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Cryo-CACTI: Cryogenic-Aware CACTI for Cache Modeling down to 10K in Advanced 7nm FinFETs

IEEE Transactions on computers 2025年

作者： Ravipati, Divya Praneetha van Santen, Victor M. Parihar, Shivendra Singh Chauhan, Yogesh Singh Panda, Preeti Ranjan Amrouch, Hussam Indian Institute of Technology Delhi Department of Computer Science and Engineering New Delhi India Technical University of Munich TUM School of Computation Information and Technology Chair of AI Processor Design Munich Institute of Robotics and Machine Intelligence Germany Kanpur Nanolab Department of Electrical Engineering Uttar Pradesh India

Cryogenic circuits are currently employed in fields such as quantum computing, particle detectors, magnetic resonance imaging, and space applications. While cryogenic circuits are being researched, there is limited work on designing cryogenic caches at temperatures below 77K. Moreover, there is no tool to estimate the delay, power, and area of cryogenic caches at advanced technology nodes. Our research focuses on the development of cryogenic caches tailored for the 7nm technology node, operating at 10K. However, a key challenge is the lack of cryogenic measurement data, especially in recent technologies. Consequently, through conducting our own FinFET transistor measurements, we calibrate cryogenic transistor models at 10K. With the 7nm cryogenic transistor data, we model Cryo-CACTI for cryogenic caches (due to cache’s vital role in improving performance and their considerable share in area and power of the processor). Using Cryo-CACTI, our evaluation reveals considerable improvements in the energy efficiency (up to 99%) of cryogenic caches of larger sizes compared to the caches at room temperature (300K). Additionally, we explore alternative cache configurations at circuit-level to optimize cryogenic operation. Furthermore, we use Cryo-CACTI to explore the performance/energy consumption of cryogenic caches while simulating workloads such as SPEC CPU2017 and machine learning via neural networks. © 1968-2012 IEEE.

关键词： Combinatorial circuits

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Verification of embedded binaries using coverage-guided fuzzing with system C-based virtual prototypes 20

Verification of embedded binaries using coverage-guided fuzz...

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30th Great Lakes Symposium on VLSI, GLSVLSI 2020

作者： Herdt, Vladimir Große, Daniel Wloka, Jonas Güneysu, Tim Drechsler, Rolf Cyber-Physical Systems DFKI GmbH Bremen Germany Chair of Complex Systems Johannes Kepler University Linz Austria Cyber-Physical Systems DFKI GmbH Bremen Germany Chair for Security Engineering Ruhr-University Bochum Cyber-Physical Systems DFKI GmbH Bremen Germany Institute of Computer Science University of Bremen Cyber-Physical Systems DFKI GmbH Bremen Germany

ISBN: (纸本)9781450379441

Extensive verification of embedded SW is very important to avoid errors and security vulnerabilities. Therefore, mainly simulation-based methods are employed that leverage Virtual Prototypes (VPs) for SW execution early in the design flow. VPs are essentially abstract models of the entire HW platform including peripherals. They are predominantly created in SystemC. However, a comprehensive simulation-based verification requires integration of sophisticated test generation techniques. In this paper we propose to leverage state-of-the-art Coverage-guided Fuzzing (CGF) methods in combination with SystemC-based VPs for verification of embedded SW binaries. Using VPs, our approach allows a fast and accurate binary-level SW analysis and enables checking of complex HW/SW interactions. To guide the fuzzing process we combine the coverage from the embedded SW with the coverage of the SystemC-based peripherals. Our experiments, using RISC-V embedded SW binaries as examples, demonstrate the effectiveness of our approach. © 2020 Association for Computing Machinery.

关键词： Virtual prototyping

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Bayesian uncertainty analysis for underwater 3D reconstruction with neural radiance fields

arXiv

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arXiv 2024年

作者： Lian, Haojie Li, Xinhao Qu, Yilin Du, Jing Meng, Zhuxuan Liu, Jie Chen, Leilei Key Laboratory of In-situ Property-improving Mining of Ministry of Education Taiyuan University of Technology Taiyuan100190 China Henan International Joint Laboratory of Structural Mechanics and Computational Simulation College of Architecture and Civil Engineering Huanghuai University Zhumadian463000 China School of Marine Science and Technology Northwestern Polytechnical University Xi’an710072 China Unmanned Vehicle Innovation Center Ningbo Institute of Northwestern Polytechnical University Ningbo315103 China Key Laboratory of Unmanned Underwater Vehicle Technology of Ministry of Industry and Information Technology Northwestern Polytechnical University Xi’an710072 China Center for Strategic Assessment and Consulting Academy of Military Science Beijing100091 China Computer Engineering Department Taiyuan Institute of Technology Taiyuan030008 China

Neural radiance fields (NeRFs) are a deep learning technique that can generate novel views of 3D scenes using sparse 2D images from different viewing directions and camera poses. As an extension of conventional NeRFs in underwater environment, where light can get absorbed and scattered by water, SeaThru-NeRF was proposed to separate the clean appearance and geometric structure of underwater scene from the effects of the scattering medium. Since the quality of the appearance and structure of underwater scenes is crucial for downstream tasks such as underwater infrastructure inspection, the reliability of the 3D reconstruction model should be considered and evaluated. Nonetheless, owing to the lack of ability to quantify uncertainty in 3D reconstruction of underwater scenes under natural ambient illumination, the practical deployment of NeRFs in unmanned autonomous underwater navigation is limited. To address this issue, we introduce a spatial perturbation field Dω based on Bayes’ rays in SeaThru-NeRF and perform Laplace approximation to obtain a Gaussian distribution N(0, Σ) of the parameters ω, where the diagonal elements of Σ correspond to the uncertainty at each spatial location. We also employ a simple thresholding method to remove artifacts from the rendered results of underwater scenes. Numerical experiments are provided to demonstrate the effectiveness of this approach. Copyright © 2024, The Authors. All rights reserved.

关键词： Uncertainty analysis

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Intelligent Techniques for Prediction of Drilling Rate for Percussive Drills in Topically Weathered Limestone

Intelligent Techniques for Prediction of Drilling Rate for P...

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International Conference on Geotechnical challenges in Mining, Tunneling and Underground structures, ICGMTU 2021

作者： Bhatawdekar, Ramesh Murlidhar Roy, Bishwajit Changtham, Saksarid Khandelwal, Manoj Armaghani, Danial Jahed Mohamad, Edy Tonnizam Pathak, Pranjal Mondal, Subhrojit Kumar, Radhikesh Md Dan, M.F. Department of Mining Engineering Indian Institute of Technology Kharagpur721302 India Faculty of Civil Engineering University Technology Malaysia Johor UTM Skudai81310 Malaysia Department of Computer and Science Engineering Bennett University Uttar Pradesh Greater Noida201310 India Siam City Concrete Company Limited Bang Sue Bangkok10800 Thailand School of Engineering Information Technology and Physical Sciences Federation University Ballarat Australia Department of Urban Planning Engineering Networks and Systems Institute of Architecture and Construction South Ural State University 76 Lenin Prospect Chelyabinsk454080 Russia NIT Patna800005 India Faculty of Civil and Built Environment University Tun Hussein Onn Malaysia Johor Batu Pahat86400 Malaysia

ISBN: (纸本)9789811697692

Physico-mechanical properties of rocks have a direct correlation with the drilling rate of percussive drill. The prediction of drilling rate is important for the deployment of drills during the planning stage. In tropical climatic regions, limestone is classified as blocky, very blocky, blocky/ seamy and disintegrated based on the degree of weathering. Weathering of limestone takes place very rapidly in tropical (wet) climatic regions. Previous researchers have correlated different individual rock mass properties with rate of drilling. However, single property of limestone is not adequate to correlate with the drilling rate. In this study, sensitivity analysis of different properties of weathered limestone was carried out with respect to drilling rate. Rock density, rock quality designation (RQD), geological strength index (GSI), point load index (PLI) and Schmidt hammer rebound number (SHRN) were identified as crucial input parameters. 113 data sets were collected with the foregoing five input parameters and the output parameter as drilling rate of percussive drills. Data was analysed with multi variable regression analysis (MVRA) which showed R2 value as 0.54. Artificial neural network (ANN) has been widely used for solving various engineering problems. On the other hand, optimization problems are solved by the Biogeography Based Optimization (BBO) model. Further this data was analysed with a hybrid intelligent model namely BBO- ANN. The R2 values for training data set and testing data set 0.638 and 0.761 respectively. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Limestone

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Modular Inverse for Integers using Fast Constant Time GCD Algorithm and its Applications

Modular Inverse for Integers using Fast Constant Time GCD Al...

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International Conference on Field Programmable Logic and Applications

作者： Sanjay Deshpande Santos Merino del Pozo Victor Mateu Marc Manzano Najwa Aaraj Jakub Szefer Computer Architecture and Security Laboratory Yale University New Haven CT USA Cryptography Research Centre Technology Innovation Institute Abu Dhabi UAE Digital Security Group Faculty of Science Radboud University Nijmegen Netherlands Faculty of Engineering Mondragon Unibertsitatea Mondragon Spain Okinawa Institute of Science and Technology Okinawa Japan

Modular inversion, the multiplicative inverse of an integer in the ring of integers modulo a prime number, is widely used in public-key cryptography. However, it is one of the most computationally intensive operations, thus, it remains the main performance bottleneck for many cryptographic *** paper presents to the best of the author’s knowledge, the first FPGA-based hardware design for computing the multiplicative inverse using the recently proposed fast constant-time Greatest Common Divisor (GCD) algorithm. This paper introduces two distinct design architectures targeting different applications: (a) a full-width design and (b) a sequential design. The presented designs are compact, parameterizable, and scalable in terms of area and speed. The evaluation shows the proposed designs, which are constant-time and protect against timing-based attacks, outperform existing software and hardware implementations that use other modular inversion techniques. As a specific example, this work presents an evaluation focusing on the use of the multiplicative inverse hardware module to accelerate the ElGamal cryptosystem. The proposed design achieves a speed-up of 90% in the modular inverse calculation and a speed-up of 45% in the overall ElGamal decryption algorithm using our sequential hardware design of fast constant-time GCD *** addition to developing the fast hardware implementation, this work potentially opens up a new direction for designing cryptosystems: the inverse operation is often avoided when designing algorithms, due to its complexity. With the new hardware module, using the inverse becomes more tractable, making it more appealing to use in the design of new cryptosystems.

关键词： Software algorithms Focusing computer architecture Public key cryptography Hardware Software Complexity theory

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Non-convex potential games for finding global solutions to sensor network localization

arXiv

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arXiv 2023年

作者： Xu, Gehui Chen, Guanpu Hong, Yiguang Fidan, Baris Parisini, Thomas Johansson, Karl H. Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden Department of Control Science and Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom Department of Engineering and Architecture University of Trieste Trieste34127 Italy

Sensor network localization (SNL) problems require determining the physical coordinates of all sensors in a network. This process relies on the global coordinates of anchors and the available measurements between non-anchor and anchor nodes. Attributed to the intrinsic non-convexity, obtaining a globally optimal solution to SNL is challenging, as well as implementing corresponding algorithms. In this paper, we formulate a non-convex multi-player potential game for a generic SNL problem to investigate the identification condition of the global Nash equilibrium (NE) therein, where the global NE represents the global solution of SNL. We employ canonical duality theory to transform the non-convex game into a complementary dual problem. Then we develop a conjugation-based algorithm to compute the stationary points of the complementary dual problem. On this basis, we show an identification condition of the global NE: the stationary point of the proposed algorithm satisfies a duality relation. Finally, simulation results are provided to validate the effectiveness of the theoretical results. Copyright © 2023, The Authors. All rights reserved.

关键词： Sensor networks

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Exploring Spatial Hybrid User Interface for Visual Sensemaking

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IEEE Transactions on Visualization and computer Graphics 2025年 PP卷 PP页

作者： Tong, Wai Li, Haobo Xia, Meng Kam-Kwai, Wong Pong, Ting-Chuen Qu, Huamin Yang, Yalong Nanchang University School of Mathematics and Computer Sciences Nanchang 330031 China Shenzhen University School of Architecture & Urban Planning Shenzhen 518060 China University of Calgary Department of Geomatics Engineering Calgary T2N 1N4 Canada Wuhan University School of Geodesy and Geomatics Wuhan 430079 China Wuhan University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan 430079 China Finnish Geospatial Research Institute Department of Remote Sensing and Photogrammetry Masala 02430 Finland Wuhan University of Technology School of Safety Science and Emergency Management Wuhan 430079 China Nanjing University of Information Science & Technology School of Remote Sensing & Geomatics Engineering Nanjing 210000 China Nanjing Forestry University College of Civil Engineering Nanjing 210037 China Guangzhou Urban Planning & Design Survey Research Institute Guangzhou 51100 China

We built a spatial hybrid system that combines a personal computer (PC) and virtual reality (VR) for visual sensemaking, addressing limitations in both environments. Although VR offers immense potential for interactive data visualization (e.g., large display space and spatial navigation), it can also present challenges such as imprecise interactions and user fatigue. At the same time, a PC offers precise and familiar interactions but has limited display space and interaction modality. Therefore, we iteratively designed a spatial hybrid system (PC+VR) to complement these two environments by enabling seamless switching between PC and VR environments. To evaluate the system's effectiveness and user experience, we compared it to using a single computing environment (i.e., PC-only and VR-only). Our study results (N=18) showed that spatial PC+VR could combine the benefits of both devices to outperform user preference for VR-only without a negative impact on performance from device switching overhead. Finally, we discussed future design implications. © 1995-2012 IEEE.

关键词： Data visualization

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Cloud-Magnetic Resonance Imaging System: In the Era of 6G and Artificial Intelligence

arXiv

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arXiv 2023年

作者： Zhou, Yirong Wu, Yanhuang Su, Yuhan Li, Jing Cai, Jianyun You, Yongfu Guo, Di Qu, Xiaobo The Department of Electronic Science Biomedical Intelligent Cloud R&D Center Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance National Institute for Data Science in Health and Medicine Institute of Artificial Intelligence Xiamen University Xiamen361104 China The Department of Electronic Science Key Laboratory of Digital Fujian on IoT Communication Architecture and Safety Technology Xiamen University Xiamen361104 China Shanghai Electric Group CO. LTD Shanghai200001 China China Telecom Group Quanzhou362000 China China Mobile Group Xiamen361005 China School of Computer and Information Engineering Fujian Engineering Research Center for Medical Data Mining and Application Xiamen University of Technology Xiamen361024 China

Magnetic Resonance Imaging (MRI) plays an important role in medical diagnosis, generating petabytes of image data annually in large hospitals. This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure. Additionally, local data processing demands substantial manpower and hardware investments. Data isolation across different healthcare institutions hinders cross-institutional collaboration in clinics and research. In this work, we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing, 6G bandwidth, edge computing, federated learning, and blockchain technology. This system is called Cloud-MRI, aiming at solving the problems of MRI data storage security, transmission speed, AI algorithm maintenance, hardware upgrading, and collaborative work. The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data (ISMRMRD) format. Then, the data are uploaded to the cloud or edge nodes for fast image reconstruction, neural network training, and automatic analysis. Then, the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services. The Cloud-MRI system will save the raw imaging data, reduce the risk of data loss, facilitate inter-institutional medical collaboration, and finally improve diagnostic accuracy and work efficiency. Copyright © 2023, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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An interpretable spatially weighted machine learning approach for revealing spatial nonstationarity impacts of the built environment on air pollution

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Building and Environment 2025年 280卷

作者： Wang, Shumin Hu, Mingxing Li, Jianyu Liu, Guoao Hu, Wanqi Qi, Junheng Huang, Jingyue Liu, Ziye Wang, Hui Han, Bing School of Architecture Southeast University Si Pailou Campus Nanjing210096 China School of Computer and Information Science University of Pennsylvania PhiladelphiaPA 19104 United States College of Landscape Architecture Nanjing Forestry University 159 Longpan Road Nanjing210037 China College of Horticulture Jinling Institute of Technology Nanjing210038 China

With urbanization acceleration, air pollution has become increasingly severe, and the built environment plays a crucial role in pollutant dispersion and accumulation. In this study, the central urban area of Nanjing is analysed in a case study, focusing on the plot scale to systematically explore spatial heterogeneity and nonlinear interactive mechanisms of built environment impacts. To accurately capture the complex spatial nonstationarity effects of the built environment on air pollution, a geographically weighted machine learning (GeoML) approach driven by an adjacency-based spatial mechanism integrated with the SHapley Additive exPlanations (SHAP) framework for interpretability is established. The findings reveal that the GeoML model outperforms other models (the ordinary least squares (OLS), random forest (RF), geographically weighted regression (GWR), and geographically weighted random forest (GWRF) models), with an R² value of 0.74, effectively capturing spatial heterogeneity and nonlinearity. Further analysis reveals significant variations in the impact of spatial weighting on the contributions of different feature variables: the explanatory power of most variables increases with the inclusion of spatial effects, whereas the contributions of variables such as population density, road network density, and parcel compactness are reduced. The SHAP framework is employed to provide interpretable analysis of the patterns in the impacts of various feature variables on air pollution. This study emphasizes the importance of spatial effects at the microscale plot level in understanding the mechanisms of air pollution and highlights their importance for developing urban environmental policies, thus promoting the transformation of air pollution control towards spatially refined management. © 2025

关键词： Air quality

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Extremum Seeking Control for Beam Steering using Hypersurfaces

Extremum Seeking Control for Beam Steering using Hypersurfac...

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IEEE International Conference on Communications Workshops, ICC

作者： Nouman Ashraf Marios Lestas Taqwa Saeed Hamidreza Taghvaee Sergi Abadal Andreas Pitsillides Christos Liaskos Dep. of Electrical Engineering Frederick University Dep. of Computer Science University of Cyprus Nicosia Cyprus Dep. of Computer Architecture Universitat Politècnica de Catalunya Barcelona Spain Institute of Computer Science Foundation of Research and Technology Hellas Heraklion Greece

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

Hypersurface, a software defined metasurface (SDM) paradigm constitutes a revolutionary technology aiming at offering programmatic control over all aspects of a propagating wave, altering its direction, power, polarization and phase. In the absence of line of sight (LOS) between a transmitter and a receiver, HSF can provide seamless connectivity via programmatic reflection. However, such an application requires fine tuning of the metasurface reconfiguration parameters, which may not be effective when done in an open loop fashion due to model uncertainties. In this work, we consider a feedback-based formulation of the problem, which involves maximization of the received power and propose the use of Extremum Seeking Control (ESC) for the controller implementation due to fact that it is model-free and adheres to the maximization problem. Extensive simulations indicate that the proposed scheme is successful in guiding the impinging wave to the receiver within reasonable time even in the presence of time varying delays incurred by message propagation. In addition, a discrete time implementation is considered, investigating its limitations as we increase the sampling time while also characterizing the traffic within the controller network.

关键词： Receivers Beam steering Transmitters Aerospace electronics computer science Software Delays

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