Jayashree Mohan

43 papers A* 6A 2B 1Misc 1Journal 24Unranked 9
YearRankTypeTitle / Venue / Authors
2026 — conf
QoServe: Breaking the Silos of LLM Inference Serving.
ASPLOS (2)
Kanishk Goel, Jayashree Mohan, Nipun Kwatra, Ravi Shreyas Anupindi, Ramachandran Ramjee
2026 J jnl
Sutradhara: An Intelligent Orchestrator-Engine Co-design for Tool-based Agentic Inference.
CoRR
Anish Biswas, Kanishk Goel, Jayashree Mohan, Alind Khare, Anjaly Parayil, Ramachandran Ramjee, Chetan Bansal
2025 J jnl
AI Greenferencing: Routing AI Inferencing to Green Modular Data Centers with Heron.
CoRR
Tella Rajashekhar Reddy, Palak, Rohan Gandhi, Anjaly Parayil, Chaojie Zhang, Mike Shepperd, Liangcheng Yu, Jayashree Mohan, Srinivasan Iyengar, Shivkumar Kalyanaraman, Debopam Bhattacherjee
2025 J jnl
Efficient LLM Inference via Chunked Prefills.
ACM SIGOPS Oper. Syst. Rev.
Arney Agrawal, Nitin Kedia, Ashish Panwar, Jayashree Mohan, Nipun Kwatra, Bhargav S. Gulavani, Alexey Tumanov, Ramachandran Ramjee
2025 — conf
ModServe: Modality- and Stage-Aware Resource Disaggregation for Scalable Multimodal Model Serving.
SoCC
Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca
2025 J jnl
Niyama : Breaking the Silos of LLM Inference Serving.
CoRR
Kanishk Goel, Jayashree Mohan, Nipun Kwatra, Ravi Shreyas Anupindi, Ramachandran Ramjee
2025 J jnl
On Evaluating Performance of LLM Inference Serving Systems.
CoRR
Amey Agrawal, Nitin Kedia, Anmol Agarwal, Jayashree Mohan, Nipun Kwatra, Souvik Kundu, Ramachandran Ramjee, Alexey Tumanov
2025 — conf
POD-Attention: Unlocking Full Prefill-Decode Overlap for Faster LLM Inference.
ASPLOS (2)
Aditya K. Kamath, Ramya Prabhu, Jayashree Mohan, Simon Peter, Ramachandran Ramjee, Ashish Panwar
2025 J jnl
Project Silica: Towards Sustainable Cloud Archival Storage in Glass.
ACM Trans. Storage
Patrick Anderson, Erika Blancada Aranas, Youssef Assaf, Raphael Behrendt, Richard Black, Marco Caballero, Pashmina Cameron, Burcu Canakci, Andromachi Chatzieleftheriou, Rebekah Storan Clarke, James Clegg, Daniel Cletheroe, Bridgette Cooper, Thales De Carvalho, Tim Deegan, Austin Donnelly, Rokas Drevinskas, Alexander L. Gaunt, Christos Gkantsidis, Ariel Gomez Diaz, István Haller, Freddie Hong, Teodora Ilieva, Shashidhar Joshi, Russell Joyce, William M. Kunkel, David Lara, Sergey Legtchenko, Fanglin Linda Liu, Bruno Magalhães, Alana Marzoev, Marvin McNett, Jayashree Mohan, Michael Myrah, Truong Nguyen, Sebastian Nowozin, Aaron Ogus, Hiske Overweg, Antony I. T. Rowstron, Maneesh Sah, Masaaki Sakakura, Peter Scholtz, Nina Schreiner, Omer Sella, Adam Smith, Ioan A. Stefanovici, David Sweeney, Benn Thomsen, Govert Verkes, Phil Wainman, Jonathan Westcott, Luke Weston, Charles Whittaker, Pablo Wilke Berenguer, Hugh Williams, Thomas Winkler, Stefan Winzeck
2025 J jnl
Towards Efficient Large Multimodal Model Serving.
CoRR
Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca
2025 — conf
vAttention: Dynamic Memory Management for Serving LLMs without PagedAttention.
ASPLOS (1)
Ramya Prabhu, Ajay Nayak, Jayashree Mohan, Ramachandran Ramjee, Ashish Panwar
2024 J jnl
ASTRA: Accurate and Scalable ANNS-based Training of Extreme Classifiers.
CoRR
Sonu Mehta, Jayashree Mohan, Nagarajan Natarajan, Ramachandran Ramjee, Manik Varma
2024 J jnl
Metron: Holistic Performance Evaluation Framework for LLM Inference Systems.
CoRR
Amey Agrawal, Anmol Agarwal, Nitin Kedia, Jayashree Mohan, Souvik Kundu, Nipun Kwatra, Ramachandran Ramjee, Alexey Tumanov
2024 J jnl
POD-Attention: Unlocking Full Prefill-Decode Overlap for Faster LLM Inference.
CoRR
Aditya K. Kamath, Ramya Prabhu, Jayashree Mohan, Simon Peter, Ramachandran Ramjee, Ashish Panwar
2024 A* conf
Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve.
OSDI
Amey Agrawal, Nitin Kedia, Ashish Panwar, Jayashree Mohan, Nipun Kwatra, Bhargav S. Gulavani, Alexey Tumanov, Ramachandran Ramjee
2024 J jnl
Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve.
CoRR
Amey Agrawal, Nitin Kedia, Ashish Panwar, Jayashree Mohan, Nipun Kwatra, Bhargav S. Gulavani, Alexey Tumanov, Ramachandran Ramjee
2024 — conf
VIDUR: A Large-Scale Simulation Framework for LLM Inference.
MLSys
Amey Agrawal, Nitin Kedia, Jayashree Mohan, Ashish Panwar, Nipun Kwatra, Bhargav S. Gulavani, Ramachandran Ramjee, Alexey Tumanov
2024 J jnl
Vidur: A Large-Scale Simulation Framework For LLM Inference.
CoRR
Amey Agrawal, Nitin Kedia, Jayashree Mohan, Ashish Panwar, Nipun Kwatra, Bhargav S. Gulavani, Ramachandran Ramjee, Alexey Tumanov
2024 J jnl
vAttention: Dynamic Memory Management for Serving LLMs without PagedAttention.
CoRR
Ramya Prabhu, Ajay Nayak, Jayashree Mohan, Ramachandran Ramjee, Ashish Panwar
2023 A* conf
Project Silica: Towards Sustainable Cloud Archival Storage in Glass.
SOSP
Patrick Anderson, Erika Blancada Aranas, Youssef Assaf, Raphael Behrendt, Richard Black, Marco Caballero, Pashmina Cameron, Burcu Canakci, Thales De Carvalho, Andromachi Chatzieleftheriou, Rebekah Storan Clarke, James Clegg, Daniel Cletheroe, Bridgette Cooper, Tim Deegan, Austin Donnelly, Rokas Drevinskas, Alexander L. Gaunt, Christos Gkantsidis, Ariel Gomez Diaz, István Haller, Freddie Hong, Teodora Ilieva, Shashidhar Joshi, Russell Joyce, Mint Kunkel, David Lara, Sergey Legtchenko, Fanglin Linda Liu, Bruno Magalhães, Alana Marzoev, Marvin McNett, Jayashree Mohan, Michael Myrah, Truong Nguyen, Sebastian Nowozin, Aaron Ogus, Hiske Overweg, Antony I. T. Rowstron, Maneesh Sah, Masaaki Sakakura, Peter Scholtz, Nina Schreiner, Omer Sella, Adam Smith, Ioan A. Stefanovici, David Sweeney, Benn Thomsen, Govert Verkes, Phil Wainman, Jonathan Westcott, Luke Weston, Charles Whittaker, Pablo Wilke Berenguer, Hugh Williams, Thomas Winkler, Stefan Winzeck
2023 J jnl
SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills.
CoRR
Amey Agrawal, Ashish Panwar, Jayashree Mohan, Nipun Kwatra, Bhargav S. Gulavani, Ramachandran Ramjee
2022 A* conf
Looking Beyond GPUs for DNN Scheduling on Multi-Tenant Clusters.
OSDI
Jayashree Mohan, Amar Phanishayee, Janardhan Kulkarni, Vijay Chidambaram
2021 J jnl
Analyzing and Mitigating Data Stalls in DNN Training.
Proc. VLDB Endow.
Jayashree Mohan, Amar Phanishayee, Ashish Raniwala, Vijay Chidambaram
2021 A conf
CheckFreq: Frequent, Fine-Grained DNN Checkpointing.
FAST
Jayashree Mohan, Amar Phanishayee, Vijay Chidambaram
2021 A* conf
Memory Optimization for Deep Networks.
ICLR
Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl
2021 J jnl
Synergy: Resource Sensitive DNN Scheduling in Multi-Tenant Clusters.
CoRR
Jayashree Mohan, Amar Phanishayee, Janardhan Kulkarni, Vijay Chidambaram
2020 J jnl
Analyzing and Mitigating Data Stalls in DNN Training.
CoRR
Jayashree Mohan, Amar Phanishayee, Ashish Raniwala, Vijay Chidambaram
2020 J jnl
INSTalytics: Cluster Filesystem Co-design for Big-data Analytics.
ACM Trans. Storage
Muthian Sivathanu, Midhul Vuppalapati, Bhargav S. Gulavani, Kaushik Rajan, Jyoti Leeka, Jayashree Mohan, Piyus Kedia
2020 J jnl
Memory Optimization for Deep Networks.
CoRR
Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl
2019 — conf
Analyzing GDPR Compliance Through the Lens of Privacy Policy.
Poly/DMAH@VLDB
Jayashree Mohan, Melissa Wasserman, Vijay Chidambaram
2019 J jnl
Analyzing GDPR Compliance Through the Lens of Privacy Policy.
CoRR
Jayashree Mohan, Melissa Wasserman, Vijay Chidambaram
2019 J jnl
CrashMonkey and ACE: Systematically Testing File-System Crash Consistency.
ACM Trans. Storage
Jayashree Mohan, Ashlie Martinez, Soujanya Ponnapalli, Pandian Raju, Vijay Chidambaram
2019 A conf
INSTalytics: Cluster Filesystem Co-design for Big-data Analytics.
FAST
Muthian Sivathanu, Midhul Vuppalapati, Bhargav S. Gulavani, Kaushik Rajan, Jyoti Leeka, Jayashree Mohan, Piyus Kedia
2019 J jnl
RECIPE : Converting Concurrent DRAM Indexes to Persistent-Memory Indexes.
CoRR
Se Kwon Lee, Jayashree Mohan, Sanidhya Kashyap, Taesoo Kim, Vijay Chidambaram
2019 A* conf
Recipe: converting concurrent DRAM indexes to persistent-memory indexes.
SOSP
Se Kwon Lee, Jayashree Mohan, Sanidhya Kashyap, Taesoo Kim, Vijay Chidambaram
2018 A* conf
Finding Crash-Consistency Bugs with Bounded Black-Box Crash Testing.
OSDI
Jayashree Mohan, Ashlie Martinez, Soujanya Ponnapalli, Pandian Raju, Vijay Chidambaram
2018 J jnl
Finding Crash-Consistency Bugs with Bounded Black-Box Crash Testing.
CoRR
Jayashree Mohan, Ashlie Martinez, Soujanya Ponnapalli, Pandian Raju, Vijay Chidambaram
2017 Misc conf
A reinforcement learning approach to optimize downloads over mobile networks.
COMSNETS
Jayashree Mohan, Angad Vittal, K. Chandrasekaran, Bhaskar Krishnamachari
2017 J jnl
Analyzing IO Amplification in Linux File Systems.
CoRR
Jayashree Mohan, Rohan Kadekodi, Vijay Chidambaram
2017 — conf
Storage on Your SmartPhone Uses More Energy Than You Think.
HotStorage
Jayashree Mohan, Dhathri Purohith, Matthew Halpern, Vijay Chidambaram, Vijay Janapa Reddi
2017 — conf
The Dangers and Complexities of SQLite Benchmarking.
APSys
Dhathri Purohith, Jayashree Mohan, Vijay Chidambaram
2016 B conf
Optimizing Downloads over Random Duration Links in Mobile Networks.
ICCCN
Amber Bhargava, Spencer Congero, Timothy Ferrell, Alex Jones, Leo Linsky, Jayashree Mohan, Bhaskar Krishnamachari
2015 — conf
Smart and Secure Monitoring of Industrial Environments using IoT.
WCI
Shruthi Puranik, Jayashree Mohan, K. Chandrasekaran