Charbel Sakr

Publication Activity (10 Years)

Years Active: 1997-2023
Publications (10 Years): 26

Top Topics

Fundamental Limits

Learning Algorithm

Top Venues

IEEE J. Solid State Circuits

Publications

Ben Keller, Rangharajan Venkatesan, Steve Dai, Stephen G. Tell, Brian Zimmer, Charbel Sakr, William J. Dally, C. Thomas Gray, Brucek Khailany
A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm. IEEE J. Solid State Circuits 58 (4) (2023)
Yu-Shun Hsiao, Siva Kumar Sastry Hari, Balakumar Sundaralingam, Jason Yik, Thierry Tambe, Charbel Sakr, Stephen W. Keckler, Vijay Janapa Reddi
VaPr: Variable-Precision Tensors to Accelerate Robot Motion Planning. IROS (2023)
Yu-Shun Hsiao, Siva Kumar Sastry Hari, Balakumar Sundaralingam, Jason Yik, Thierry Tambe, Charbel Sakr, Stephen W. Keckler, Vijay Janapa Reddi
VaPr: Variable-Precision Tensors to Accelerate Robot Motion Planning. CoRR (2023)
Sujan K. Gonugondla, Charbel Sakr, Hassan Dbouk, Naresh R. Shanbhag
Fundamental Limits on Energy-Delay-Accuracy of In-Memory Architectures in Inference Applications. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41 (10) (2022)
Charbel Sakr, Steve Dai, Rangharajan Venkatesan, Brian Zimmer, William J. Dally, Brucek Khailany
Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training. ICML (2022)
Charbel Sakr, Steve Dai, Rangharajan Venkatesan, Brian Zimmer, William J. Dally, Brucek Khailany
Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training. CoRR (2022)
Abdulrahman Mahmoud, Siva Kumar Sastry Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh R. Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Stephen W. Keckler
Optimizing Selective Protection for CNN Resilience. ISSRE (2021)
Charbel Sakr, Naresh R. Shanbhag
Signal Processing Methods to Enhance the Energy Efficiency of In-Memory Computing Architectures. IEEE Trans. Signal Process. 69 (2021)
Hassan Dbouk, Sujan K. Gonugondla, Charbel Sakr, Naresh R. Shanbhag
A 0.44-μJ/dec, 39.9-μs/dec, Recurrent Attention In-Memory Processor for Keyword Spotting. IEEE J. Solid State Circuits 56 (7) (2021)
Abdulrahman Mahmoud, Siva Kumar Sastry Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh R. Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Stephen W. Keckler
HarDNN: Feature Map Vulnerability Evaluation in CNNs. CoRR (2020)
Hassan Dbouk, Sujan K. Gonugondla, Charbel Sakr, Naresh R. Shanbhag
KeyRAM: A 0.34 uJ/decision 18 k decisions/s Recurrent Attention In-memory Processor for Keyword Spotting. CICC (2020)
Sujan K. Gonugondla, Charbel Sakr, Hassan Dbouk, Naresh R. Shanbhag
Fundamental Limits on the Precision of In-memory Architectures. ICCAD (2020)
Sujan Kumar Gonugondla, Charbel Sakr, Hassan Dbouk, Naresh R. Shanbhag
Fundamental Limits on Energy-Delay-Accuracy of In-memory Architectures in Inference Applications. CoRR (2020)
Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. CoRR (2019)
Charbel Sakr, Yongjune Kim, Naresh R. Shanbhag
Minimum Precision Requirements of General Margin Hyperplane Classifiers. IEEE J. Emerg. Sel. Topics Circuits Syst. 9 (2) (2019)
Charbel Sakr, Naresh R. Shanbhag
Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm. ICLR (Poster) (2019)
Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. ICLR (Poster) (2019)
Charbel Sakr, Naresh R. Shanbhag
An Analytical Method to Determine Minimum Per-Layer Precision of Deep Neural Networks. ICASSP (2018)
Charbel Sakr, Jungwook Choi, Zhuo Wang, Kailash Gopalakrishnan, Naresh R. Shanbhag
True Gradient-Based Training of Deep Binary Activated Neural Networks Via Continuous Binarization. ICASSP (2018)
Charbel Sakr, Naresh R. Shanbhag
Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm. CoRR (2018)
Charbel Sakr, Naresh R. Shanbhag
Minimum Precision Requirements for Deep Learning with Biomedical Datasets. BioCAS (2018)
Charbel Sakr, Yongjune Kim, Naresh R. Shanbhag
Analytical Guarantees on Numerical Precision of Deep Neural Networks. ICML (2017)
Charbel Sakr, Ameya D. Patil, Sai Zhang, Yongjune Kim, Naresh R. Shanbhag
Minimum precision requirements for the SVM-SGD learning algorithm. ICASSP (2017)
Yingyan Lin, Charbel Sakr, Yongjune Kim, Naresh R. Shanbhag
PredictiveNet: An energy-efficient convolutional neural network via zero prediction. ISCAS (2017)
Charbel Sakr, Ameya Patil, Sai Zhang, Naresh R. Shanbhag
Understanding the Energy and Precision Requirements for Online Learning. CoRR (2016)
Sai Zhang, Mingu Kang, Charbel Sakr, Naresh R. Shanbhag
Reducing the Energy Cost of Inference via In-sensor Information Processing. CoRR (2016)
Charbel Sakr, Terence D. Todd
Carrier-Sense Protocols for Packet-Switched Smart Antenna Basestations. Int. J. Wirel. Inf. Networks 7 (3) (2000)
Charbel Sakr, Terence D. Todd
Carrier-sense protocols for packet-switched smart antenna basestations. ICNP (1997)