Sujan K. Gonugondla

According to our database, Sujan K. Gonugondla authored at least 29 papers between 2015 and 2024.

Collaborative distances:

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

2024

Bifurcated Attention for Single-Context Large-Batch Sampling.

Ben Athiwaratkun, Sujan Kumar Gonugondla, Sanjay Krishna Gouda, Haifeng Qian, Hantian Ding, Qing Sun, Jun Wang, Jiacheng Guo, Liangfu Chen, Parminder Bhatia, Ramesh Nallapati, Sudipta Sengupta, Bing Xiang

CoRR, 2024

Token Alignment via Character Matching for Subword Completion.

Ben Athiwaratkun, Shiqi Wang, Mingyue Shang, Yuchen Tian, Zijian Wang, Sujan Kumar Gonugondla, Sanjay Krishna Gouda, Rob Kwiatkowski, Ramesh Nallapati, Bing Xiang

CoRR, 2024

2023

Greener yet Powerful: Taming Large Code Generation Models with Quantization.

Xiaokai Wei, Sujan K. Gonugondla, Wasi Uddin Ahmad, Shiqi Wang, Baishakhi Ray, Haifeng Qian, Xiaopeng Li, Varun Kumar, Zijian Wang, Yuchen Tian, Qing Sun, Ben Athiwaratkun, Mingyue Shang, Murali Krishna Ramanathan, Parminder Bhatia, Bing Xiang

CoRR, 2023

Towards Greener Yet Powerful Code Generation via Quantization: An Empirical Study.

Xiaokai Wei, Sujan Kumar Gonugondla, Shiqi Wang, Wasi Uddin Ahmad, Baishakhi Ray, Haifeng Qian, Xiaopeng Li, Varun Kumar, Zijian Wang, Yuchen Tian, Qing Sun, Ben Athiwaratkun, Mingyue Shang, Murali Krishna Ramanathan, Parminder Bhatia, Bing Xiang

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

Multi-lingual Evaluation of Code Generation Models.

Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, Xiaopeng Li, Yuchen Tian, Ming Tan, Wasi Uddin Ahmad, Shiqi Wang, Qing Sun, Mingyue Shang, Sujan Kumar Gonugondla, Hantian Ding, Varun Kumar, Nathan Fulton, Arash Farahani, Siddhartha Jain, Robert Giaquinto, Haifeng Qian, Murali Krishna Ramanathan, Ramesh Nallapati

Proceedings of the Eleventh International Conference on Learning Representations, 2023

PRIVE: Efficient RRAM Programming with Chip Verification for RRAM-based In-Memory Computing Acceleration.

Wangxin He, Jian Meng, Sujan Kumar Gonugondla, Shimeng Yu, Naresh R. Shanbhag, Jae-sun Seo

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

2022

Fundamental Limits on Energy-Delay-Accuracy of In-Memory Architectures in Inference Applications.

Sujan K. Gonugondla, Charbel Sakr, Hassan Dbouk, Naresh R. Shanbhag

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

Multi-lingual Evaluation of Code Generation Models.

Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, Xiaopeng Li, Yuchen Tian, Ming Tan, Wasi Uddin Ahmad, Shiqi Wang, Qing Sun, Mingyue Shang, Sujan Kumar Gonugondla, Hantian Ding, Varun Kumar, Nathan Fulton, Arash Farahani, Siddhartha Jain, Robert Giaquinto, Haifeng Qian, Murali Krishna Ramanathan, Ramesh Nallapati, Baishakhi Ray, Parminder Bhatia, Sudipta Sengupta, Dan Roth, Bing Xiang

CoRR, 2022

IMPQ: Reduced Complexity Neural Networks Via Granular Precision Assignment.

Sujan Kumar Gonugondla, Naresh R. Shanbhag

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

A 0.44-μJ/dec, 39.9-μs/dec, Recurrent Attention In-Memory Processor for Keyword Spotting.

Hassan Dbouk, Sujan K. Gonugondla, Charbel Sakr, Naresh R. Shanbhag

IEEE J. Solid State Circuits, 2021

2020

Cross-layer methods for energy-efficient inference using in-memory architectures

Sujan Kumar Gonugondla

PhD thesis, 2020

Deep In-Memory Architectures in SRAM: An Analog Approach to Approximate Computing.

Mingu Kang, Sujan K. Gonugondla, Naresh R. Shanbhag

Proc. IEEE, 2020

Fundamental Limits on the Precision of In-memory Architectures.

Sujan K. Gonugondla, Charbel Sakr, Hassan Dbouk, Naresh R. Shanbhag

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020

SWIPE: Enhancing Robustness of ReRAM Crossbars for In-memory Computing.

Sujan K. Gonugondla, Ameya D. Patil, Naresh R. Shanbhag

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020

KeyRAM: A 0.34 uJ/decision 18 k decisions/s Recurrent Attention In-memory Processor for Keyword Spotting.

Hassan Dbouk, Sujan K. Gonugondla, Charbel Sakr, Naresh R. Shanbhag

Proceedings of the 2020 IEEE Custom Integrated Circuits Conference, 2020

Block-LMS and RLS adaptive filters using in-memory architectures.

Chandrasekhar Radhakrishnan, Sujan K. Gonugondla

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

An MRAM-Based Deep In-Memory Architecture for Deep Neural Networks.

Ameya D. Patil, Haocheng Hua, Sujan K. Gonugondla, Mingu Kang, Naresh R. Shanbhag

Proceedings of the IEEE International Symposium on Circuits and Systems, 2019

Adaptive Filtering in In-Memory-Based Architectures.

Chandrasekhar Radhakrishnan, Sujan K. Gonugondla

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

A Multi-Functional In-Memory Inference Processor Using a Standard 6T SRAM Array.

Mingu Kang, Sujan K. Gonugondla, Ameya Patil, Naresh R. Shanbhag

IEEE J. Solid State Circuits, 2018

A 19.4-nJ/Decision, 364-K Decisions/s, In-Memory Random Forest Multi-Class Inference Accelerator.

Mingu Kang, Sujan K. Gonugondla, Sungmin Lim, Naresh R. Shanbhag

IEEE J. Solid State Circuits, 2018

A Variation-Tolerant In-Memory Machine Learning Classifier via On-Chip Training.

Sujan K. Gonugondla, Mingu Kang, Naresh R. Shanbhag

IEEE J. Solid State Circuits, 2018

An In-Memory VLSI Architecture for Convolutional Neural Networks.

Mingu Kang, Sungmin Lim, Sujan K. Gonugondla, Naresh R. Shanbhag

IEEE J. Emerg. Sel. Topics Circuits Syst., 2018

A 42pJ/decision 3.12TOPS/W robust in-memory machine learning classifier with on-chip training.

Sujan Kumar Gonugondla, Mingu Kang, Naresh R. Shanbhag

Proceedings of the 2018 IEEE International Solid-State Circuits Conference, 2018

Energy-Efficient Deep In-memory Architecture for NAND Flash Memories.

Sujan K. Gonugondla, Mingu Kang, Yongjune Kim, Mark Helm, Sean Eilert, Naresh R. Shanbhag

Proceedings of the IEEE International Symposium on Circuits and Systems, 2018

PROMISE: An End-to-End Design of a Programmable Mixed-Signal Accelerator for Machine-Learning Algorithms.

Prakalp Srivastava, Mingu Kang, Sujan K. Gonugondla, Sungmin Lim, Jungwook Choi, Vikram S. Adve, Nam Sung Kim, Naresh R. Shanbhag

Proceedings of the 45th ACM/IEEE Annual International Symposium on Computer Architecture, 2018

2017

A 19.4 nJ/decision 364K decisions/s in-memory random forest classifier in 6T SRAM array.

Mingu Kang, Sujan K. Gonugondla, Naresh R. Shanbhag

Proceedings of the 43rd IEEE European Solid State Circuits Conference, 2017

2016

A 481pJ/decision 3.4M decision/s Multifunctional Deep In-memory Inference Processor using Standard 6T SRAM Array.

Mingu Kang, Sujan K. Gonugondla, Ameya Patil, Naresh R. Shanbhag

CoRR, 2016

Perfect error compensation via algorithmic error cancellation.

Sujan K. Gonugondla, Byonghyo Shim, Naresh R. Shanbhag

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015

An energy-efficient memory-based high-throughput VLSI architecture for convolutional networks.

Mingu Kang, Sujan K. Gonugondla, Min-Sun Keel, Naresh R. Shanbhag

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015