An energy-efficient memory-based high-throughput VLSI architecture for convolutional networks. - Mingu Kang; Sujan K. Gonugondla; Min-Sun Keel; Naresh R. Shanbhag (ICASSP, 2015)

Perfect error compensation via algorithmic error cancellation. - Sujan K. Gonugondla; Byonghyo Shim; Naresh R. Shanbhag (ICASSP, 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)

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 (ESSCIRC, 2017)

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 (ISCA, 2018)

Energy-Efficient Deep In-memory Architecture for NAND Flash Memories. - Sujan K. Gonugondla; Mingu Kang; Yongjune Kim 001; Mark Helm; Sean Eilert; Naresh R. Shanbhag (ISCAS, 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 (ISSCC, 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 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)

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 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)

Adaptive Filtering in In-Memory-Based Architectures. - Chandrasekhar Radhakrishnan; Sujan K. Gonugondla (ACSSC, 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 (ISCAS, 2019)

Block-LMS and RLS adaptive filters using in-memory architectures. - Chandrasekhar Radhakrishnan; Sujan K. Gonugondla (ACSSC, 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 (CICC, 2020)

SWIPE: Enhancing Robustness of ReRAM Crossbars for In-memory Computing. - Sujan K. Gonugondla; Ameya D. Patil; Naresh R. Shanbhag (ICCAD, 2020)

Fundamental Limits on the Precision of In-memory Architectures. - Sujan K. Gonugondla; Charbel Sakr; Hassan Dbouk; Naresh R. Shanbhag (ICCAD, 2020)

Deep In-Memory Architectures in SRAM: An Analog Approach to Approximate Computing. - Mingu Kang; Sujan K. Gonugondla; Naresh R. Shanbhag (Proc. IEEE, 2020)

Cross-layer methods for energy-efficient inference using in-memory architectures - Sujan Kumar Gonugondla (2020)

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)

IMPQ: Reduced Complexity Neural Networks Via Granular Precision Assignment. - Sujan Kumar Gonugondla; Naresh R. Shanbhag (ICASSP, 2022)

Multi-lingual Evaluation of Code Generation Models. - Ben Athiwaratkun; Sanjay Krishna Gouda; Zijian Wang 002; Xiaopeng Li 002; Yuchen Tian; Ming Tan; Wasi Uddin Ahmad; Shiqi Wang 002; Qing Sun; Mingyue Shang; Sujan Kumar Gonugondla; Hantian Ding; et al. (CoRR, 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)

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 (DATE, 2023)

Multi-lingual Evaluation of Code Generation Models. - Ben Athiwaratkun; Sanjay Krishna Gouda; Zijian Wang 002; Xiaopeng Li 002; Yuchen Tian; Ming Tan; Wasi Uddin Ahmad; Shiqi Wang 002; Qing Sun; Mingyue Shang; Sujan Kumar Gonugondla; Hantian Ding; et al. (ICLR, 2023)

Towards Greener Yet Powerful Code Generation via Quantization: An Empirical Study. - Xiaokai Wei; Sujan Kumar Gonugondla; Shiqi Wang 002; Wasi Uddin Ahmad; Baishakhi Ray; Haifeng Qian; Xiaopeng Li 002; Varun Kumar; Zijian Wang 002; Yuchen Tian; Qing Sun; Ben Athiwaratkun; et al. (ESEC/SIGSOFT FSE, 2023)

Greener yet Powerful: Taming Large Code Generation Models with Quantization. - Xiaokai Wei; Sujan K. Gonugondla; Wasi Uddin Ahmad; Shiqi Wang 002; Baishakhi Ray; Haifeng Qian; Xiaopeng Li 002; Varun Kumar; Zijian Wang 002; Yuchen Tian; Qing Sun; Ben Athiwaratkun; et al. (CoRR, 2023)

Token Alignment via Character Matching for Subword Completion. - Ben Athiwaratkun; Shiqi Wang 002; Mingyue Shang; Yuchen Tian; Zijian Wang 002; Sujan Kumar Gonugondla; Sanjay Krishna Gouda; Robert Kwiatkowski; Ramesh Nallapati; Parminder Bhatia; Bing Xiang (ACL (Findings), 2024)

BASS: Batched Attention-optimized Speculative Sampling. - Haifeng Qian; Sujan Kumar Gonugondla; Sungsoo Ha; Mingyue Shang; Sanjay Krishna Gouda; Ramesh Nallapati; Sudipta Sengupta; Xiaofei Ma 001; Anoop Deoras (ACL (Findings), 2024)

The N-Grammys: Accelerating Autoregressive Inference with Learning-Free Batched Speculation. - Lawrence Stewart; Matthew Trager; Sujan K. Gonugondla; Stefano Soatto (ENLSP, 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 022; Jiacheng Guo; Liangfu Chen; Parminder Bhatia; Ramesh Nallapati; Sudipta Sengupta; et al. (ICML, 2024)

Token Alignment via Character Matching for Subword Completion. - Ben Athiwaratkun; Shiqi Wang 002; Mingyue Shang; Yuchen Tian; Zijian Wang 002; Sujan Kumar Gonugondla; Sanjay Krishna Gouda; Rob Kwiatkowski; Ramesh Nallapati; Bing Xiang (CoRR, 2024)

Approximately Aligned Decoding. - Daniel Melcer; Sujan K. Gonugondla; Pramuditha Perera; Haifeng Qian; Wen-Hao Chiang; Yanjun Wang; Nihal Jain; Pranav Garg 001; Xiaofei Ma 001; Anoop Deoras (CoRR, 2024)