Search Results - HARDWARE ACCELERATION

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  1. 1

    Hardware for Deep Learning Acceleration by Choongseok Song, ChangMin Ye, Yonguk Sim, Doo Seok Jeong

    Published in Advanced Intelligent Systems (2024-10-01)
    “…To cope with the consequent prohibitive latency for computation, 1) general‐purpose hardware, e.g., central processing units and graphics processing units, has been redesigned, and 2) various DL accelerators have been newly introduced, e.g., neural processing units, and computing‐in‐memory units for deep NN‐based DL, and neuromorphic processors for spiking NN‐based DL. …”
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  2. 2

    Hardware-friendly compression and hardware acceleration for transformer: A survey by Shizhen Huang, Enhao Tang, Shun Li, Xiangzhan Ping, Ruiqi Chen

    Published in Electronic Research Archive (2022-08-01)
    Subjects: “…hardware accelerators…”
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  3. 3

    Hardware Accelerated Sequence Alignment with Traceback by Scott Lloyd, Quinn O. Snell

    “…A space-efficient, global sequence alignment algorithm and architecture is presented that accelerates the forward scan and traceback in hardware without memory and I/O limitations. …”
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  4. 4

    Hardware accelerators for processing clusters in binary vectors by Skliarova Iouliia, Skliarov Valeri

    Published in ITM Web of Conferences (2024-01-01)
    “…The paper suggests fast hardware accelerators for discovering clusters of zeros and/or ones in binary vectors. …”
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  5. 5

    On-Chip Reconfigurable Hardware Accelerators for Popcount Computations by Valery Sklyarov, Iouliia Skliarova, João Silva

    “…The paper suggests two types of hardware accelerators that are (1) designed in FPGAs and (2) implemented in Zynq-7000 all programmable systems-on-chip with partitioning of algorithms that use popcounts between software of ARM Cortex-A9 processing system and advanced programmable logic. …”
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  6. 6

    Image Processing Hardware Acceleration—A Review of Operations Involved and Current Hardware Approaches by Costin-Emanuel Vasile, Andrei-Alexandru Ulmămei, Călin Bîră

    Published in Journal of Imaging (2024-11-01)
    Subjects: “…hardware accelerators…”
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  7. 7

    A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware by Eric Müller, Elias Arnold, Oliver Breitwieser, Milena Czierlinski, Arne Emmel, Jakob Kaiser, Christian Mauch, Sebastian Schmitt, Philipp Spilger, Raphael Stock, Yannik Stradmann, Johannes Weis, Andreas Baumbach, Andreas Baumbach, Sebastian Billaudelle, Benjamin Cramer, Falk Ebert, Julian Göltz, Julian Göltz, Joscha Ilmberger, Vitali Karasenko, Mitja Kleider, Aron Leibfried, Christian Pehle, Johannes Schemmel

    Published in Frontiers in Neuroscience (2022-05-01)
    Subjects: “…hardware abstraction…”
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  8. 8

    A Component-Centric Perspective on Hardware Accelerators for LLMs by Jia Ke, Wang Xiaohao, Chen Hailin, Zhong Wei, Li Xinxiong, Fang Zenan, An Fengwei

    Published in IEEE Access (2025-01-01)
    “…The rapid scaling of large language models (LLMs), especially those based on the Transformer architecture, has intensified the demand for high-performance hardware accelerators capable of supporting massive parameter counts with minimal latency and energy consumption. …”
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  9. 9

    Scalable QKD Postprocessing System With Reconfigurable Hardware Accelerator by Natarajan Venkatachalam, Foram P. Shingala, Selvagangai C, Hema Priya S, Dillibabu S, Pooja Chandravanshi, Ravindra P. Singh

    Published in IEEE Transactions on Quantum Engineering (2023-01-01)
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  10. 10

    Approximate CNN Hardware Accelerators for Resource Constrained Devices by P Thejaswini, Gautham Suresh, V. Chiraag, Sukumar Nandi

    Published in IEEE Access (2025-01-01)
    Subjects: “…hardware accelerators…”
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  11. 11

    Hardware Acceleration of Number Theoretic Transform in zk-SNARK by ZHAO Haixu, CHAI Zhilei, HUA Pengcheng, WANG Feng, DING Dong

    Published in Jisuanji kexue yu tansuo (2024-02-01)
    Subjects: “…field programmable gate array (fpga); zero-knowledge succinct non-interactive arguments of knowledge (zk-snark); modular multiplication; number theoretic transform; hardware acceleration…”
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    Article


  12. 12

    Hardware Acceleration Design for Edge Intelligence of Transmission Lines by ZHANG Shuhua, WANG Jiye, ZHAO Chuanqi, CHEN Hongming, GUO Yongwen

    Published in Jisuanji gongcheng (2025-02-01)
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    Article


  13. 13

    OPTIMSM: FPGA hardware accelerator for Zero-Knowledge MSM by Xander Pottier, Thomas de Ruijter, Jonas Bertels, Wouter Legiest, Michiel Van Beirendonck, Ingrid Verbauwhede

    Subjects: “…Hardware Acceleration…”
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  14. 14

    A Flexible Hardware Accelerator for Booth Polynomial Multiplier by Omar S. Sonbul

    Published in Applied Sciences (2024-04-01)
    “…This article presents a parameterized/flexible hardware accelerator design tailored for the Booth polynomial multiplication method. …”
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  15. 15

    Quick Boot of Trusted Execution Environment With Hardware Accelerators by Trong-Thuc Hoang, Ckristian Duran, Duc-Thinh Nguyen-Hoang, Duc-Hung Le, Akira Tsukamoto, Kuniyasu Suzaki, Cong-Kha Pham

    Published in IEEE Access (2020-01-01)
    “…In this paper, a RISC-V system compatible with TEEs featuring security algorithm accelerators is presented. The hardware accelerators are the SHA-3 hash and the Ed25519 elliptic curve algorithms. …”
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  16. 16

    Investigating hardware acceleration for simulation of CFD quantum circuits by Youssef Moawad, Wim Vanderbauwhede, René Steijl

    Published in Frontiers in Mechanical Engineering (2022-10-01)
    Subjects: “…hardware acceleration…”
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    Article


  17. 17

    Hardware-accelerated interactive data visualization for neuroscience in Python by Cyrille eRossant, Kenneth D Harris

    Published in Frontiers in Neuroinformatics (2013-12-01)
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  18. 18

    On the Hardware–Software Integration in Cryptographic Accelerators for Industrial IoT by Luigi Leonardi, Giuseppe Lettieri, Pericle Perazzo, Sergio Saponara

    Published in Applied Sciences (2022-10-01)
    Subjects: “…hardware acceleration…”
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  19. 19

    A Survey on Hardware Accelerators for Large Language Models by Christoforos Kachris

    Published in Applied Sciences (2025-01-01)
    Subjects: “…hardware accelerators…”
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  20. 20

    Efficient Hardware Architectures for Accelerating Deep Neural Networks: Survey by Pudi Dhilleswararao, Srinivas Boppu, M. Sabarimalai Manikandan, Linga Reddy Cenkeramaddi

    Published in IEEE Access (2022-01-01)
    “…This review article is intended to guide hardware architects to accelerate and improve the effectiveness of deep learning research.…”
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