Michael Kuchnik
Title
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Cited by
Year
File systems unfit as distributed storage backends: lessons from 10 years of Ceph evolution
A Aghayev, S Weil, M Kuchnik, M Nelson, GR Ganger, G Amvrosiadis
Proceedings of the 27th ACM Symposium on Operating Systems Principles, 353-369, 2019
212019
Efficient Augmentation via Data Subsampling
M Kuchnik, V Smith
International Conference on Learning Representations, 2019
112019
The Case for Custom Storage Backends in Distributed Storage Systems
A Aghayev, S Weil, M Kuchnik, M Nelson, GR Ganger, G Amvrosiadis
ACM Transactions on Storage (TOS) 16 (2), 1-31, 2020
12020
This is why ML-driven cluster scheduling remains widely impractical
M Kuchnik, JW Park, C Cranor, E Moore, N DeBardeleben, G Amvrosiadis
12019
The Atlas Cluster Trace Repository
G Amvrosiadis, M Kuchnik, JW Park, C Cranor, G Ganger R., E Moore, ...
https://www.usenix.org/publications/login/winter-2018-vol-43-no-4/amvrosiadis, 2018
12018
Progressive Compressed Records: Taking a Byte out of Deep Learning Data
M Kuchnik, G Amvrosiadis, V Smith
arXiv preprint arXiv:1911.00472, 2019
2019
SSL Freeform Generator v1. 00
M Kuchnik
2014
File Systems Unfit as Distributed Storage Back Ends
A AGHAYEV, S WEIL, M KUCHNIK, M NELSON, G GANGER, ...
Deep Reinforcement Learning in Continuous Multi Agent Environments
A Li, M Kuchnik, Y Luo, R Sawhney
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