Towards Practical Page Placement for a Green Memory Manager. - Ashish Panwar; K. Gopinath (HiPC, 2015)

A Case for Protecting Huge Pages from the Kernel. - Ashish Panwar; Naman Patel; K. Gopinath (APSys, 2016)

Making Huge Pages Actually Useful. - Ashish Panwar; Aravinda Prasad; K. Gopinath (ASPLOS, 2018)

HawkEye: Efficient Fine-grained OS Support for Huge Pages. - Ashish Panwar; Sorav Bansal; K. Gopinath (ASPLOS, 2019)

Mitosis: Transparently Self-Replicating Page-Tables for Large-Memory Machines. - Reto Achermann; Ashish Panwar; Abhishek Bhattacharjee; Timothy Roscoe; Jayneel Gandhi (ASPLOS, 2020)

Leveraging Architectural Support of Three Page Sizes with Trident. - Venkat Sri Sai Ram; Ashish Panwar; Arkaprava Basu (CoRR, 2020)

nuKSM: NUMA-aware Memory De-duplication on Multi-socket Servers. - Akash Panda; Ashish Panwar; Arkaprava Basu (PACT, 2021)

Fast local page-tables for virtualized NUMA servers with vMitosis. - Ashish Panwar; Reto Achermann; Arkaprava Basu; Abhishek Bhattacharjee; K. Gopinath; Jayneel Gandhi (ASPLOS, 2021)

Trident: Harnessing Architectural Resources for All Page Sizes in x86 Processors. - Venkat Sri Sai Ram; Ashish Panwar; Arkaprava Basu (MICRO, 2021)

SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills. - Amey Agrawal; Ashish Panwar; Jayashree Mohan; Nipun Kwatra; Bhargav S. Gulavani; Ramachandran Ramjee (CoRR, 2023)

VIDUR: A Large-Scale Simulation Framework for LLM Inference. - Amey Agrawal; Nitin Kedia; Jayashree Mohan; Ashish Panwar; Nipun Kwatra; Bhargav S. Gulavani; Ramachandran Ramjee; Alexey Tumanov (MLSys, 2024)

Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve. - Amey Agrawal; Nitin Kedia; Ashish Panwar; Jayashree Mohan; Nipun Kwatra; Bhargav S. Gulavani; Alexey Tumanov; Ramachandran Ramjee (OSDI, 2024)

Address Scaling: Architectural Support for Fine-Grained Thread-Safe Metadata Management. - Deepanjali Mishra; Konstantinos Kanellopoulos; Ashish Panwar; Akshitha Sriraman; Vivek Seshadri; Onur Mutlu; Todd C. Mowry (IEEE Comput. Archit. Lett., 2024)

SIGMA: Secure GPT Inference with Function Secret Sharing. - Kanav Gupta; Neha Jawalkar; Ananta Mukherjee; Nishanth Chandran; Divya Gupta 001; Ashish Panwar; Rahul Sharma 001 (Proc. Priv. Enhancing Technol., 2024)

POD-Attention: Unlocking Full Prefill-Decode Overlap for Faster LLM Inference. - Aditya K. Kamath; Ramya Prabhu; Jayashree Mohan; Simon Peter 001; Ramachandran Ramjee; Ashish Panwar (ASPLOS (2), 2025)

vAttention: Dynamic Memory Management for Serving LLMs without PagedAttention. - Ramya Prabhu; Ajay Nayak; Jayashree Mohan; Ramachandran Ramjee; Ashish Panwar (ASPLOS (1), 2025)

EMD: Fair and Efficient Dynamic Memory De-bloating of Transparent Huge Pages. - Parth Gangar; Ashish Panwar; K. Gopinath (ISMM, 2025)

PyGraph: Robust Compiler Support for CUDA Graphs in PyTorch. - Abhishek Ghosh; Ajay Nayak; Ashish Panwar; Arkaprava Basu (CoRR, 2025)

Efficient LLM Inference via Chunked Prefills. - Arney Agrawal; Nitin Kedia; Ashish Panwar; Jayashree Mohan; Nipun Kwatra; Bhargav S. Gulavani; Alexey Tumanov; Ramachandran Ramjee (ACM SIGOPS Oper. Syst. Rev., 2025)