Prasanth Chatarasi

According to our database, Prasanth Chatarasi authored at least 16 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

14.1 A Software-Assisted Peak Current Regulation Scheme to Improve Power-Limited Inference Performance in a 5nm AI SoC.

Monodeep Kar, Joel Silberman, Swagath Venkataramani, Viji Srinivasan, Bruce M. Fleischer, Joshua Rubin, JohnDavid Lancaster, Sae Kyu Lee, Matthew Cohen, Matthew M. Ziegler, Nianzheng Cao, Sandra Woodward, Ankur Agrawal, Ching Zhou, Prasanth Chatarasi, Thomas Gooding, Michael Guillorn, Bahman Hekmatshoartabari, Philip Jacob, Radhika Jain, Shubham Jain, Jinwook Jung, Kyu-Hyoun Kim, Siyu Koswatta, Martin Lutz, Alberto Mannari, Abey Mathew, Indira Nair, Ashish Ranjan, Zhibin Ren, Scot Rider, Thomas Roewer, David L. Satterfield, Marcel Schaal, Sanchari Sen, Gustavo Tellez, Hung Tran, Wei Wang, Vidhi Zalani, Jintao Zhang, Xin Zhang, Vinay Shah, Robert M. Senger, Arvind Kumar, Pong-Fei Lu, Leland Chang

Proceedings of the IEEE International Solid-State Circuits Conference, 2024

FEATHER: A Reconfigurable Accelerator with Data Reordering Support for Low-Cost On-Chip Dataflow Switching.

Jianming Tong, Anirudh Itagi, Prasanth Chatarasi, Tushar Krishna

Proceedings of the 51st ACM/IEEE Annual International Symposium on Computer Architecture, 2024

2022

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication.

Gordon Euhyun Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna

IEEE Trans. Parallel Distributed Syst., 2022

Marvel: A Data-Centric Approach for Mapping Deep Learning Operators on Spatial Accelerators.

Prasanth Chatarasi, Hyoukjun Kwon, Angshuman Parashar, Michael Pellauer, Tushar Krishna, Vivek Sarkar

ACM Trans. Archit. Code Optim., 2022

2021

Advancing Compiler Optimizations for General-Purpose & Domain-Specific Parallel Architectures.

Prasanth Chatarasi

PhD thesis, 2021

Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators.

Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi, Angshuman Parashar, Po-An Tsai, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna

Proceedings of the 30th International Conference on Parallel Architectures and Compilation Techniques, 2021

2020

MAESTRO: A Data-Centric Approach to Understand Reuse, Performance, and Hardware Cost of DNN Mappings.

Hyoukjun Kwon, Prasanth Chatarasi, Vivek Sarkar, Tushar Krishna, Michael Pellauer, Angshuman Parashar

IEEE Micro, 2020

MARVEL: A Decoupled Model-driven Approach for Efficiently Mapping Convolutions on Spatial DNN Accelerators.

Prasanth Chatarasi, Hyoukjun Kwon, Natesh Raina, Saurabh Malik, Vaisakh Haridas, Tushar Krishna, Vivek Sarkar

CoRR, 2020

Vyasa: A High-Performance Vectorizing Compiler for Tensor Convolutions on the Xilinx AI Engine.

Prasanth Chatarasi, Stephen Neuendorffer, Samuel Bayliss, Kees A. Vissers, Vivek Sarkar

Proceedings of the 2020 IEEE High Performance Extreme Computing Conference, 2020

2019

Understanding Reuse, Performance, and Hardware Cost of DNN Dataflow: A Data-Centric Approach.

Hyoukjun Kwon, Prasanth Chatarasi, Michael Pellauer, Angshuman Parashar, Vivek Sarkar, Tushar Krishna

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019

Experimental Insights from the Rogues Gallery.

Jeffrey S. Young, E. Jason Riedy, Thomas M. Conte, Vivek Sarkar, Prasanth Chatarasi, Sriseshan Srikanth

Proceedings of the 2019 IEEE International Conference on Rebooting Computing, 2019

2018

A Preliminary Study of Compiler Transformations for Graph Applications on the Emu System.

Prasanth Chatarasi, Vivek Sarkar

Proceedings of the Workshop on Memory Centric High Performance Computing, 2018

A Unified Approach to Variable Renaming for Enhanced Vectorization.

Prasanth Chatarasi, Jun Shirako, Albert Cohen, Vivek Sarkar

Proceedings of the Languages and Compilers for Parallel Computing, 2018

2016

An Extended Polyhedral Model for SPMD Programs and Its Use in Static Data Race Detection.

Prasanth Chatarasi, Jun Shirako, Martin Kong, Vivek Sarkar

Proceedings of the Languages and Compilers for Parallel Computing, 2016

2015

Polyhedral Optimizations of Explicitly Parallel Programs.

Prasanth Chatarasi, Jun Shirako, Vivek Sarkar

Proceedings of the 2015 International Conference on Parallel Architectures and Compilation, 2015

Extending Polyhedral Model for Analysis and Transformation of OpenMP Programs.

Prasanth Chatarasi, Vivek Sarkar

Proceedings of the 2015 International Conference on Parallel Architectures and Compilation, 2015