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TBD: Benchmarking and Analyzing Deep Neural Network Training

H. Zhu, M. Akrout, B. Zheng, A. Pelegris, A. Phanishayee, B. Schroeder, and G. Pekhimenko. (2018)cite arxiv:1803.06905.

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Gennady Uryadov

Gennady Samorodnitsky

Gennady Fedosenko

Gennady Tenin

Gennady Churakov

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Efficient Program Compilation Through Machine Learning Techniques.G. Pekhimenko, and A. Brown. Software Automatic Tuning, From Concepts to State-of-the-Art Results, Springer, (2010)Reducing DRAM Latency by Exploiting Design-Induced Latency Variation in Modern DRAM Chips.D. Lee, S. Khan, L. Subramanian, R. Ausavarungnirun, G. Pekhimenko, V. Seshadri, S. Ghose, and O. Mutlu. CoRR, (2016)How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU.S. Tonekaboni, G. Morgenshtern, A. Assadi, A. Pokhrel, X. Huang, A. Jayarajan, R. Greer, G. Pekhimenko, M. McCradden, M. Mazwi and 1 other author(s). CHIL, volume 174 of Proceedings of Machine Learning Research, page 169-182. PMLR, (2022)GPUPool: A Holistic Approach to Fine-Grained GPU Sharing in the Cloud.X. Tan, P. Golikov, N. Vijaykumar, and G. Pekhimenko. PACT, page 317-332. ACM, (2022)Linearly compressed pages: a low-complexity, low-latency main memory compression framework.G. Pekhimenko, V. Seshadri, Y. Kim, H. Xin, O. Mutlu, P. Gibbons, M. Kozuch, and T. Mowry. MICRO, page 172-184. ACM, (2013)Skyline: Interactive In-Editor Computational Performance Profiling for Deep Neural Network Training.G. Yu, T. Grossman, and G. Pekhimenko. UIST, page 126-139. ACM, (2020)Rollback-free value prediction with approximate loads.B. Thwaites, G. Pekhimenko, H. Esmaeilzadeh, A. Yazdanbakhsh, O. Mutlu, J. Park, G. Mururu, and T. Mowry. PACT, page 493-494. ACM, (2014)Page overlays: an enhanced virtual memory framework to enable fine-grained memory management.V. Seshadri, G. Pekhimenko, O. Ruwase, O. Mutlu, P. Gibbons, M. Kozuch, T. Mowry, and T. Chilimbi. ISCA, page 79-91. ACM, (2015)TiLT: A Time-Centric Approach for Stream Query Optimization and Parallelization.A. Jayarajan, W. Zhao, Y. Sun, and G. Pekhimenko. ASPLOS (2), page 818-832. ACM, (2023)Priority-based Parameter Propagation for Distributed DNN Training.A. Jayarajan, J. Wei, G. Gibson, A. Fedorova, and G. Pekhimenko. SysML, mlsys.org, (2019)

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Disambiguation of "Pekhimenko, Gennady"

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TBD: Benchmarking and Analyzing Deep Neural Network Training

Please choose a person to relate this publication to

Gennady Uryadov

Gennady Samorodnitsky

Gennady Fedosenko

Gennady Tenin

Gennady Churakov

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Pekhimenko, Gennady"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML TBD: Benchmarking and Analyzing Deep Neural Network Training

Please choose a person to relate this publication to

Gennady Uryadov

Gennady Samorodnitsky

Gennady Fedosenko

Gennady Tenin

Gennady Churakov

Other publications of authors with the same name

Disambiguation

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community post
history of this post
URL
DOI
BibTeX
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Chicago
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TBD: Benchmarking and Analyzing Deep Neural Network Training