Mikhail Smelyanskiy
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On large-batch training for deep learning: Generalization gap and sharp minima
NS Keskar, D Mudigere, J Nocedal, M Smelyanskiy, PTP Tang
arXiv preprint arXiv:1609.04836, 2016
13832016
Debunking the 100X GPU vs. CPU myth: an evaluation of throughput computing on CPU and GPU
VW Lee, C Kim, J Chhugani, M Deisher, D Kim, AD Nguyen, N Satish, ...
Proceedings of the 37th annual international symposium on Computer …, 2010
10892010
Proving program termination
B Cook, A Podelski, A Rybalchenko
Communications of the ACM 54 (5), 88-98, 2011
306*2011
Applied machine learning at facebook: A datacenter infrastructure perspective
K Hazelwood, S Bird, D Brooks, S Chintala, U Diril, D Dzhulgakov, ...
2018 IEEE International Symposium on High Performance Computer Architecture …, 2018
2982018
Efficient sparse matrix-vector multiplication on x86-based many-core processors
X Liu, M Smelyanskiy, E Chow, P Dubey
Proceedings of the 27th international ACM conference on International …, 2013
2572013
Design and implementation of the linpack benchmark for single and multi-node systems based on intel® xeon phi coprocessor
A Heinecke, K Vaidyanathan, M Smelyanskiy, A Kobotov, R Dubtsov, ...
2013 IEEE 27th International Symposium on Parallel and Distributed …, 2013
1942013
Exploring simd for molecular dynamics, using intel® xeon® processors and intel® xeon phi coprocessors
SJ Pennycook, CJ Hughes, M Smelyanskiy, SA Jarvis
2013 IEEE 27th International Symposium on Parallel and Distributed …, 2013
1852013
Convergence of recognition, mining, and synthesis workloads and its implications
YK Chen, J Chhugani, P Dubey, CJ Hughes, D Kim, S Kumar, VW Lee, ...
Proceedings of the IEEE 96 (5), 790-807, 2008
1382008
Can traditional programming bridge the ninja performance gap for parallel computing applications?
N Satish, C Kim, J Chhugani, H Saito, R Krishnaiyer, M Smelyanskiy, ...
2012 39th Annual International Symposium on Computer Architecture (ISCA …, 2012
1362012
Glow: Graph lowering compiler techniques for neural networks
N Rotem, J Fix, S Abdulrasool, G Catron, S Deng, R Dzhabarov, N Gibson, ...
arXiv preprint arXiv:1805.00907, 2018
1332018
Anatomy of high-performance many-threaded matrix multiplication
TM Smith, R Van De Geijn, M Smelyanskiy, JR Hammond, FG Van Zee
2014 IEEE 28th International Parallel and Distributed Processing Symposium …, 2014
1122014
Petascale high order dynamic rupture earthquake simulations on heterogeneous supercomputers
A Heinecke, A Breuer, S Rettenberger, M Bader, AA Gabriel, C Pelties, ...
SC'14: Proceedings of the International Conference for High Performance …, 2014
1082014
Mapping high-fidelity volume rendering for medical imaging to CPU, GPU and many-core architectures
M Smelyanskiy, D Holmes, J Chhugani, A Larson, DM Carmean, ...
IEEE transactions on visualization and computer graphics 15 (6), 1563-1570, 2009
1032009
Deep learning recommendation model for personalization and recommendation systems
M Naumov, D Mudigere, HJM Shi, J Huang, N Sundaraman, J Park, ...
arXiv preprint arXiv:1906.00091, 2019
1002019
Vector instructions to enable efficient synchronization and parallel reduction operations
M Smelyanskiy, S Kumar, D Kim, J Chhugani, C Kim, CJ Hughes, VW Lee, ...
US Patent 9,513,905, 2016
962016
The BLIS framework: Experiments in portability
FGV Zee, TM Smith, B Marker, TM Low, RAVD Geijn, FD Igual, ...
ACM Transactions on Mathematical Software (TOMS) 42 (2), 1-19, 2016
862016
Optimization of geometric multigrid for emerging multi-and manycore processors
S Williams, DD Kalamkar, A Singh, AM Deshpande, B Van Straalen, ...
SC'12: Proceedings of the International Conference on High Performance …, 2012
832012
Deep learning inference in facebook data centers: Characterization, performance optimizations and hardware implications
J Park, M Naumov, P Basu, S Deng, A Kalaiah, D Khudia, J Law, P Malani, ...
arXiv preprint arXiv:1811.09886, 2018
742018
qHiPSTER: The quantum high performance software testing environment
M Smelyanskiy, NPD Sawaya, A Aspuru-Guzik
arXiv preprint arXiv:1601.07195, 2016
742016
Practical optimization for hybrid quantum-classical algorithms
GG Guerreschi, M Smelyanskiy
arXiv preprint arXiv:1701.01450, 2017
712017
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