Bit-Pragmatic Deep Neural Network Computing. - Jorge Albericio; Patrick Judd; Alberto Delmas; Sayeh Sharify; Andreas Moshovos (ICLR (Workshop), 2017)

Bit-pragmatic deep neural network computing. - Jorge Albericio; Alberto Delmas; Patrick Judd; Sayeh Sharify; Gerard O'Leary; Roman Genov; Andreas Moshovos (MICRO, 2017)

Dynamic Stripes: Exploiting the Dynamic Precision Requirements of Activation Values in Neural Networks. - Alberto Delmas; Patrick Judd; Sayeh Sharify; Andreas Moshovos (CoRR, 2017)

Tartan: Accelerating Fully-Connected and Convolutional Layers in Deep Learning Networks by Exploiting Numerical Precision Variability. - Alberto Delmas; Sayeh Sharify; Patrick Judd; Andreas Moshovos (CoRR, 2017)

Cnvlutin2: Ineffectual-Activation-and-Weight-Free Deep Neural Network Computing. - Patrick Judd; Alberto Delmas Lascorz; Sayeh Sharify; Andreas Moshovos (CoRR, 2017)

Loom: Exploiting Weight and Activation Precisions to Accelerate Convolutional Neural Networks. - Sayeh Sharify; Alberto Delmas Lascorz; Patrick Judd; Andreas Moshovos (CoRR, 2017)

Loom: exploiting weight and activation precisions to accelerate convolutional neural networks. - Sayeh Sharify; Alberto Delmas Lascorz; Kevin Siu; Patrick Judd; Andreas Moshovos (DAC, 2018)

Identifying and Exploiting Ineffectual Computations to Enable Hardware Acceleration of Deep Learning. - Andreas Moshovos; Jorge Albericio; Patrick Judd; Alberto Delmas; Sayeh Sharify; Mostafa Mahmoud; Tayler H. Hetherington; Milos Nikolic 002; Dylan Malone Stuart; Kevin Siu; Zissis Poulos; Tor M. Aamodt; et al. (NEWCAS, 2018)

Exploiting Typical Values to Accelerate Deep Learning. - Andreas Moshovos; Jorge Albericio; Patrick Judd; Alberto Delmas Lascorz; Sayeh Sharify; Zissis Poulos; Tayler H. Hetherington; Tor M. Aamodt; Natalie D. Enright Jerger (Computer, 2018)

Bit-Tactical: Exploiting Ineffectual Computations in Convolutional Neural Networks: Which, Why, and How. - Alberto Delmas; Patrick Judd; Dylan Malone Stuart; Zissis Poulos; Mostafa Mahmoud; Sayeh Sharify; Milos Nikolic 002; Andreas Moshovos (CoRR, 2018)

DPRed: Making Typical Activation Values Matter In Deep Learning Computing. - Alberto Delmas; Sayeh Sharify; Patrick Judd; Milos Nikolic 002; Andreas Moshovos (CoRR, 2018)

Laconic Deep Learning Computing. - Sayeh Sharify; Mostafa Mahmoud; Alberto Delmas Lascorz; Milos Nikolic 002; Andreas Moshovos (CoRR, 2018)

Value-Based Deep-Learning Acceleration. - Andreas Moshovos; Jorge Albericio; Patrick Judd; Alberto Delmas Lascorz; Sayeh Sharify; Tayler H. Hetherington; Tor M. Aamodt; Natalie D. Enright Jerger (IEEE Micro, 2018)

Bit-Tactical: A Software/Hardware Approach to Exploiting Value and Bit Sparsity in Neural Networks. - Alberto Delmas Lascorz; Patrick Judd; Dylan Malone Stuart; Zissis Poulos; Mostafa Mahmoud; Sayeh Sharify; Milos Nikolic 002; Kevin Siu; Andreas Moshovos (ASPLOS, 2019)

Laconic deep learning inference acceleration. - Sayeh Sharify; Alberto Delmas Lascorz; Mostafa Mahmoud; Milos Nikolic 002; Kevin Siu; Dylan Malone Stuart; Zissis Poulos; Andreas Moshovos (ISCA, 2019)

ShapeShifter: Enabling Fine-Grain Data Width Adaptation in Deep Learning. - Alberto Delmas Lascorz; Sayeh Sharify; Isak Edo Vivancos; Dylan Malone Stuart; Omar Mohamed Awad; Patrick Judd; Mostafa Mahmoud; Milos Nikolic 002; Kevin Siu; Zissis Poulos; Andreas Moshovos (MICRO, 2019)

Accelerating Image-Sensor-Based Deep Learning Applications. - Mostafa Mahmoud; Dylan Malone Stuart; Zissis Poulos; Alberto Delmas Lascorz; Patrick Judd; Sayeh Sharify; Milos Nikolic 002; Kevin Siu; Isak Edo Vivancos; Jorge Albericio; Andreas Moshovos (IEEE Micro, 2019)

Late Breaking Results: Building an On-Chip Deep Learning Memory Hierarchy Brick by Brick. - Isak Edo Vivancos; Sayeh Sharify; Milos Nikolic 002; Ciaran Bannon; Mostafa Mahmoud; Alberto Delmas Lascorz; Andreas Moshovos (DAC, 2020)

Boveda: Building an On-Chip Deep Learning Memory Hierarchy Brick by Brick. - Isak Edo Vivancos; Sayeh Sharify; Daniel Ly-Ma; Ameer Abdelhadi; Ciaran Bannon; Milos Nikolic 002; Mostafa Mahmoud; Alberto Delmas Lascorz; Gennady Pekhimenko; Andreas Moshovos (MLSys, 2021)

Mixed-Precision Quantization with Cross-Layer Dependencies. - Zihao Deng; Xin Wang; Sayeh Sharify; Michael Orshansky (CoRR, 2023)

Post Training Quantization of Large Language Models with Microscaling Formats. - Sayeh Sharify; Utkarsh Saxena; Zifei Xu; Wanzin Yazar; Ilya Soloveychik; Xin Wang (ENLSP, 2024)

Scaling laws for post-training quantized large language models. - Zifei Xu; Alexander Lan; Wanzin Yazar; Tristan Webb; Sayeh Sharify; Xin Wang (ENLSP, 2024)

Self-Selected Attention Span for Accelerating Large Language Model Inference. - Tian Jin; Wanzin Yazar; Zifei Xu; Sayeh Sharify; Xin Wang (CoRR, 2024)

Combining multiple post-training techniques to achieve most efficient quantized LLMs. - Sayeh Sharify; Zifei Xu; Wanzin Yazar; Xin Wang (CoRR, 2024)

Understanding the difficulty of low-precision post-training quantization of large language models. - Zifei Xu; Sayeh Sharify; Wanzin Yazar; Tristan Webb; Xin Wang (CoRR, 2024)

ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals. - Utkarsh Saxena; Sayeh Sharify; Kaushik Roy; Xin Wang (CoRR, 2024)

Early Attentive Sparsification Accelerates Neural Speech Transcription. - Zifei Xu; Sayeh Sharify; Hesham Mostafa; Tristan Webb; Wanzin Yazar; Xin Wang (CoRR, 2025)