Deepika Bablani

According to our database, Deepika Bablani authored at least 10 papers between 2018 and 2025.

Collaborative distances:

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

2025

SiLQ: Simple Large Language Model Quantization-Aware Training.

Steven K. Esser, Jeffrey L. McKinstry, Deepika Bablani, Rathinakumar Appuswamy, Dharmendra S. Modha

Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2025

2024

11.4 IBM NorthPole: An Architecture for Neural Network Inference with a 12nm Chip.

Andrew S. Cassidy, John V. Arthur, Filipp Akopyan, Alexander Andreopoulos, Rathinakumar Appuswamy, Pallab Datta, Michael V. DeBole, Steven K. Esser, Carlos Ortega Otero, Jun Sawada, Brian Taba, Arnon Amir, Deepika Bablani, Peter J. Carlson, Myron D. Flickner, Rajamohan Gandhasri, Guillaume Garreau, Megumi Ito, Jennifer L. Klamo, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Jeffrey L. McKinstry, Yutaka Y. Nakamura, Tapan K. Nayak, William P. Risk, Kai Schleupen, Ben Shaw, Jay Sivagnaname, Daniel F. Smith, Ignacio Terrizzano, Takanori Ueda, Dharmendra S. Modha

Proceedings of the IEEE International Solid-State Circuits Conference, 2024

Breakthrough Low-Latency, High-Energy-Efficiency LLM Inference Performance Using NorthPole.

Rathinakumar Appuswamy, Michael V. DeBole, Brian Taba, Steven K. Esser, Andrew S. Cassidy, Arnon Amir, Alexander Andreopoulos, Deepika Bablani, Pallab Datta, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Neil McGlohon, Jeffrey L. McKinstry, Tapan K. Nayak, Daniel F. Smith, Rafael Sousa, Ignacio Terrizzano, Filipp Akopyan, Peter J. Carlson, Rajamohan Gandhasri, Guillaume Garreau, Nelson M. Gonzalez, Megumi Ito, Jennifer L. Klamo, Yutaka Y. Nakamura, Carlos Ortega Otero, William P. Risk, Jun Sawada, Kai Schleupen, Jay Sivagnaname, Matthew Stallone, Takanori Ueda, Myron D. Flickner, John V. Arthur, Rameswar Panda, David D. Cox, Dharmendra S. Modha

Proceedings of the IEEE High Performance Extreme Computing Conference, 2024

Breakthrough Edge AI Inference Performance Using Northpole in 3U Vpx Form Factor.

Filipp Akopyan, William P. Risk, John V. Arthur, Andrew S. Cassidy, Michael V. DeBole, Carlos Ortega Otero, Jun Sawada, Evan Colgan, Michael E. Criscolo, Phillip V. Mann, Heinz Baier, Kai Schleupen, Arnon Amir, Alexander Andreopoulos, Rathinakumar Appuswamy, Deepika Bablani, Peter J. Carlson, Pallab Datta, Steven K. Esser, Myron D. Flickner, Rajamohan Gandhasri, Guillaume J. Garreau, Megumi Ito, Jennifer L. Klamo, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Neil McGlohon, Jeffrey L. McKinstry, Yutaka Y. Nakamura, Tapan K. Nayak, Jay Sivagnaname, Daniel F. Smith, Rafael Sousa, Brian Taba, Ignacio Terrizzano, Takanori Ueda, Dharmendra S. Modha

Proceedings of the IEEE High Performance Extreme Computing Conference, 2024

2023

Efficient and Effective Methods for Mixed Precision Neural Network Quantization for Faster, Energy-efficient Inference.

Deepika Bablani, Jeffrey L. McKinstry, Steven K. Esser, Rathinakumar Appuswamy, Dharmendra S. Modha

CoRR, 2023

IBM NorthPole Neural Inference Machine.

Dharmendra S. Modha, Filipp Akopyan, Alexander Andreopoulos, Rathinakumar Appuswamy, John V. Arthur, Andrew S. Cassidy, Pallab Datta, Michael V. DeBole, Steven K. Esser, Carlos Ortega Otero, Jun Sawada, Brian Taba, Arnon Amir, Deepika Bablani, Peter J. Carlson, Myron D. Flickner, Rajamohan Gandhasri, Guillaume Garreau, Megumi Ito, Jennifer L. Klamo, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Jeffrey L. McKinstry, Yutaka Y. Nakamura, Tapan K. Nayak, William P. Risk, Kai Schleupen, Ben Shaw, Jay Sivagnaname, Daniel F. Smith, Ignacio Terrizzano, Takanori Ueda

Proceedings of the 35th IEEE Hot Chips Symposium, 2023

2020

Learned Step Size quantization.

Steven K. Esser, Jeffrey L. McKinstry, Deepika Bablani, Rathinakumar Appuswamy, Dharmendra S. Modha

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Discovering Low-Precision Networks Close to Full-Precision Networks for Efficient Inference.

Jeffrey L. McKinstry, Steven K. Esser, Rathinakumar Appuswamy, Deepika Bablani, John V. Arthur, Izzet B. Yildiz, Dharmendra S. Modha

Proceedings of the Fifth Workshop on Energy Efficient Machine Learning and Cognitive Computing, 2019

2018

Low Precision Policy Distillation with Application to Low-Power, Real-time Sensation-Cognition-Action Loop with Neuromorphic Computing.

Jeffrey L. McKinstry, Davis R. Barch, Deepika Bablani, Michael DeBole, Steven K. Esser, Jeffrey A. Kusnitz, John V. Arthur, Dharmendra S. Modha

CoRR, 2018

Discovering Low-Precision Networks Close to Full-Precision Networks for Efficient Embedded Inference.

Jeffrey L. McKinstry, Steven K. Esser, Rathinakumar Appuswamy, Deepika Bablani, John V. Arthur, Izzet B. Yildiz, Dharmendra S. Modha

CoRR, 2018