Siddhisanket Raskar

23 papers B 1Journal 5Unranked 17
YearRankTypeTitle / Venue / Authors
2026 — conf
PagedEviction: Structured Block-wise KV Cache Pruning for Efficient Large Language Model Inference.
EACL (Findings)
Krishna Teja Chitty-Venkata, Jie Ye, Siddhisanket Raskar, Anthony Kougkas, Xian-He Sun, Murali Emani, Venkatram Vishwanath, Bogdan Nicolae
2025 — conf
MoE-Inference-Bench: Performance Evaluation of Mixture of Expert Large Language and Vision Models.
SC Workshops
Krishna Teja Chitty-Venkata, Sylvia Howland, Golara Azar, Daria Soboleva, Natalia Vassilieva, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath
2025 J jnl
MoE-Inference-Bench: Performance Evaluation of Mixture of Expert Large Language and Vision Models.
CoRR
Krishna Teja Chitty-Venkata, Sylvia Howland, Golara Azar, Daria Soboleva, Natalia Vassilieva, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath
2024 — conf
LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators.
SC Workshops
Krishna Teja Chitty-Venkata, Siddhisanket Raskar, Bharat Kale, Farah Ferdaus, Aditya Tanikanti, Ken Raffenetti, Valerie Taylor, Murali Emani, Venkatram Vishwanath
2024 J jnl
LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators.
CoRR
Krishna Teja Chitty-Venkata, Siddhisanket Raskar, Bharat Kale, Farah Ferdaus, Aditya Tanikanti, Ken Raffenetti, Valerie Taylor, Murali Emani, Venkatram Vishwanath
2024 — conf
Thorough Characterization and Analysis of Large Transformer Model Training At-Scale.
SIGMETRICS/Performance (Abstracts)
Scott Cheng, Jun-Liang Lin, Murali Emani, Siddhisanket Raskar, Sam Foreman, Zhen Xie, Venkatram Vishwanath, Mahmut T. Kandemir
2024 J jnl
Thorough Characterization and Analysis of Large Transformer Model Training At-Scale.
Proc. ACM Meas. Anal. Comput. Syst.
Scott Cheng, Jun-Liang Lin, Murali Emani, Siddhisanket Raskar, Sam Foreman, Zhen Xie, Venkatram Vishwanath, Mahmut Taylan Kandemir
2024 — conf
Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators.
IPDPS (Workshops)
Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, Michael E. Papka, Sanjif Shanmugavelu, Darshan Gandhi, Hengyu Zhao, Dun Ma, Kiran Ranganath, Rick Weisner, Jiunn-Yeu Chen, Yuting Yang, Natalia Vassilieva, Bin C. Zhang, Sylvia Howland, Alexander Tsyplikhin
2023 J jnl
A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators.
CoRR
Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, Michael E. Papka
2023 — conf
Characterizing the Performance of Triangle Counting on Graphcore's IPU Architecture.
SC Workshops
Reet Barik, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath
2023 — conf
Codelet Pipe: Realization of Dataflow Software Pipelining for Extended Codelet Model.
ICPP Workshops
Siddhisanket Raskar, Thomas Applencourt, Kalyan Kumaran, Guang R. Gao
2023 B conf
Implementation of Dataflow Software Pipelining for Codelet Model.
ICPE
Siddhisanket Raskar, Jose Manuel Monsalve Diaz, Thomas Applencourt, Kalyan Kumaran, Guang Gao
2023 — conf
Towards Fault Tolerance and Resilience in the Sequential Codelet Model.
CARLA
Diego A. Roa Perdomo, Rafael A. Herrera Guaitero, Dawson Fox, Hervé Yviquel, Siddhisanket Raskar, Xiaoming Li, Jose Manuel Monsalve Diaz
2023 — conf
Towards Maximum Throughput of Dataflow Software Pipeline under Resource Constraints.
PMAM@PPoPP
Siddhisanket Raskar, Thomas Applencourt, Kalyan Kumaran, Guang Gao
2023 — conf
TrainBF: High-Performance DNN Training Engine Using BFloat16 on AI Accelerators.
Euro-Par
Zhen Xie, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath
2023 — conf
Transfer Learning Across Heterogeneous Features For Efficient Tensor Program Generation.
ExHET@PPoPP
Gaurav Verma, Siddhisanket Raskar, Zhen Xie, Abid M. Malik, Murali Emani, Barbara M. Chapman
2023 J jnl
Transfer Learning Across Heterogeneous Features For Efficient Tensor Program Generation.
CoRR
Gaurav Verma, Siddhisanket Raskar, Zhen Xie, Abid M. Malik, Murali Emani, Barbara M. Chapman
2022 — conf
A Comprehensive Evaluation of Novel AI Accelerators for Deep Learning Workloads.
PMBS@SC
Murali Emani, Zhen Xie, Siddhisanket Raskar, Varuni Sastry, William Arnold, Bruce Wilson, Rajeev Thakur, Venkatram Vishwanath, Zhengchun Liu, Michael E. Papka, Cindy Orozco Bohorquez, Rick Weisner, Karen Li, Yongning Sheng, Yun Du, Jian Zhang, Alexander Tsyplikhin, Gurdaman Khaira, Jeremy Fowers, Ramakrishnan Sivakumar, Victoria Godsoe, Adrián Macías, Chetan Tekur, Matthew Boyd
2022 — conf
Throughput-oriented and Accuracy-aware DNN Training with BFloat16 on GPU.
IPDPS Workshops
Zhen Xie, Siddhisanket Raskar, Murali Emani
2020 — conf
CODIR: Towards an MLIR Codelet Model Dialect.
IPDRM@SC
Ryan Kabrick, Diego A. Roa Perdomo, Siddhisanket Raskar, Jose Manuel Monsalve Diaz, Dawson Fox, Guang R. Gao
2020 — conf
DEMAC: A Modular Platform for HW-SW Co-Design.
IPDRM@SC
Diego A. Roa Perdomo, Ryan Kabrick, Jose Manuel Monsalve Diaz, Siddhisanket Raskar, Dawson Fox, Guang R. Gao
2019 — conf
Position Paper: Extending Codelet Model for Dataflow Software Pipelining using Software-Hardware Co-Design.
COMPSAC (2)
Siddhisanket Raskar, Thomas Applencourt, Kalyan Kumaran, Guang Gao
2019 — conf
Toward A High-Performance Emulation Platformfor Brain-Inspired Intelligent SystemsExploring Dataflow-Based Execution Model and Beyond.
COMPSAC (2)
Sihan Zeng, Jose Manuel Monsalve Diaz, Siddhisanket Raskar