Position Paper: Extending Codelet Model for Dataflow Software Pipelining using Software-Hardware Co-Design. - Siddhisanket Raskar; Thomas Applencourt; Kalyan Kumaran; Guang Gao 001 (COMPSAC (2), 2019)

Toward A High-Performance Emulation Platformfor Brain-Inspired Intelligent SystemsExploring Dataflow-Based Execution Model and Beyond. - Sihan Zeng; Jose Manuel Monsalve Diaz; Siddhisanket Raskar (COMPSAC (2), 2019)

CODIR: Towards an MLIR Codelet Model Dialect. - Ryan Kabrick; Diego A. Roa Perdomo; Siddhisanket Raskar; Jose Manuel Monsalve Diaz; Dawson Fox; Guang R. Gao (IPDRM@SC, 2020)

DEMAC: A Modular Platform for HW-SW Co-Design. - Diego A. Roa Perdomo; Ryan Kabrick; Jose Manuel Monsalve Diaz; Siddhisanket Raskar; Dawson Fox; Guang R. Gao (IPDRM@SC, 2020)

Throughput-oriented and Accuracy-aware DNN Training with BFloat16 on GPU. - Zhen Xie; Siddhisanket Raskar; Murali Emani (IPDPS Workshops, 2022)

A Comprehensive Evaluation of Novel AI Accelerators for Deep Learning Workloads. - 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; et al. (PMBS@SC, 2022)

Towards Fault Tolerance and Resilience in the Sequential Codelet Model. - Diego A. Roa Perdomo; Rafael A. Herrera Guaitero; Dawson Fox; Hervé Yviquel; Siddhisanket Raskar; Xiaoming Li 010; Jose Manuel Monsalve Diaz (CARLA, 2023)

TrainBF: High-Performance DNN Training Engine Using BFloat16 on AI Accelerators. - Zhen Xie; Siddhisanket Raskar; Murali Emani; Venkatram Vishwanath (Euro-Par, 2023)

Codelet Pipe: Realization of Dataflow Software Pipelining for Extended Codelet Model. - Siddhisanket Raskar; Thomas Applencourt; Kalyan Kumaran; Guang R. Gao (ICPP Workshops, 2023)

Towards Maximum Throughput of Dataflow Software Pipeline under Resource Constraints. - Siddhisanket Raskar; Thomas Applencourt; Kalyan Kumaran; Guang Gao 001 (PMAM@PPoPP, 2023)

Transfer Learning Across Heterogeneous Features For Efficient Tensor Program Generation. - Gaurav Verma; Siddhisanket Raskar; Zhen Xie; Abid M. Malik; Murali Emani; Barbara M. Chapman (ExHET@PPoPP, 2023)

Characterizing the Performance of Triangle Counting on Graphcore's IPU Architecture. - Reet Barik; Siddhisanket Raskar; Murali Emani; Venkatram Vishwanath (SC Workshops, 2023)

Implementation of Dataflow Software Pipelining for Codelet Model. - Siddhisanket Raskar; Jose Manuel Monsalve Diaz; Thomas Applencourt; Kalyan Kumaran; Guang Gao 001 (ICPE, 2023)

A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators. - Murali Emani; Sam Foreman; Varuni Sastry; Zhen Xie; Siddhisanket Raskar; William Arnold; Rajeev Thakur; Venkatram Vishwanath; Michael E. Papka (CoRR, 2023)

Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators. - 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; et al. (IPDPS (Workshops), 2024)

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators. - Krishna Teja Chitty-Venkata; Siddhisanket Raskar; Bharat Kale; Farah Ferdaus; Aditya Tanikanti; Ken Raffenetti; Valerie Taylor 001; Murali Emani; Venkatram Vishwanath (SC Workshops, 2024)

Thorough Characterization and Analysis of Large Transformer Model Training At-Scale. - Scott Cheng; Jun-Liang Lin; Murali Emani; Siddhisanket Raskar; Sam Foreman; Zhen Xie; Venkatram Vishwanath; Mahmut Taylan Kandemir (Proc. ACM Meas. Anal. Comput. Syst., 2024)