-Play Method for Rare Human-Object Interactions De...

引用

32nd ACM International conference on Multimedia, MM 2024

作者： Zhang, Lijun Suo, Wei Wang, Peng Zhang, Yanning School of Computer Science and Ningbo Institute Northwestern Polytechnical University Shaanxi Xi'an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Shaanxi Xi'an China

ISBN: (纸本)9798400706868

Human-object interactions (HOI) detection aims at capturing human-object pairs in images and corresponding actions. It is an important step toward high-level visual reasoning and scene understanding. However, due to the natural bias from the real world, existing methods mostly struggle with rare human-object pairs and lead to sub-optimal results. Recently, with the development of the generative model, a straightforward approach is to construct a more balanced dataset based on a group of supplementary samples. Unfortunately, there is a significant domain gap between the generated data and the original data, and simply merging the generated images into the original dataset cannot significantly boost the performance. To alleviate the above problem, we present a novel model-agnostic framework called Context-Enhanced Feature Alignment (CEFA) module, which can effectively align the generated data with the original data at the feature level and bridge the domain gap. Specifically, CEFA consists of a feature alignment module and a context enhancement module. On one hand, considering the crucial role of human-object pairs information in HOI tasks, the feature alignment module aligns the human-object pairs by aggregating instance information. On the other hand, to mitigate the issue of losing important context information caused by the traditional discriminator-style alignment method, we employ a context-enhanced image reconstruction module to improve the model's learning ability of contextual cues. Extensive experiments have shown that our method can serve as a plug-and-play module to improve the detection performance of HOI models on rare categories. © 2024 ACM.

关键词： Object detection

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SharDAG: Scaling DAG-Based Blockchains Via Adaptive Sharding 40

SharDAG: Scaling DAG-Based Blockchains Via Adaptive Sharding

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40th IEEE International conference on Data Engineering, ICDE 2024

作者： Cheng, Feng Xiao, Jiang Liu, Cunyang Zhang, Shijie Zhou, Yifan Li, Bo Li, Baochun Jin, Hai School of Computer Science and Technology Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab China Hong Kong University of Science and Technology Hong Kong University of Toronto Canada

ISBN: (纸本)9798350317152

Directed Acyclic Graph (DAG)-based blockchain (a.k.a distributed ledger) has become prevalent for supporting highly concurrent applications. Its inherent parallel data structure accelerates block generation significantly, shifting the bottleneck from performance to storage scalability. An intuitive solution is to apply state sharding that divides the entire ledger (i.e., transactions and states) into multiple shards. While each node only stores proportional transactions, it suffers from the challenges of storing and ensuring the processing consistency of cross-shard transactions. In this paper, we propose SharDAG, a new mechanism that leverages adaptive sharding for DAG-based blockchains to achieve high performance and strong consistency. The key idea of SharDAG is to exploit unique characteristics -silent assets -and design a lightweight processing mechanism based on avatar account caching. Furthermore, we design a Byzantine resilient cross-shard verification mechanism with a theoretically optimal number of participating nodes, which guarantees the consistency and security of avatar account aggregation. Our comprehensive evaluations on real-world workloads demonstrate that SharDAG presents up to 3.8 x throughput improvement compared to the state-of-the-art and reduces the storage overhead of cross-shard transactions. © 2024 IEEE.

关键词： Blockchain

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Research on the Development and Application of Parallel programming Technology in Heterogeneous Systems 3

Research on the Development and Application of Parallel Prog...

引用

3rd International conference on Modeling, Simulation, Optimization and Algorithm, ICMSOA 2021

作者： Wu, Linghong School of Computer and Information Engineering Nanchang Institute of Technology JIANGXI Nanchang330044 China

In recent years, with the continuous improvement of high performance computing hardware platform,the application of high performance for a wide range of high-performance, traditional parallel programming environment tools cannot meet the growing demand for high-performance applications and the face of parallel software development environment in a relatively backward state. The heterogeneous system of the new coprocessor with a high performance and power ratio can have high performance computing needs to provide the task to accelerate. As a result, heterogeneous systems are becoming a new trend in high performance computing. However, with the introduction of the new coprocessor and the expansion of the system scale, heterogeneous systems are difficult to program the problem is also increasingly prominent. In view of this problem, this paper adopts the abstract technology to enhance the granularity of parallel programming, and designs a structured parallel programming prototype system which can achieve different levels of implicit parallelism © Published under licence by IOP Publishing Ltd.

关键词： Parallel programming

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Revalidating the Encoder-Decoder Depths and Activation Function to Find Optimum Vanilla Transformer Model

Revalidating the Encoder-Decoder Depths and Activation Funct...

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2023 International conference on computer Science, Information Technology and Engineering, ICCoSITE 2023

作者： Heryadi, Yaya Wijanarko, Bambang Dwi Fitria Murad, Dina Tho, Cuk Hashimoto, Kiyota Bina Nusantara University Graduate Program- Computer Science Computer Science Department BINUS Jakarta11480 Indonesia Bina Nusantara University Online Learning Computer Science Department BINUS Jakarta11480 Indonesia Bina Nusantara University BINUS Online Learning Information Systems Department Jakarta11480 Indonesia Prince of Songkla University Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Phuket83120 Thailand

ISBN: (纸本)9798350320954

The transformer model has become a state-of-the-art model in Natural Language Processing. The initial transformer model, known as the vanilla transformer model, is designed to improve some prominent models in sequence modeling and transduction problems such as language modeling and machine translation. The initial transformer model has 6 stacks of identical encoder-decoder layers with an attention mechanism whose aim is to push limitations of common recurrent language models and encoder-decoder architectures. Its outstanding performance has inspired many researchers to extend the architecture to improve its performance and computation efficiency. Despite many extensions to the vanilla transformer, there is no clear explanation of the encoder-decoder set out depth in the vanilla transformer model. This paper presents exploration results on the effect of combination encoder-decoder layer depth and activation function in the feed-forward layer of the vanilla transformer model on its performance. The model is tested to address a downstream task: text translation from Bahasa Indonesia to the Sundanese language. Although the value difference is not significantly large, the empirical results show that the combination of depth = 2 with Sigmoid, Tanh, and ReLU activation function;and d = 6 with ReLU activation shows the highest average training accuracy. Interestingly, d = 6 and ReLU show the lowest average training and validation loss. However, statistically, there is no significant difference between depth and activation functions. © 2023 IEEE.

关键词： Neural machine translation

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EVREAL: Towards a Comprehensive Benchmark and Analysis Suite for Event-based Video Reconstruction

EVREAL: Towards a Comprehensive Benchmark and Analysis Suite...

引用

2023 IEEE/CVF conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Ercan, Burak Eker, Onur Erdem, Aykut Erdem, Erkut Hacettepe University Computer Engineering Department Turkey Havelsan Inc Turkey Koç University Computer Engineering Department Turkey Koç University Kuis Ai Center Turkey

ISBN: (纸本)9798350302493

Event cameras are a new type of vision sensor that incorporates asynchronous and independent pixels, offering advantages over traditional frame-based cameras such as high dynamic range and minimal motion blur. However, their output is not easily understandable by humans, making the reconstruction of intensity images from event streams a fundamental task in event-based vision. While recent deep learning-based methods have shown promise in video reconstruction from events, this problem is not completely solved yet. To facilitate comparison between different approaches, standardized evaluation protocols and diverse test datasets are essential. This paper proposes a unified evaluation methodology and introduces an open-source framework called EVREAL to comprehensively benchmark and analyze various event-based video reconstruction methods from the literature. Using EVREAL, we give a detailed analysis of the state-of-the-art methods for event-based video reconstruction, and provide valuable insights into the performance of these methods under varying settings, challenging scenarios, and downstream tasks. © 2023 IEEE.

关键词： Cameras

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An Interactive and Flexible Widget-Based Whiteboard Platform for E-Learning 2

An Interactive and Flexible Widget-Based Whiteboard Platform...

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2nd International conference on Advanced computer Applications, ACA 2023

作者： Al-Shammari, Ahmed Al-Khaleefa, Ahmed Salih Alazzawi, Murtadha A. Almalchy, Mohammed Tali Albehadili, Hayder M. University of Al-Qadisiyah Computer Center Al Diwaniyah58002 Iraq University of Misan Faculty of Education Department of Physics Misan62001 Iraq Department of Computer Techniques Engineering Baghdad10001 Iraq Imam ja'Afar Al-Sadiq University Faculty of Information Technology Department of Computer Engineering Maysan10011 Iraq Missan Oil Company Maysan10011 Iraq

ISBN: (纸本)9798350341829

E-learning involves numerous virtual courses offered by primary universities or schools. Traditional courses prepared in a brick-and-mortar school facility are compared with online learning or virtual programs delivered through the internet. Existing works on whiteboard-based E-learning software have shown some limitations in terms of response time and high complexity. Therefore, in this paper, we proposed an interactive and flexible widget-based whiteboard platform to improve the performance of E-learning. Technically, we employed advanced software and programming languages to implement the proposed platform, such as C#, Dot Net Framework, Oxy-Plot, HelixToolKit, and MathPraser. The proposed platform is self-contained interactive modules. These modules can be easily searched and downloaded to the whiteboard program. A widget can be used to interactively and visually represent some concept, idea, or process. The experiments on real classroom cases verify the efficiency and effectiveness of the proposed work. This improvement supports different e-learning scenarios, especially a better teacher/student experience. © 2023 IEEE.

关键词： E-learning

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Optimizing Winograd Convolution on GPUs via Multithreaded Communication 2

Optimizing Winograd Convolution on GPUs via Multithreaded Co...

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2nd International conference on Algorithms, Microchips, and Network Applications, AMNA 2023

作者： An, Yunqing Li, Bin Bu, Jingde Gao, Ya School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450000 China

ISBN: (纸本)9781510664791

In advanced high-performance computing (HPC), convolution operations take a big proportion in convolutional neural networks, and convolutional neural networks very common in image and video based deep learning applications, because of which, this paper takes improving the performance of convolution operation as the research direction. Convolution can be performance in many ways, such as using mathematical definition to calculate, conversing to Fast Fourier Transform (FFT), conversing to batch matrix multiplication (im2col) or using Winograd algorithm. For small filter, Winograd has unique advantages. AMD based ROCm environment, the implementation of Winograd and an optimization method of Winograd based on multi-thread communication algorithm are introduced in this paper. For the Winograd convolution in ROCm 2.9.0, the speed of the algorithm was increased by more than 150% after optimization in this paper. Under some certain computing power ituations, the performance of the optimization algorithm approaches or even exceeds cuDNN and MIOpen. © 2023 SPIE.

关键词： Convolution

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Using Escape Rooms to Apply Team Building and Leadership Skills in an Engineering Leadership Development program: A Work in Progress

Using Escape Rooms to Apply Team Building and Leadership Ski...

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2023 ASEE Annual conference and Exposition - The Harbor of Engineering: Education for 130 Years, ASEE 2023

作者： Melvin, Elizabeth Michelle Bowles, Boz Steele, Adrienne Louisiana State University A&M College United States

Performing under pressure is common in engineering. Many engineers work in fields with pressing deadlines, on projects where millions or even billions of dollars, public safety, or the lives of the end user of their designs are at stake. Engineering and computer science-based professions account for just under 6% the 800+ high-stress professions reported by ONET [1]. Helping students to develop strategies for performing on teams effectively in stressful situations is essential for their successful goal achievement, productivity and team performance in their future engineering careers [2], [3]. This EL work in progress design paper will introduce a model for a non-traditional engineering leadership development activity. Specifically, this paper will explore the incorporation of a simulated stressful situation (escape room) paired with the introduction of psychometric/behavioral profiling, curated reflective activities, and placement of the event in a scaffolded series of workshops. Through pre- and post-survey evaluations and evaluation of the post-activity reflection exercise, the change in students' attitudes towards teamwork, self-perception of their role on teams, their perceptions of the importance of clear communication with teammates and their comfort level of effectively working on teams will be examined. The Chevron Leadership Academy at Louisiana State University is a corporate-sponsored, extracurricular leadership program. As part of this program, students attend a series of workshops covering a variety of leadership development topics. One is a game-based, team-building event-participation in an award-winning escape room activity, 13th Gate Escape in Baton Rouge, Louisiana. The goals of this activity are to help the students apply strategy skills to improve teamwork, to learn how to thrive as a team in a high-pressure situations, and to increase their confidence in their own leadership skills. Recognizing the importance of connecting activities to reflect

关键词： Students

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