Michael Andersch

15 papers A* 1B 4Journal 6Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Scalable Training of Mixture-of-Experts Models with Megatron Core.
CoRR
Zijie Yan, Hongxiao Bai, Xin Yao, Dennis Liu, Tong Liu, Hongbin Liu, Pingtian Li, Evan Wu, Shiqing Fan, Li Tao, Robin Zhang, Yuzhong Wang, Shifang Xu, Jack Chang, Xuwen Chen, Kunlun Li, Yan Bai, Gao Deng, Nan Zheng, Vijay Anand Korthikanti, Abhinav Khattar, Ethan He, Soham Govande, Sangkug Lym, Zhongbo Zhu, Qi Zhang, Haochen Yuan, Xiaowei Ren, Deyu Fu, Tailai Ma, Shunkang Zhang, Jiang Shao, Ray Wang, Vasudevan Rengasamy, Rachit Garg, Santosh Bhavani, Xipeng Li, Chandler Zhou, David Wu, Yingcan Wei, Ashwath Aithal, Michael Andersch, Mohammad Shoeybi, Jiajie Yao, June Yang
2025 J jnl
MoE Parallel Folding: Heterogeneous Parallelism Mappings for Efficient Large-Scale MoE Model Training with Megatron Core.
CoRR
Dennis Liu, Zijie Yan, Xin Yao, Tong Liu, Vijay Korthikanti, Evan Wu, Shiqing Fan, Gao Deng, Hongxiao Bai, Jianbin Chang, Ashwath Aithal, Michael Andersch, Mohammad Shoeybi, Jiajie Yao, Chandler Zhou, David Wu, Xipeng Li, June Yang
2024 A* conf
ScaleFold: Reducing AlphaFold Initial Training Time to 10 Hours.
DAC
Feiwen Zhu, Arkadiusz Nowaczynski, Rundong Li, Jie Xin, Yifei Song, Michal Marcinkiewicz, Sukru Burc Eryilmaz, Jun Yang, Michael Andersch
2024 J jnl
ScaleFold: Reducing AlphaFold Initial Training Time to 10 Hours.
CoRR
Feiwen Zhu, Arkadiusz Nowaczynski, Rundong Li, Jie Xin, Yifei Song, Michal Marcinkiewicz, Sukru Burc Eryilmaz, Jun Yang, Michael Andersch
2023 B conf
FastDimeNet++: Training DimeNet++ in 22 minutes.
ICPP
Feiwen Zhu, Michal Futrega, Han Bao, Sukru Burc Eryilmaz, Fei Kong, Kefeng Duan, Xinnian Zheng, Nimrod Angel, Matthias Jouanneaux, Maximilian Stadler, Michal Marcinkiewicz, Fung Xie, June Yang, Michael Andersch
2023 — conf
Reducing Activation Recomputation in Large Transformer Models.
MLSys
Vijay Anand Korthikanti, Jared Casper, Sangkug Lym, Lawrence McAfee, Michael Andersch, Mohammad Shoeybi, Bryan Catanzaro
2022 J jnl
Reducing Activation Recomputation in Large Transformer Models.
CoRR
Vijay Korthikanti, Jared Casper, Sangkug Lym, Lawrence McAfee, Michael Andersch, Mohammad Shoeybi, Bryan Catanzaro
2018 — conf
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip.
ICLR (Poster)
Feiwen Zhu, Jeff Pool, Michael Andersch, Jeremy Appleyard, Fung Xie
2018 J jnl
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip.
CoRR
Feiwen Zhu, Jeff Pool, Michael Andersch, Jeremy Appleyard, Fung Xie
2015 B conf
On latency in GPU throughput microarchitectures.
ISPASS
Michael Andersch, Jan Lucas, Mauricio Alvarez-Mesa, Ben H. H. Juurlink
2015 J jnl
Spatiotemporal SIMT and Scalarization for Improving GPU Efficiency.
ACM Trans. Archit. Code Optim.
Jan Lucas, Michael Andersch, Mauricio Alvarez-Mesa, Ben H. H. Juurlink
2014 — conf
GPGPU workload characteristics and performance analysis.
ICSAMOS
Sohan Lal, Jan Lucas, Michael Andersch, Mauricio Alvarez-Mesa, Ahmed Elhossini, Ben H. H. Juurlink
2013 B conf
How a single chip causes massive power bills GPUSimPow: A GPGPU power simulator.
ISPASS
Jan Lucas, Sohan Lal, Michael Andersch, Mauricio Alvarez-Mesa, Ben H. H. Juurlink
2012 B conf
Programming parallel embedded and consumer applications in OpenMP superscalar.
PPoPP
Michael Andersch, Chi Ching Chi, Ben H. H. Juurlink
2012 — conf
Using OpenMP superscalar for parallelization of embedded and consumer applications.
ICSAMOS
Michael Andersch, Chi Ching Chi, Ben H. H. Juurlink