Chakra: Advancing Performance Benchmarking and Co-design using
Standardized Execution Traces

Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces

23 May 2023

Srinivas Sridharan

Louis Feng

Papers citing "Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces"

8 / 8 papers shown

Title
Towards Easy and Realistic Network Infrastructure Testing for Large-scale Machine Learning Jinsun Yoo ChonLam Lao Lianjie Cao Bob Lantz Minlan Yu Tushar Krishna Puneet Sharma 52 0 0 29 Apr 2025
LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation Mufei Li Viraj Shitole Eli Chien Changhai Man Zhaodong Wang Srinivas Sridharan Ying Zhang Tushar Krishna P. Li 37 0 0 04 Nov 2024
Towards a Standardized Representation for Deep Learning Collective Algorithms Jinsun Yoo William Won Meghan Cowan Nan Jiang Benjamin Klenk Srinivas Sridharan Tushar Krishna 26 1 0 20 Aug 2024
LLMServingSim: A HW/SW Co-Simulation Infrastructure for LLM Inference Serving at Scale Jaehong Cho Minsu Kim Hyunmin Choi Guseul Heo Jongse Park 38 9 0 10 Aug 2024
Towards Universal Performance Modeling for Machine Learning Training on Multi-GPU Platforms Zhongyi Lin Ning Sun Pallab Bhattacharya Xizhou Feng Louis Feng John Douglas Owens 42 1 0 19 Apr 2024
MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems Samuel Hsia Alicia Golden Bilge Acun Newsha Ardalani Zach DeVito Gu-Yeon Wei David Brooks Carole-Jean Wu MoE 50 9 0 04 Oct 2023
Proteus: Simulating the Performance of Distributed DNN Training Jiangfei Duan Xiuhong Li Ping Xu Xingcheng Zhang Shengen Yan Yun Liang Dahua Lin 79 10 0 04 Jun 2023
ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale William Won Taekyung Heo Saeed Rashidi Srinivas Sridharan Sudarshan Srinivasan T. Krishna 36 43 0 24 Mar 2023