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

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Usage of Static Taint Analysis and Auto Rule Generation for Smart Contract Vulnerability Detection 15

Usage of Static Taint Analysis and Auto Rule Generation for ...

引用

15th International conference on Information and Communication Technology Convergence, ICTC 2024

作者： Son, Ki Soo Shin, Jinmyeong Hwang, Seon-Jin Choi, Yoon-Ho School of Computer Science and Engineering Pusan National University Busan Korea Republic of

ISBN: (纸本)9798350364637

With the advent of Bitcoin, virtual currency and blockchain technology are attracting attention, and the market is growing with the addition of the smart contract function of Blockchain 2.0. With the growth of the blockchain market, financial damage using the vulnerabilities of virtual currency and smart contracts is increasing. Recently, many studies have been conducted to detect smart contract vulnerabilities, and various methods using static and dynamic analysis exist. This paper proposes a method to detect smart contract vulnerabilities using static analysis and association mining techniques. From the experiment, we show that the performance of the proposed method is high compared to well-known open-source tools. We observe the effectiveness of static taint analysis for smart contract vulnerability detection. The proposed method shows high performance against reentrancy vulnerabilities. We expected that rapid response will be possible when a new type of vulnerability occurs in the future. © 2024 IEEE.

关键词： Smart contract

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Expediting higher Fidelity Plasma State Reconstructions for the DIII-D National Fusion Facility Using Leadership Class Computing Resources

Expediting Higher Fidelity Plasma State Reconstructions for ...

引用

2024 Workshops of the International conference for high performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Smith, Sterling Paul Anthony Xing, Zichuan Amara, Torrin Bechtel Sebastian Denk, Severin Deshazer, Earl William Meneghini, Orso Neiser, Tom Stephey, Laurie Antepara, Oscar Clark, Christopher Mitchell Dart, Eli Ding, Pengfei Flanagan, Sean Nazikian, Raffi Schissel, David Simpson, Christine Tyler, Nicholas Scoville Uram, Thomas D Williams, Samuel Webb General Atomics San Diego United States Lawrence Berkeley National Laboratory Berkeley United States Argonne National Laboratory Lemont United States

ISBN: (纸本)9798350355543

The OMFIT CAKE workflow for plasma state reconstruction has been automated on the DIII-D National Fusion Facility to run on a combination of computational resources at DIII-D and the National Energy Research Computing (NERSC) Center, utilizing the emerging DOE Integrated Research Infrastructure (IRI). The reconstruction of the plasma state is vital for understanding what occurred in the DIII-D machine during the pulse. This understanding allows informed decisions to be made on how to change the configuration for the next pulse. The initial reconstruction workflow was performed on DIII-D resources for a benchmark case in 62 minutes. The wall-clock time for the benchmark case was reduced to 11 minutes by running on the Perlmutter system at NERSC, which opens the possibility to influence decisions between DIII-D pulses during an experiment. The reconstruction results can be used as inputs for other modeling analyses;the determination of the classification of the microturbulence modes is given as an example model analysis. © 2024 IEEE.

关键词： equilibrium reconstruction fusion high performance computing integrated modeling

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A ShuffleNet Architecture-Based Multi-Layer Feature Scaling and Fusion Approach for Underwater Net Cage Damage Detection in Aquaculture

A ShuffleNet Architecture-Based Multi-Layer Feature Scaling ...

引用

2024 IEEE International conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Huang, Xiang-Rui Chen, Yi-Cheng Chen, Liang-Bi Hu, Wu-Chih National Penghu University of Science and Technology Master Program in Electrical Engineering and Computer Science Department of Electrical Engineering Penghu Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

ISBN: (纸本)9798331530839

In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consuming and complex. To overcome this problem, this paper proposes a computer vision solution for identifying damage in underwater net cages to address the inefficiencies and challenges of traditional manual inspections. The proposed scheme utilizes a high-performance multi-branch computational architecture designed based on ShuffleNet architecture to detect net cage damage more efficiently. Experimental results demonstrate that this work performs well on the ImageNet ILSVRC-2010 dataset and achieves an accuracy of 88.54% in underwater net damage detection. © 2024 IEEE.

关键词： Aquaculture

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Area and Speed-Efficient Floating-Point Arithmetic Logical Unit Implementation on FPGA 13

Area and Speed-Efficient Floating-Point Arithmetic Logical U...

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13th IEEE International conference on Communication Systems and Network Technologies, CSNT 2024

作者： Kourav, Sateesh Thakur, Devendra Singh Shah, Sunil Kumar Verma, Kirti Department of Electronics and Communication Engineering MP Jabalpur India Gyan Ganga Institute of Technology and Sciences Department of Electronics and Communication Engineering Jabalpur India Gyan Ganga Institute of Technology and Sciences Department of Engineering Mathematics MP Jabalpur India

ISBN: (纸本)9798350305463

The Arithmetic and Logic Unit is a CPU component that performs arithmetic and logical operations on data. The execution of the multiple instructions in a computer program is required. ALUs frequently feature, among other things, adders, multipliers, and logical units. These components work together to conduct a range of calculations. Ideas and approaches for building the computing units of the ALU are offered. The design also includes a suggested splitter mechanism. The whole ALU is written in Verilog, stressing the usage of a high-level hardware description language in the paper. FALU is widely employed as a key component of DSPs for real-time signal and data processing. The research suggests creating an area- and speed-optimized FALU to increase the performance of DSPs in present computing contexts. The processing power and performance of processors utilized in real-time signal processing applications. The paper's goal is to improve both the speed and the area efficiency of real-time signal processing applications. The Arithmetic and Logic Unit is an important component that performs arithmetic and logical operations on data. The whole ALU is implemented using Verilog, a high-level hardware description language. FALU is designed for speed and space efficiency. © 2024 IEEE.

关键词： computer hardware description languages

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PyCIM: A Python Framework for the Dynamics of Coherent Ising Machine 20th

PyCIM: A Python Framework for the Dynamics of Coherent Ising...

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20th International conference on Intelligent Computing (ICIC)

作者： Li, Peixiang Cheng, Hao Liu, Yingwen Wang, Dongyang Wu, Junjie Natl Univ Def Technol Coll Comp Sci & Technol Inst Quantum Informat Changsha 410073 Peoples R China Natl Univ Def Technol Coll Comp Sci & Technol State Key Lab High Performance Comp Changsha 410073 Peoples R China

ISBN: (纸本)9789819756087;9789819756094

Coherent Ising Machine (CIM) as an optical device for solving combinatorial optimization problems has received significant attention. However, the core unit of CIM, degenerate optical parametric oscillator (DOPO), is an open dissipative system and exhibits complicated dynamics, making the analysis and design of CIM challenging. Based on existing theoretical models for describing CIM, we develop PyCIM. To the best of our knowledge, PyCIM is the first simulator that can produce the dynamic behavior of CIM. We effectively capture some characteristic phenomena of DOPO and CIM, including a spontaneous symmetry breaking, threshold behavior, gain saturation, and the process of CIM solving MAX-CUT problems. Additionally, we implement time-varying coupling strengths and pump schedules. Moreover, we analyze the impact of parameters on the performance of CIM, which can be used to guide the design and optimization of actual physical systems. Finally, we evaluate the performance of the CIM on a standard graph benchmark set.

关键词： Coherent Ising Machine Degenerate Optical Parametric Oscillator Simulator

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How to Steal CPU Idle Time When Synchronous I/O Mode Becomes Promising 24

How to Steal CPU Idle Time When Synchronous I/O Mode Becomes...

引用

61st ACM/IEEE Design Automation conference, DAC 2024

作者： Wu, Chun-Feng Chang, Yuan-Hao Yang, Ming-Chang Kuo, Tei-Wei Department of Computer Science National Yang Ming Chiao Tung University Taiwan Institue of Information Science Academia Sinica Taiwan Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Department of Computer Science and Information Engineering National Taiwan University Taiwan High Performance and Scientific Computing Center National Taiwan University Taiwan Delta Electronics Taiwan

ISBN: (纸本)9798400706011

The advent of Ultra-Low-Latency storage devices has narrowed the performance gap between storage and CPU in computing platforms, facilitating synchronous I/O adoption. Yet, this approach introduces substantial busy waiting time and underutilizes computing units. To address this, we propose a light-weighted Idle-Time-Stealing (ITS) design. This involves a self-improving thread conducting prefetching for high-priority processes during synchronous I/O, and an I/O-waiting process continuing subsequent instruction executions when justifiable. Another thread, the self-sacrificing thread, proactively switches low-priority process I/O requests from synchronous to asynchronous mode, prioritizing high-priority executions. Experimental results demonstrate the effectiveness of our ITS design in reducing CPU idle time. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Data storage equipment

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Exposing LLM Vulnerabilities: Adversarial Scam Detection and performance

Exposing LLM Vulnerabilities: Adversarial Scam Detection and...

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2024 IEEE International conference on Big Data, BigData 2024

作者： Chang, Chen-Wei Sarkar, Shailik Mitra, Shutonu Zhang, Qi Salemi, Hossein Purohit, Hemant Zhang, Fengxiu Hong, Michin Cho, Jin-Hee Lu, Chang-Tien Virginia Tech Department of Computer Science United States Department of Information Sciences and Technology United States George Mason University School of Policy and Government United States Indiana University School of Social Work United States

ISBN: (纸本)9798350362480

Can we trust Large Language Models (LLMs) to accurately predict scam? This paper investigates the vulnerabilities of LLMs when facing adversarial scam messages for the task of scam detection. We addressed this issue by creating a comprehensive dataset with fine-grained labels of scam messages, including both original and adversarial scam messages. The dataset extended traditional binary classes for the scam detection task into more nuanced scam types. Our analysis showed how adversarial examples took advantage of vulnerabilities of a LLM, leading to high misclassification rate. We evaluated the performance of LLMs on these adversarial scam messages and proposed strategies to improve their robustness. © 2024 IEEE.

关键词： Adversarial machine learning

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Automated classification of renal tumors on ultrasound images using deep neural network 9

Automated classification of renal tumors on ultrasound image...

引用

9th International conference on Intelligent Informatics and BioMedical Sciences, ICIIBMS 2024

作者： Wu, Wei-Chieh Chiang, Te-Mei Tsai, Zhi-Ren Asia University Program in Artificial Intelligence College of Information and Electrical Engineering Taichung City Taiwan Asia University Hospital Department of Radiation Oncology Taichung City Taiwan Asia University Department of Computer Science & Information Engineering Taiwan

ISBN: (纸本)9798350363043

Kidney cancer is one of the most common cancers worldwide. The major types of malignant renal tumors are renal cell carcinoma and urothelial carcinoma. Although the majority of renal tumors are malignant, up to 20% are benign, most commonly renal cyst and angiomyolipomas. Ultrasound is the most accessible imaging tool in medical practice, but it highly depends on operator skill, which may lead to high false-negative rate in diagnosis. The purpose of this study was to develop a predictive model for the automated classification of renal tumors on ultrasound images using deep neural network. A total of 880 kidney ultrasound images were used for training and testing. Transfer learning was used to the ten Convolution neural network models. The kidney ultrasound images were classified as benign or malignant tumors. The classification performance of the model was evaluated by sensitivity and specificity. The research results show that VGG18 yielded the best performance, with a sensitivity of 79%, and a specificity of 86%. © 2024 IEEE.

关键词： Ultrasonic imaging

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Architecture-Aware Optimization Strategies for Instruction Selection in DSP Compilers 18th

Architecture-Aware Optimization Strategies for Instruction S...

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18th EAI International conference on Communications and Networking in China, ChinaCom 2023

作者： Wang, Yiwei Wu, Jun Ren, Haoqi Zhang, Zhifeng Tan, Bin School of Computer Science and Technology Tongji University Shanghai China School of Computer Science Fudan University Shanghai China School of Electronics and Information Engineering Tongji University Shanghai China The College of Electronics and Information Engineering Jinggangshan University Ji’an343009 China

ISBN: (纸本)9783031671616

This paper explores the problem of instruction selection optimization in LLVM backend code for transforming platform-independent intermediate code into high-quality target platform instructions. The instruction selection process is divided into two problems: pattern matching and pattern selection. We propose a novel architecture-aware optimization strategy that leverages the features of digital signal processors (DSPs) to improve the efficiency and performance of instruction selection. Our approach involves analyzing the characteristics of DSP architectures to guide the selection of optimal instructions. We evaluate our approach on a set of benchmarks and demonstrate significant improvements in both execution time and code size compared to existing LLVM optimization techniques. Our results show that architecture-aware optimization strategies can effectively enhance instruction selection in DSP compilers, leading to better performance and reduced energy consumption in real-world applications. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： program compilers

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Hidden Markov Model Approach to Predict performance Improvement of 4G Cellular Network 11

Hidden Markov Model Approach to Predict Performance Improvem...

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11th International conference on Electrical Engineering, computer Science and Informatics, EECSI 2024

作者： Kosasih, Eka Oktavia, Tanty BINUS Graduate Program Information System Management Department Bina Nusantara University 11480 Indonesia

ISBN: (纸本)9798350355314

The automation of performance optimization in 4G cellular networks remains a significant research challenge. Although advances in artificial intelligence, machine learning, and deep learning have been made, their application in cellular networks is still in its early stages. The evolution of automated learning algorithms in these networks requires continuous optimization to improve performance. This research aims to develop a data analysis model using a Machine Learning approach to predict 4G network Key performance Indicators (KPIs) and enable automated assessments. The study employs Hidden Markov Models (HMM) to predict KPIs such as eRAB Drop Rate and Setup Success Rate. Data were collected from 1,600 newly deployed sites of a mobile operator in Indonesia over six months, from July 2023 to January 2024. The findings indicate that HMM models can significantly contribute to understanding and enhancing cellular network performance. For instance, the model achieved an accuracy of 99.52% and an F1 score of 99.76% in predicting the eRAB Drop Rate. The Inter-Frequency Handover Success Rate showed 96.15% accuracy and a 97.99%F1 score, while the RRC Connection Setup Success Rate achieved 91.35% accuracy and a 95.29% F1 score. These metrics highlight the model's effectiveness in predicting KPIs. By utilizing HMM models for high-accuracy KPI analysis, network operators can gain deeper insights into network performance and implement targeted improvements. This approach presents a promising avenue for automating and enhancing performance in 4G networks. © 2024 IEEE.

关键词： Hidden Markov models

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