Jiecao Yu

According to our database, Jiecao Yu authored at least 16 papers between 2017 and 2026.

Collaborative distances:

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

2026

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale.

Liang Luo, Yinbin Ma, Quanyu Zhu, Vasiliy Kuznetsov, Yuxin Chen, Jian Jiao, Jiecao Yu, Buyun Zhang, Tongyi Tang, Xiaohan Wei, Yanli Zhao, Zeliang Chen, Yuchen Hao, Venkatesh Ranganathan, Sandeep Parab, Yantao Yao, Maxim Naumov, Chunzhi Yang, Shen Li, Ellie Wen, Wenlin Chen, Santanu Kolay, Chunqiang Tang

CoRR, May, 2026

Scaling Multi-Node Mixture-of-Experts Inference Using Expert Activation Patterns.

Abhimanyu Bambhaniya, Geonhwa Jeong, Jason Park, Jiecao Yu, Jaewon Lee, Pengchao Wang, Changkyu Kim, Chunqiang Tang, Tushar Krishna

CoRR, April, 2026

Unveiling the Potential of Quantization with MXFP4: Strategies for Quantization Error Reduction.

Jatin Chhugani, Geonhwa Jeong, Bor-Yiing Su, Yunjie Pan, Hanmei Yang, Aayush Ankit, Jiecao Yu, Summer Deng, Yunqing Chen, Nadathur Satish, Changkyu Kim

CoRR, March, 2026

2025

Fast and Simplex: 2-Simplicial Attention in Triton.

Aurko Roy, Timothy Chou, Sai Surya Duvvuri, Sijia Chen, Jiecao Yu, Xiaodong Wang, Manzil Zaheer, Rohan Anil

CoRR, July, 2025

Accelerating Transformer Inference and Training with 2:4 Activation Sparsity.

Daniel Haziza, Timothy Chou, Dhruv Choudhary, Luca Wehrstedt, Francisco Massa, Jiecao Yu, Geonhwa Jeong, Supriya Rao, Patrick Labatut, Jesse Cai

CoRR, March, 2025

Scaling Llama 3 Training with Efficient Parallelism Strategies.

Weiwei Chu, Xinfeng Xie, Jiecao Yu, Jie Wang, Amar Phanishayee, Chunqiang Tang, Yuchen Hao, Jianyu Huang, Mustafa Ozdal, Jun Wang, Vedanuj Goswami, Naman Goyal, Abhishek Kadian, Andrew Gu, Chris Cai, Feng Tian, Xiaodong Wang, Min Si, Pavan Balaji, Ching-Hsiang Chu, Jongsoo Park

Proceedings of the 52nd Annual International Symposium on Computer Architecture, 2025

2023

BitSET: Bit-Serial Early Termination for Computation Reduction in Convolutional Neural Networks.

Yunjie Pan, Jiecao Yu, Andrew Lukefahr, Reetuparna Das, Scott A. Mahlke

ACM Trans. Embed. Comput. Syst., October, 2023

2021

First-Generation Inference Accelerator Deployment at Facebook.

Michael J. Anderson, Benny Chen, Stephen Chen, Summer Deng, Jordan Fix, Michael Gschwind, Aravind Kalaiah, Changkyu Kim, Jaewon Lee, Jason Liang, Haixin Liu, Yinghai Lu, Jack Montgomery, Arun Moorthy, Nadathur Satish, Sam Naghshineh, Avinash Nayak, Jongsoo Park, Chris Petersen, Martin Schatz, Narayanan Sundaram, Bangsheng Tang, Peter Tang, Amy Yang, Jiecao Yu, Hector Yuen, Ying Zhang, Aravind Anbudurai, Vandana Balan, Harsha Bojja, Joe Boyd, Matthew Breitbach, Claudio Caldato, Anna Calvo, Garret Catron, Sneh Chandwani, Panos Christeas, Brad Cottel, Brian Coutinho, Arun Dalli, Abhishek Dhanotia, Oniel Duncan, Roman Dzhabarov, Simon Elmir, Chunli Fu, Wenyin Fu, Michael Fulthorp, Adi Gangidi, Nick Gibson, Sean Gordon, Beatriz Padilla Hernandez, Daniel Ho, Yu-Cheng Huang, Olof Johansson, Shishir Juluri, et al.

CoRR, 2021

Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems.

Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Compute-Capable Block RAMs for Efficient Deep Learning Acceleration on FPGAs.

Xiaowei Wang, Vidushi Goyal, Jiecao Yu, Valeria Bertacco, Andrew Boutros, Eriko Nurvitadhi, Charles Augustine, Ravi R. Iyer, Reetuparna Das

Proceedings of the 29th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2021

2020

Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data.

Mao Ye, Dhruv Choudhary, Jiecao Yu, Ellie Wen, Zeliang Chen, Jiyan Yang, Jongsoo Park, Qiang Liu, Arun Kejariwal

CoRR, 2020

2019

Efficient Deep Neural Network Computation on Processors.

Jiecao Yu

PhD thesis, 2019

TF-Net: Deploying Sub-Byte Deep Neural Networks on Microcontrollers.

Jiecao Yu, Andrew Lukefahr, Reetuparna Das, Scott A. Mahlke

ACM Trans. Embed. Comput. Syst., 2019

Spatial-Winograd Pruning Enabling Sparse Winograd Convolution.

Jiecao Yu, Jongsoo Park, Maxim Naumov

CoRR, 2019

Bit Prudent In-Cache Acceleration of Deep Convolutional Neural Networks.

Xiaowei Wang, Jiecao Yu, Charles Augustine, Ravi R. Iyer, Reetuparna Das

Proceedings of the 25th IEEE International Symposium on High Performance Computer Architecture, 2019

2017

Scalpel: Customizing DNN Pruning to the Underlying Hardware Parallelism.

Jiecao Yu, Andrew Lukefahr, David J. Palframan, Ganesh S. Dasika, Reetuparna Das, Scott A. Mahlke

Proceedings of the 44th Annual International Symposium on Computer Architecture, 2017