Search Results - Sakr, Charbel

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  1. 1
    An Analytical Method to Determine Minimum Per-Layer Precision of Deep Neural Networks

    An Analytical Method to Determine Minimum Per-Layer Precision of Deep Neural Networks by Sakr, Charbel, Shanbhag, Naresh

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  2. 2
    Signal Processing Methods to Enhance the Energy Efficiency of In-Memory Computing Architectures

    Signal Processing Methods to Enhance the Energy Efficiency of In-Memory Computing Architectures by Sakr, Charbel, Shanbhag, Naresh R.

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  3. 3
    Seed germination ecology and salt stress response in eight Mediterranean populations of Sarcopoterium spinosum (L.) Spach

    Seed germination ecology and salt stress response in eight Mediterranean populations of Sarcopoterium spinosum (L.) Spach by Santo, Andrea, Dessì, Ludovica, Ucchesu, Mariano, Bou Dagher Kharrat, Magda, Charbel Sakr, Ramy, Accogli, Rita A., Buhagiar, Joseph, Kyratzis, Angelos, Fournaraki, Christini, Bacchetta, Gianluigi

    Published in Plant species biology
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  4. 4
    A 0.44-μJ/dec, 39.9-μs/dec, Recurrent Attention In-Memory Processor for Keyword Spotting

    A 0.44-μJ/dec, 39.9-μs/dec, Recurrent Attention In-Memory Processor for Keyword Spotting by Dbouk, Hassan, Gonugondla, Sujan K., Sakr, Charbel, Shanbhag, Naresh R.

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  5. 5
    Fundamental Limits on Energy-Delay-Accuracy of In-Memory Architectures in Inference Applications

    Fundamental Limits on Energy-Delay-Accuracy of In-Memory Architectures in Inference Applications by Gonugondla, Sujan K., Sakr, Charbel, Dbouk, Hassan, Shanbhag, Naresh R.

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  6. 6
    Fundamental Limits on the Precision of In-memory Architectures

    Fundamental Limits on the Precision of In-memory Architectures by Gonugondla, Sujan K., Sakr, Charbel, Dbouk, Hassan, Shanbhag, Naresh R.

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  7. 7
    A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm

    A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm by Keller, Ben, Venkatesan, Rangharajan, Dai, Steve, Tell, Stephen G., Zimmer, Brian, Sakr, Charbel, Dally, William J., Gray, C. Thomas, Khailany, Brucek

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  8. 8
    Energy‐dispersive Laue diffraction analysis of the influence of statherin and histatin on the crystallographic texture during human dental enamel demineralization

    Energy‐dispersive Laue diffraction analysis of the influence of statherin and histatin on the crystallographic texture during human dental enamel demineralization by Sakr, Charbel, Al-Mosawi, Mohammed, Grünewald, Tilman A., Cook, Philip, Tack, Pieter, Vincze, Laszlo, Micha, Jean-Sebastien, Anderson, Paul, Al-Jawad, Maisoon, Lichtenegger, Helga C.

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  9. 9
    Minimum Precision Requirements of General Margin Hyperplane Classifiers

    Minimum Precision Requirements of General Margin Hyperplane Classifiers by Sakr, Charbel, Kim, Yongjune, Shanbhag, Naresh

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  10. 10
    True Gradient-Based Training of Deep Binary Activated Neural Networks Via Continuous Binarization

    True Gradient-Based Training of Deep Binary Activated Neural Networks Via Continuous Binarization by Sakr, Charbel, Choi, Jungwook, Wang, Zhuo, Gopalakrishnan, Kailash, Shanbhag, Naresh

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  11. 11
    Unique orientation of 1D and 2D nanoparticle assemblies confined in smectic topological defects

    Unique orientation of 1D and 2D nanoparticle assemblies confined in smectic topological defects by Jeridi, Haifa, Niyonzima, Jean de Dieu, Sakr, Charbel, Missaoui, Amine, Shahini, Sharif, Vlad, Alina, Coati, Alessandro, Goubet, Nicolas, Royer, Sébastien, Vickridge, Ian, Goldmann, Michel, Constantin, Doru, Garreau, Yves, Babonneau, David, Croset, Bernard, Gallas, Bruno, Lhuillier, Emmanuel, Lacaze, Emmanuelle

    Published in Soft matter
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  12. 12
    KeyRAM: A 0.34 uJ/decision 18 k decisions/s Recurrent Attention In-memory Processor for Keyword Spotting

    KeyRAM: A 0.34 uJ/decision 18 k decisions/s Recurrent Attention In-memory Processor for Keyword Spotting by Dbouk, Hassan, Gonugondla, Sujan K., Sakr, Charbel, Shanbhag, Naresh R.

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  13. 13
    VaPr: Variable-Precision Tensors to Accelerate Robot Motion Planning

    VaPr: Variable-Precision Tensors to Accelerate Robot Motion Planning by Hsiao, Yu-Shun, Sastry Hari, Siva Kumar, Sundaralingam, Balakumar, Yik, Jason, Tambe, Thierry, Sakr, Charbel, Keckler, Stephen W., Reddi, Vijay Janapa

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  14. 14
    Minimum precision requirements for the SVM-SGD learning algorithm

    Minimum precision requirements for the SVM-SGD learning algorithm by Sakr, Charbel, Patil, Ameya, Sai Zhang, Yongjune Kim, Shanbhag, Naresh

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  15. 15
    Optimizing Selective Protection for CNN Resilience

    Optimizing Selective Protection for CNN Resilience by Mahmoud, Abdulrahman, Sastry Hari, Siva Kumar, Fletcher, Christopher W., Adve, Sarita V., Sakr, Charbel, Shanbhag, Naresh, Molchanov, Pavlo, Sullivan, Michael B., Tsai, Timothy, Keckler, Stephen W.

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  16. 16
    ESPACE: Dimensionality Reduction of Activations for Model Compression

    ESPACE: Dimensionality Reduction of Activations for Model Compression by Sakr, Charbel, Khailany, Brucek

    Published in arXiv.org
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  17. 17
    Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm

    Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm by Sakr, Charbel, Shanbhag, Naresh

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  18. 18
    Fundamental Limits on Energy-Delay-Accuracy of In-memory Architectures in Inference Applications

    Fundamental Limits on Energy-Delay-Accuracy of In-memory Architectures in Inference Applications by Gonugondla, Sujan Kumar, Sakr, Charbel, Dbouk, Hassan, Shanbhag, Naresh R

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  19. 19
    Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training

    Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training by Sakr, Charbel, Dai, Steve, Venkatesan, Rangharajan, Zimmer, Brian, Dally, William J, Khailany, Brucek

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  20. 20
    EoRA: Training-free Compensation for Compressed LLM with Eigenspace Low-Rank Approximation

    EoRA: Training-free Compensation for Compressed LLM with Eigenspace Low-Rank Approximation by Shih-Yang, Liu, Huck, Yang, Chien-Yi, Wang, Nai Chit Fung, Yin, Hongxu, Sakr, Charbel, Muralidharan, Saurav, Kwang-Ting, Cheng, Kautz, Jan, Yu-Chiang, Frank Wang, Molchanov, Pavlo, Min-Hung, Chen

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