An improved FPGA-based specific processor for Blokus Duo. - Javier Olivito; Alberto Delmas; Javier Resano (FPT, 2014)

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)

IDEAL: image denoising accelerator. - Mostafa Mahmoud; Bojian Zheng; Alberto Delmas Lascorz; Felix Heide; Jonathan Assouline; Paul Boucher; Emmanuel Onzon; 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)

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. - Milos Nikolic 002; Ghouthi Boukli Hacene; Ciaran Bannon; Alberto Delmas Lascorz; Matthieu Courbariaux; Yoshua Bengio; Vincent Gripon; Andreas Moshovos (CoRR, 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)

APack: Off-Chip, Lossless Data Compression for Efficient Deep Learning Inference. - Alberto Delmas Lascorz; Mostafa Mahmoud; Andreas Moshovos (CoRR, 2022)

Every Bit Matters: A Hardware/Software Approach for Enabling More Powerful Machine Learning Models. - Enrique Torres-Sánchez; Milos Nikolic 002; Kareem Ibrahim; Alberto Delmas Lascorz; Ali Hadi Zadeh; Jiahui Wang; Ameer Abdelhadi; Mostafa Mahmoud; Christina Giannoula; Andreas Moshovos (IEEECONF, 2024)

Atalanta: A Bit is Worth a "Thousand" Tensor Values. - Alberto Delmas Lascorz; Mostafa Mahmoud; Ali Hadi Zadeh; Milos Nikolic 002; Kareem Ibrahim; Christina Giannoula; Ameer Abdelhadi; Andreas Moshovos (ASPLOS (2), 2024)

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. - Milos Nikolic 002; Ghouthi Boukli Hacene; Ciaran Bannon; Alberto Delmas Lascorz; Matthieu Courbariaux; Omar Mohamed Awad; Isak Edo Vivancos; Yoshua Bengio; Vincent Gripon; Andreas Moshovos (ISCAS, 2024)