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TCCL: Discovering Better Communication Paths for PCIe GPU Clusters 24

TCCL: Discovering Better Communication Paths for PCIe GPU Cl...

引用

29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2024

作者： Kim, Heehoon Ryu, Junyeol Lee, Jaejin Dept. of Computer Science and Engineering Seoul National University Seoul Korea Republic of Dept. of Data Science Dept. of Computer Science and Engineering Seoul National University Seoul Korea Republic of

ISBN: (纸本)9798400703867

Exploiting parallelism to train deep learning models requires GPUs to cooperate through collective communication primitives. While systems like DGX, equipped with proprietary interconnects, have been extensively studied, the systems where GPUs mainly communicate through PCIe have received limited attention. This paper introduces TCCL, a collective communication library designed explicitly for such systems. TCCL has three components: a profiler for multitransfer performance measurement, a pathfinder to discover optimal communication paths, and a modified runtime of NCCL to utilize the identified paths. The focus is on ring-based collective communication algorithms that apply to popular communication operations in deep learning, such as AllReduce and AllGather. The evaluation results of TCCL on three different PCIe-dependent GPU clusters show that TCCL outperforms (up to ×2.07) the state-of-the-art communication libraries, NCCL and MSCCL. We also evaluate TCCL with DL training workloads with various combinations of parallelism types. © 2024 Copyright held by the owner/author(s).

关键词： Graphics processing unit

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Asynchronous communication for complicated e-commerce applications 3

Asynchronous communication for complicated e-commerce applic...

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3rd International Conference on Quality Software, QSIC 2003

作者： Cao, Wei Qi Li, Juan Zi Wang, Ke Hong Zeng, Tao Knowledge Engineering Group Dept. of Computer Science and Technology Tsinghua University Beijing100084 China

ISBN: (纸本)0769520154

In this paper, we explored the various complicated e-commerce applications enhanced by loosely coupled asynchronous communication. And then, we put forward the automatic modeling of e-commerce based on the server-side component models. It fully leverages the various features of the underlying middleware services and meanwhile combines the dynamic modeling and coordination feature of workflow with the auto-generation and logic integration of the components. It realizes the faster development of workflow management system and also satisfies the demand of swift flexibility and extensibility on the business logic. © 2004 IEEE.

关键词： Middleware

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Detection of Geometry-based Adversarial Facial Attacks using Error Level Analysis

Detection of Geometry-based Adversarial Facial Attacks using...

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2022 IEEE Region 10 International Conference, TENCON 2022

作者： Sadu, Chiranjeevi Das, Pradip K. Rajiv Gandhi University of Knowledge Technologies Dept. of Computer Science and Engineering Nuzvid India Indian Institute of Technology Guwahati Dept. of Computer Science and Engineering Guwahati India

ISBN: (数字)9781665450959

ISBN: (纸本)9781665450959

Despite Machine Learning (ML) and Deep Learning (DL) models in specific have achieved significant success in various applications of computer vision in recent years, they remain vulnerable to carefully crafted, human-invisible adversarial attacks. Adversarial attacks are generated intentionally by adding small perturbations to an input image to mislead the classifier. This paper investigates a new defense method against geometry-based adversarial face attacks that significantly mitigate the impact of such adversarial attacks on image-classification models. We generate geometry-based adversarial face images based on Fast Landmark Manipulation (FLM) method and Error Level Analysis (ELA) is performed to effectively discriminate adversarial face images from clean images. The performance of the proposed defense method is demonstrated on a real-world dataset with different types of classifiers. The experimental results show that our defense method can effectively detect adversarial face images from clean images with 99.75% accuracy. © 2022 IEEE.

关键词： Geometry

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Swapping face images based on augmented facial landmarks and its detection

Swapping face images based on augmented facial landmarks and...

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2020 IEEE Region 10 Conference, TENCON 2020

ISBN: (纸本)9781728184555

Facial landmark points that are precisely extracted from the face images improve the performance of many applications in the domains of computer vision and graphics. Face swapping is one of such applications. With the availability of sophisticated image editing tools and the use of deep learning models, it is easy to create swapped face images or face swap attacks in images or videos even for non-professionals. Face swapping transfers a face from a source to a destination image, while preserving photo realism. It has potential applications in computer games, privacy protection, etc. However, it could also be used for fraudulent purposes. In this paper, we propose an approach to create face swap attacks and detect them from the original images. The augmented 81-facial landmark points are extracted for creating the face swap attacks. The feature descriptors Weighted Local Magnitude Patterns (WLMP) and Support Vector Machines (SVM) are utilized for the swapped face images detection. The performance of the proposed approach is demonstrated by different types of SVM classifiers on a real-world dataset. Experimental results show that the proposed system effectively does face swapping and detection with an accuracy of 95%. © 2020 IEEE.

关键词： Computer games

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The twitter bullishness index: A social media analytics indicator for the stock market 16

The twitter bullishness index: A social media analytics indi...

引用

20th International database engineering and Applications Symposium, IDEAS 2016

作者： Barrelet, Carl Julien Kuzulugil, Sebnem Sahin Bener, Ayşe Başar Data Science Lab Dept. of Mechanical and Industrial Engineering Ryerson University Canada

ISBN: (纸本)9781450341189

The Twitter Bullishness Index (TBI) has previously been reported to be a social media analytics indicator for the stock market. We explore the different components that shape the TBI. First, we determine the users to be dominated by the US and the Englishspeaking world. Second, we applied the Natural Language Processing tool term frequency-inverse document frequency (TFIDF) to explore the tweet content that contribute to the TBI. We revealed that the keyword lexicon associated with the terms bullish and bearish differs. Finally, we used the vector autoregression framework. Our results do not show the TBI to be a leading indicator for the returns of the Dow Jones Industrial Average (DJIA) within statistical significance. However, a Pearson correlation of 0.49 is observed between the TBI and the DJIA return. © ACM 2016.

关键词： Financial markets

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Interacting with digital cultural heritage collections via annotations: The CULTURA approach 13

Interacting with digital cultural heritage collections via a...

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2013 ACM Symposium on Document engineering, DocEng 2013

作者： Agosti, Maristella Conlan, Owen Ferro, Nicola Hampson, Cormac Munnelly, Gary Dept. of Information Engineering University of Padua Via Gradenigo 6/a Padua Italy Knowledge and Data Engineering Group Trinity College Dublin Ireland

ISBN: (纸本)9781450317894

This paper introduces the main characteristics of the digital cultural collections that constitute the use cases presently in use in the CULTURA environment. A section on related work follows giving an account on efforts on the management of digital annotations that are pertinent and that have been considered. Afterwards the innovative annotation features of the CULTURA portal for digital humanities are described;those features are aimed at improving the interaction of non-specialist users and general public with digital cultural heritage content. The annotation functions consist of two modules: the FAST annotation service as back-end and the CAT Web front-end integrated in the CULTURA portal. The annotation features have been, and are being, tested with different types of users and useful feedback is being collated, with the overall aim of generalising the approach to diverse document collections and not only the area of cultural heritage. © 2013 ACM.

关键词： Digital libraries

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A Detection Method for Copy-Move Forgery Attacks in Digital Images

A Detection Method for Copy-Move Forgery Attacks in Digital ...

引用

2022 IEEE Region 10 International Conference, TENCON 2022

ISBN: (数字)9781665450959

ISBN: (纸本)9781665450959

Digital images are carrying important information in many real-world applications such as surveillance, courts of law as evidence for crimes, journalism, scientific publications, and medical imaging. Manipulating these images becomes easy due to the paramount image processing and editing tools. Thus, the authentication of digital images becomes one of the principal problems in digital image forensics and attracts the attention of the research community. In this paper, we focus on the detection of copy-move forgery attacks in digital images. It is one of the most actively used attacks. It copies some region of the image and pastes it into one or more parts of the same image to cover or emphasize important scenes in the image. We propose a method to detect such forgery regions based on Speeded Up Robust Features (SURF) and Binary Robust Invariant Scalable Keypoints (BRISK) descriptors. Both fused features are matched and performed clustering to reduce the false positives using Hierarchical Agglomerative Clustering (HAC). The proposed method is tested on real-world copy-move datasets. Experimental results show that our method is robust against various geometric transformations and able to precisely determine the forged regions. © 2022 IEEE.

关键词： Medical imaging

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An algorithmic approach to missing data problem in modeling human aspects in software development 9

An algorithmic approach to missing data problem in modeling ...

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9th International Conference on Predictive Models in Software engineering, PROMISE 2013

作者： Calikli, Gul Bener, Ayse Data Science Laboratory Dept. of Mechanical and Industrial Engineering Ryerson University Canada

ISBN: (纸本)9781450320160

Background: In our previous research, we built defect prediction models by using confirmation bias metrics. Due to confirmation bias developers tend to perform unit tests to make their programs run rather than breaking their code. This, in turn, leads to an increase in defect density. The performance of prediction model that is built using confirmation bias was as good as the models that were built with static code or churn metrics. Aims: Collection of confirmation bias metrics may result in partially "missing data" due to developers' tight schedules, evaluation apprehension and lack of motivation as well as staff turnover. In this paper, we employ Expectation-Maximization (EM) algorithm to impute missing confirmation bias data. Method: We used four datasets from two large-scale companies. For each dataset, we generated all possible missing data configurations and then employed Roweis' EM algorithm to impute missing data. We built defect prediction models using the imputed data. We compared the performances of our proposed models with the ones that used complete data. Results: In all datasets, when missing data percentage is less than or equal to 50% on average, our proposed model that used imputed data yielded performance results that are comparable with the performance results of the models that used complete data. Conclusions: We may encounter the "missing data" problem in building defect prediction models. Our results in this study showed that instead of discarding missing or noisy data, in our case confirmation bias metrics, we can use effective techniques such as EM based imputation to overcome this problem.

关键词： Defect density

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Text Sentiment Analysis of Film Reviews Using Bi-LSTM and GRU 4

Text Sentiment Analysis of Film Reviews Using Bi-LSTM and GR...

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4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023

作者： Mouthami, K. Yuvaraj, N. Thilaheswaran, K.K. Lokeshvar, K.J. Kpr Institute of Engineering and Technology Dept. of Computer Science Engineering Coimbatore India Kpr Institute of Engineering and Technology Dept. of Artificial Intelligence and Data Science Coimbatore India

ISBN: (纸本)9798350300093

Sentiment analysis is a vast subject to explore in natural language processing (NLP) techniques. The film reviews were analyzed and segregated into positive, neutral, and negative reviews. The proposed model examines two distinct datasets, one with multi-class labels and the other with binary-type class labels. The preprocessing is done by using the bag of words and skip-gram word2vec, variety of classifiers, including Two state Gated recurrent units (TS-GRU), was used for binary classification, and the Bidirectional Long Short-Term Memory (Bi-LSTM for the multi-class situation was implemented. Bi-LSTM was utilized in the model, in which symmetric Bi-LSTM replaces the LSTM approaches to get around the high computational cost of training the normal LSTM. The Bi-LSTM has equivalent accuracy to the LSTM while significantly reducing computational costs. Sentiment analysis offers a glimpse of how consumers feel about certain movies. This endeavor is undertaken via the study of natural language processing, in which sentiment analysis is a branch which examines how words are arranged and utilized to extract meaning from user writing. This helps to investigate further the methods for deciphering such data thanks to significant advancements in machine learning techniques;with Keras API and the Internet Movie database (IMDb) dataset, this study compares single and multi-branch CNN with Bidirectional LSTMs with different kernel sizes. GRU achieved 98.24% of accuracy, and bi-LSTM achieved 98.65% of accuracy. © 2023 IEEE.

关键词： Sentiment analysis

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Analysis and Ranking Resume using Machine Learning Algorithms and NLP 1

Analysis and Ranking Resume using Machine Learning Algorithm...

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Deshmukh, Pratik Chandrasen Bendre, M.R. Pravara Rural Engineering College Dept. of Data Science Engineering Loni India Pravara Rural Engineering College Dept. of Computer Engineering Loni India

ISBN: (纸本)9798350356816

Specialized recruiting firms have emerged as a result of the expansion of the Indian employment market. These agencies use machine learning models to expedite the hiring process and provide their clients with the best candidates. Thus, the suggested methodology offers the potential to improve the hiring process by incorporating the advantages of machine learning in addition to natural language processing(NLP). Employing NLP techniques, one may accurately grade resumes according to the company's criteria and extract useful information from them. After thorough testing and improvement, the web portal might prove to be an invaluable tool for hiring managers and job seekers ***, one might think about adding features to the CV classifier and ranker, such as customized feedback and recommendations for enhancements that might assist candidates in understanding where they might be lacking and increase their chances of getting recruited. © 2024 IEEE.

关键词： Adversarial machine learning

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