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ORCIDMichael Andersch
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- affiliation: Technical University of Berlin, Department of Mathematics, Germany
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Journal Articles
- 2015
[j1]Jan Lucas, Michael Andersch, Mauricio Alvarez-Mesa, Ben H. H. Juurlink:
Spatiotemporal SIMT and Scalarization for Improving GPU Efficiency. ACM Trans. Archit. Code Optim. 12(3): 32:1-32:26 (2015)
Conference and Workshop Papers
- 2023
- [c8]Feiwen Zhu
, Michal Futrega, Han Bao, Sukru Burc Eryilmaz, Fei Kong, Kefeng Duan, Xinnian Zheng, Nimrod Angel, Matthias Jouanneaux, Maxmilian Stadler, Michal Marcinkiewicz, Fung Xie, June Yang, Michael Andersch:
FastDimeNet++: Training DimeNet++ in 22 minutes. ICPP 2023: 274-284 - [c7]Vijay Anand Korthikanti, Jared Casper, Sangkug Lym, Lawrence McAfee, Michael Andersch, Mohammad Shoeybi, Bryan Catanzaro:
Reducing Activation Recomputation in Large Transformer Models. MLSys 2023 - 2018
- [c6]Feiwen Zhu, Jeff Pool, Michael Andersch, Jeremy Appleyard, Fung Xie:
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip. ICLR (Poster) 2018 - 2015
- [c5]Michael Andersch, Jan Lucas, Mauricio Alvarez-Mesa, Ben H. H. Juurlink:
On latency in GPU throughput microarchitectures. ISPASS 2015: 169-170 - 2014
- [c4]Sohan Lal, Jan Lucas, Michael Andersch, Mauricio Alvarez-Mesa, Ahmed Elhossini, Ben H. H. Juurlink:
GPGPU workload characteristics and performance analysis. ICSAMOS 2014: 115-124 - 2013
- [c3]Jan Lucas, Sohan Lal, Michael Andersch, Mauricio Alvarez-Mesa, Ben H. H. Juurlink:
How a single chip causes massive power bills GPUSimPow: A GPGPU power simulator. ISPASS 2013: 97-106 - 2012
- [c2]Michael Andersch, Chi Ching Chi, Ben H. H. Juurlink:
Programming parallel embedded and consumer applications in OpenMP superscalar. PPoPP 2012: 281-282 - [c1]Michael Andersch, Chi Ching Chi, Ben H. H. Juurlink:
Using OpenMP superscalar for parallelization of embedded and consumer applications. ICSAMOS 2012: 23-32
Informal and Other Publications
- 2024
- [i3]Feiwen Zhu, Arkadiusz Nowaczynski, Rundong Li, Jie Xin, Yifei Song, Michal Marcinkiewicz, Sukru Burc Eryilmaz, Jun Yang, Michael Andersch:
ScaleFold: Reducing AlphaFold Initial Training Time to 10 Hours. CoRR abs/2404.11068 (2024) - 2022
- [i2]Vijay Korthikanti, Jared Casper, Sangkug Lym, Lawrence McAfee, Michael Andersch, Mohammad Shoeybi, Bryan Catanzaro:
Reducing Activation Recomputation in Large Transformer Models. CoRR abs/2205.05198 (2022) - 2018
- [i1]Feiwen Zhu, Jeff Pool, Michael Andersch, Jeremy Appleyard, Fung Xie:
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip. CoRR abs/1804.10223 (2018)
Coauthor Index
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