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检索条件"任意字段=IEEE/ACM International Conference on Computer Aide Digest"
890 条 记 录,以下是11-20 订阅
排序:
Invited Paper: Enhancing Privacy-Preserving Computing with Optimized CKKS Encryption: A Hardware Acceleration Approach  24
Invited Paper: Enhancing Privacy-Preserving Computing with O...
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43rd international conference on computer-aided Design, ICCAD 2024
作者: Bao, Tianyou He, Pengzhou Xie, Jiafeng Department of Electrical and Computer Engineering Villanova University VillanovaPA19085 United States
The widespread adoption of the FHE (Fully Homomorphic Encryption) CKKS (Cheon-Kim-Kim-Song) encryption algorithm is stunted by its slow software implementation, driving the need for efficient hardware acceleration sol... 详细信息
来源: 评论
Co-Designing NVM-based Systems for Machine Learning and In-memory Search Applications  24
Co-Designing NVM-based Systems for Machine Learning and In-m...
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43rd international conference on computer-aided Design, ICCAD 2024
作者: Henkel, Jörg Siddhu, Lokesh Nassar, Hassan Bauer, Lars Chen, Jian-Jia Hakert, Christian Seidl, Tristan Chen, Kuan Hsun Hu, Xiaobo Sharon Li, Mengyuan Yang, Chia-Lin Wei, Ming-Liang Karlsruhe Institute of Technology Germany TU Dortmund Germany University of Twente Netherlands University of Notre Dame IN United States National Taiwan University Taiwan
With the rapid development of the Internet of Things, machine learning applications on edge devices with limited resources face challenges due to large data scales and irregular memory access patterns. Non-volatile me... 详细信息
来源: 评论
ConSmax: Hardware-Friendly Alternative Softmax with Learnable Parameters  24
ConSmax: Hardware-Friendly Alternative Softmax with Learnabl...
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43rd international conference on computer-aided Design, ICCAD 2024
作者: Liu, Shiwei Tao, Guanchen Zou, Yifei Chow, Derek Fan, Zichen Lei, Kauna Pan, Bangfei Sylvester, Dennis Kielian, Gregory Saligane, Mehdi Google Research United States Department of Electrical Engineering and Computer Sciences University of Michigan United States
The self-attention mechanism distinguishes transformer-based large language models (LLMs) apart from convolutional and recurrent neural networks. Despite the performance improvement, achieving real-time LLM inference ... 详细信息
来源: 评论
FSMM: An Efficient Matrix Multiplication Accelerator Supporting Flexible Sparsity  24
FSMM: An Efficient Matrix Multiplication Accelerator Support...
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43rd international conference on computer-aided Design, ICCAD 2024
作者: Qiao, Yuxuan Yang, Fan Zhang, Yecheng Xiong, Xiankui Yao, Xiao Yao, Haidong State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai China School of Microelectronics Fudan University Shanghai China State Key Laboratory of Mobile Network and Mobile Multimedia Technology ZTE Corporation Shenzhen China
Sparse matrix multiplication is a critical operation in deep learning. However, matrix sparsity leads to irregular data flow, which would degrade the efficiency of matrix multiplication. Traditional accelerators, equi... 详细信息
来源: 评论
BPINN-EM: Fast Stochastic Analysis of Electromigration Damage using Bayesian Physics-Informed Neural Networks  24
BPINN-EM: Fast Stochastic Analysis of Electromigration Damag...
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43rd international conference on computer-aided Design, ICCAD 2024
作者: Lamichhane, Subed Kavousi, Mohamadamir Tan, Sheldon X.-D. Department of Electrical and Computer Engineering University of California RiversideCA92521 United States
Electromigration (EM) induced aging and degradation in interconnect wires is inherently a stochastic process, with lifetime typically measured in terms of mean time to failure at both wire and circuit levels. However,... 详细信息
来源: 评论
ALISA: An Adaptive Learned Index Structure for Spatial Data on Solid-State Drives  24
ALISA: An Adaptive Learned Index Structure for Spatial Data ...
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43rd international conference on computer-aided Design, ICCAD 2024
作者: Lin, Che-Wei Wu, Chun-Feng Department of Computer Science National Yang Ming Chiao Tung University Taiwan
Spatial learned index is becoming popular as a solution to relieve the intense storage demands and high I/O costs of spatial databases. LISA, the original and most prominent spatial learned index structure, is tailore... 详细信息
来源: 评论
Hardware-Aware Quantization for Accurate Memristor-Based Neural Networks  24
Hardware-Aware Quantization for Accurate Memristor-Based Neu...
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43rd international conference on computer-aided Design, ICCAD 2024
作者: Diware, Sumit Yaldagard, Mohammad Amin Bishnoi, Rajendra Computer Engineering Lab Delft University of Technology Delft Netherlands
Memristor-based Computation-In-Memory (CIM) has emerged as a compelling paradigm for designing energy-efficient neural network hardware. However, memristors suffer from conductance variation issue, which introduces co... 详细信息
来源: 评论
Joint Placement Optimization for Hierarchical Analog/Mixed-Signal Circuits  24
Joint Placement Optimization for Hierarchical Analog/Mixed-S...
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43rd international conference on computer-aided Design, ICCAD 2024
作者: Gao, Xiaohan Zhang, Haoyi Liu, Bingyang Lin, Yibo Wang, Runsheng Huang, Ru School of Computer Science Peking University China School of Integrated Circuits Peking University China Institute of EDA Peking University China School of EECS Peking University China Beijing Advanced Innovation Center for Integrated Circuits China
The performance of Analog/Mixed Signal (AMS) circuits is highly dependent on the meticulous layout implementation. To meet performance and area requirements, real-world AMS layout design is thoroughly optimized to con... 详细信息
来源: 评论
Spiking Transformer Hardware Accelerators in 3D Integration  24
Spiking Transformer Hardware Accelerators in 3D Integration
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43rd international conference on computer-aided Design, ICCAD 2024
作者: Xu, Boxun Hwang, Junyoung Vanna-Iampikul, Pruek Lim, Sung Kyu Li, Peng Department of Electrical and Computer Engineering University of California Santa BarbaraCA United States Department of Electrical and Computer Engineering Georgia Institute of Technology GA United States Department of Electrical Engineering Burapha University Chonburi Thailand
Spiking neural networks (SNNs) are powerful models of spatiotemporal computation and are well suited for deployment on resource-constrained edge devices and neuromorphic hardware due to their low power consumption. Le... 详细信息
来源: 评论
Invited Paper: Learned In-Sensor Visual Computing: From Compression to Eventification  42
Invited Paper: Learned In-Sensor Visual Computing: From Comp...
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42nd ieee/acm international conference on computer-aided Design, ICCAD 2023
作者: Feng, Yu Ma, Tianrui Boloor, Adith Zhu, Yuhao Zhang, Xuan University of Rochester Department of Computer Science United States Washington University Department of Electrical and Systems Engineering St. Louis United States
Visual computing is vital for numerous applications. In conventional visual computing systems, CMOS image sensors (CIS) act as pure imaging devices for capturing images, however, recent CIS designs increasingly integr... 详细信息
来源: 评论