Milos Nikolic

According to our database, Milos Nikolic authored at least 17 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Schrodinger's FP Training Neural Networks with Dynamic Floating-Point Containers.

Milos Nikolic, Enrique Torres-Sánchez, Jiahui Wang, Ali Hadi Zadeh, Mostafa Mahmoud, Ameer Abdelhadi, Kareem Ibrahim, Andreas Moshovos

Proceedings of the Seventh Annual Conference on Machine Learning and Systems, 2024

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization.

Milos Nikolic, Ghouthi Boukli Hacene, Ciaran Bannon, Alberto Delmas Lascorz, Matthieu Courbariaux, Omar Mohamed Awad, Isak Edo Vivancos, Yoshua Bengio, Vincent Gripon, Andreas Moshovos

Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

Atalanta: A Bit is Worth a "Thousand" Tensor Values.

Alberto Delmas Lascorz, Mostafa Mahmoud, Ali Hadi Zadeh, Milos Nikolic, Kareem Ibrahim, Christina Giannoula, Ameer Abdelhadi, Andreas Moshovos

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2022

Schrödinger's FP: Dynamic Adaptation of Floating-Point Containers for Deep Learning Training.

Milos Nikolic, Enrique Torres-Sánchez, Jiahui Wang, Ali Hadi Zadeh, Mostafa Mahmoud, Ameer Abdelhadi, Andreas Moshovos

CoRR, 2022

2021

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, Mostafa Mahmoud, Alberto Delmas Lascorz, Gennady Pekhimenko, Andreas Moshovos

Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

2020

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization.

Milos Nikolic, Ghouthi Boukli Hacene, Ciaran Bannon, Alberto Delmas Lascorz, Matthieu Courbariaux, Yoshua Bengio, Vincent Gripon, Andreas Moshovos

CoRR, 2020

Late Breaking Results: Building an On-Chip Deep Learning Memory Hierarchy Brick by Brick.

Isak Edo Vivancos, Sayeh Sharify, Milos Nikolic, Ciaran Bannon, Mostafa Mahmoud, Alberto Delmas Lascorz, Andreas Moshovos

Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

2019

Accelerating Image-Sensor-Based Deep Learning Applications.

Mostafa Mahmoud, Dylan Malone Stuart, Zissis Poulos, Alberto Delmas Lascorz, Patrick Judd, Sayeh Sharify, Milos Nikolic, Kevin Siu, Isak Edo Vivancos, Jorge Albericio, Andreas Moshovos

IEEE Micro, 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, Kevin Siu, Zissis Poulos, Andreas Moshovos

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019

Characterizing Sources of Ineffectual Computations in Deep Learning Networks.

Milos Nikolic, Mostafa Mahmoud, Andreas Moshovos, Yiren Zhao, Robert D. Mullins

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2019

Laconic deep learning inference acceleration.

Sayeh Sharify, Alberto Delmas Lascorz, Mostafa Mahmoud, Milos Nikolic, Kevin Siu, Dylan Malone Stuart, Zissis Poulos, Andreas Moshovos

Proceedings of the 46th International Symposium on Computer Architecture, 2019

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, Kevin Siu, Andreas Moshovos

Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems, 2019

2018

Laconic Deep Learning Computing.

Sayeh Sharify, Mostafa Mahmoud, Alberto Delmas Lascorz, Milos Nikolic, Andreas Moshovos

CoRR, 2018

DPRed: Making Typical Activation Values Matter In Deep Learning Computing.

Alberto Delmas, Sayeh Sharify, Patrick Judd, Milos Nikolic, Andreas Moshovos

CoRR, 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, Andreas Moshovos

CoRR, 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, Dylan Malone Stuart, Kevin Siu, Zissis Poulos, Tor M. Aamodt, Natalie D. Enright Jerger

Proceedings of the 16th IEEE International New Circuits and Systems Conference, 2018

Characterizing Sources of Ineffectual Computations in Deep Learning Networks.

Milos Nikolic, Mostafa Mahmoud, Andreas Moshovos

Proceedings of the 2018 IEEE International Symposium on Workload Characterization, 2018