Spremljaj
Bharat Kaul
Bharat Kaul
Intel Labs
Preverjeni e-poštni naslov na intel.com - Domača stran
Naslov
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Leto
Sigma: A sparse and irregular gemm accelerator with flexible interconnects for dnn training
E Qin, A Samajdar, H Kwon, V Nadella, S Srinivasan, D Das, B Kaul, ...
2020 IEEE International Symposium on High Performance Computer Architecture …, 2020
5032020
A study of BFLOAT16 for deep learning training
D Kalamkar, D Mudigere, N Mellempudi, D Das, K Banerjee, S Avancha, ...
arXiv preprint arXiv:1905.12322, 2019
3892019
Out-of-distribution detection using an ensemble of self supervised leave-out classifiers
A Vyas, N Jammalamadaka, X Zhu, D Das, B Kaul, TL Willke
Proceedings of the European conference on computer vision (ECCV), 550-564, 2018
2992018
Scaledeep: A scalable compute architecture for learning and evaluating deep networks
S Venkataramani, A Ranjan, S Banerjee, D Das, S Avancha, ...
Proceedings of the 44th Annual International Symposium on Computer …, 2017
2802017
Mixed precision training of convolutional neural networks using integer operations
D Das, N Mellempudi, D Mudigere, D Kalamkar, S Avancha, K Banerjee, ...
arXiv preprint arXiv:1802.00930, 2018
2192018
Distributed deep learning using synchronous stochastic gradient descent
D Das, S Avancha, D Mudigere, K Vaidynathan, S Sridharan, D Kalamkar, ...
arXiv preprint arXiv:1602.06709, 2016
2152016
Method and apparatus to manage network addresses
B Kaul, N Tulpule, M Zhu, P Krishnaswamy
US Patent App. 10/651,929, 2005
2042005
Ternary neural networks with fine-grained quantization
N Mellempudi, A Kundu, D Mudigere, D Das, B Kaul, P Dubey
arXiv preprint arXiv:1705.01462, 2017
1392017
Mixed precision training with 8-bit floating point
N Mellempudi, S Srinivasan, D Das, B Kaul
arXiv preprint arXiv:1905.12334, 2019
812019
Apparatuses, methods, and systems for neural networks
S Venkataramani, D Das, A Ranjan, S Banerjee, S Avancha, ...
US Patent App. 16/317,497, 2019
642019
Data structure and movement for lattice-based simulations
AG Shet, SH Sorathiya, S Krithivasan, AM Deshpande, B Kaul, ...
Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 88 (1 …, 2013
552013
X-mann: A crossbar based architecture for memory augmented neural networks
A Ranjan, S Jain, JR Stevens, D Das, B Kaul, A Raghunathan
Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019
482019
AI Powered Compiler Techniques for DL Code Optimization
S Tavarageri, G Goyal, S Avancha, B Kaul, R Upadrasta
arXiv preprint arXiv:2104.05573, 2021
462021
Madras: Multi agent driving simulator
A Santara, S Rudra, SA Buridi, M Kaushik, A Naik, B Kaul, B Ravindran
Journal of Artificial Intelligence Research 70, 1517-1555, 2021
362021
On scale-out deep learning training for cloud and hpc
S Sridharan, K Vaidyanathan, D Kalamkar, D Das, ME Smorkalov, ...
arXiv preprint arXiv:1801.08030, 2018
342018
Mixed low-precision deep learning inference using dynamic fixed point
N Mellempudi, A Kundu, D Das, D Mudigere, B Kaul
arXiv preprint arXiv:1701.08978, 2017
332017
Manna: An accelerator for memory-augmented neural networks
JR Stevens, A Ranjan, D Das, B Kaul, A Raghunathan
Proceedings of the 52nd Annual IEEE/ACM international symposium on …, 2019
322019
Polydl: Polyhedral optimizations for creation of high-performance dl primitives
S Tavarageri, A Heinecke, S Avancha, B Kaul, G Goyal, R Upadrasta
ACM Transactions on Architecture and Code Optimization (TACO) 18 (1), 1-27, 2021
302021
Rail: Risk-averse imitation learning
A Santara, A Naik, B Ravindran, D Das, D Mudigere, S Avancha, B Kaul
arXiv preprint arXiv:1707.06658, 2017
262017
GNNerator: A hardware/software framework for accelerating graph neural networks
JR Stevens, D Das, S Avancha, B Kaul, A Raghunathan
2021 58th ACM/IEEE Design Automation Conference (DAC), 955-960, 2021
232021
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