Követés
Eriko Nurvitadhi
Eriko Nurvitadhi
MangoBoost
E-mail megerősítve itt: mangoboost.io - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Can FPGAs beat GPUs in accelerating next-generation deep neural networks?
E Nurvitadhi, G Venkatesh, J Sim, D Marr, R Huang, J Ong Gee Hock, ...
Proceedings of the 2017 ACM/SIGDA international symposium on field …, 2017
5832017
Accelerating binarized neural networks: Comparison of FPGA, CPU, GPU, and ASIC
E Nurvitadhi, D Sheffield, J Sim, A Mishra, G Venkatesh, D Marr
2016 International Conference on Field-Programmable Technology (FPT), 77-84, 2016
4002016
WRPN: Wide reduced-precision networks
A Mishra, E Nurvitadhi, JJ Cook, D Marr
arXiv preprint arXiv:1709.01134, 2017
3592017
Accelerating recurrent neural networks in analytics servers: Comparison of FPGA, CPU, GPU, and ASIC
E Nurvitadhi, J Sim, D Sheffield, A Mishra, S Krishnan, D Marr
2016 26th International Conference on Field Programmable Logic and …, 2016
2372016
Accelerating deep convolutional networks using low-precision and sparsity
G Venkatesh, E Nurvitadhi, D Marr
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
1662017
GraphGen: An FPGA framework for vertex-centric graph computation
E Nurvitadhi, G Weisz, Y Wang, S Hurkat, M Nguyen, JC Hoe, JF Martínez, ...
2014 IEEE 22nd Annual International Symposium on Field-Programmable Custom …, 2014
1602014
Programmable coarse grained and sparse matrix compute hardware with advanced scheduling
E Nurvitadhi, B Vembu, NCG Von Borries, R Barik, TH Lin, K Sinha, ...
US Patent 10,186,011, 2019
1222019
ProtoFlex: Towards scalable, full-system multiprocessor simulations using FPGAs
ES Chung, MK Papamichael, E Nurvitadhi, JC Hoe, K Mai, B Falsafi
ACM Transactions on Reconfigurable Technology and Systems (TRETS) 2 (2), 1-32, 2009
1192009
A customizable matrix multiplication framework for the intel harpv2 xeon+ fpga platform: A deep learning case study
DJM Moss, S Krishnan, E Nurvitadhi, P Ratuszniak, C Johnson, J Sim, ...
Proceedings of the 2018 ACM/SIGDA International Symposium on Field …, 2018
1022018
High performance binary neural networks on the Xeon+ FPGA™ platform
DJM Moss, E Nurvitadhi, J Sim, A Mishra, D Marr, S Subhaschandra, ...
2017 27Th International conference on field programmable logic and …, 2017
942017
Machine learning accelerator mechanism
A Bleiweiss, A Ramesh, A Mishra, D Marr, J Cook, S Sridharan, ...
US Patent 11,373,088, 2022
922022
Compute optimizations for neural networks
K Nealis, A Yao, X Chen, E Ould-Ahmed-Vall, SS Baghsorkhi, ...
US Patent 10,410,098, 2019
902019
Exploration of low numeric precision deep learning inference using intel® fpgas
P Colangelo, N Nasiri, E Nurvitadhi, A Mishra, M Margala, K Nealis
2018 IEEE 26th annual international symposium on field-programmable custom …, 2018
862018
Beyond peak performance: Comparing the real performance of AI-optimized FPGAs and GPUs
A Boutros, E Nurvitadhi, R Ma, S Gribok, Z Zhao, JC Hoe, V Betz, ...
2020 international conference on field-programmable technology (ICFPT), 10-19, 2020
762020
Machine learning sparse computation mechanism
E Nurvitadhi, B Vembu, TH Lin, K Sinha, R Barik, NCG Von Borries
US Patent 10,346,944, 2019
742019
A complexity-effective architecture for accelerating full-system multiprocessor simulations using FPGAs
ES Chung, E Nurvitadhi, JC Hoe, B Falsafi, K Mai
Proceedings of the 16th international ACM/SIGDA symposium on Field …, 2008
712008
Specialized fixed function hardware for efficient convolution
R Barik, E Ould-Ahmed-Vall, X Chen, D Srivastava, A Yao, K Nealis, ...
US Patent 10,824,938, 2020
682020
Why compete when you can work together: FPGA-ASIC integration for persistent RNNs
E Nurvitadhi, D Kwon, A Jafari, A Boutros, J Sim, P Tomson, H Sumbul, ...
2019 IEEE 27th Annual International Symposium on Field-Programmable Custom …, 2019
682019
Hardware accelerator architecture and template for web-scale k-means clustering
E Nurvitadhi, G Venkatesh, S Krishnan, S Subhaschandra, D Marr
US Patent App. 15/396,515, 2018
652018
Machine learning sparse computation mechanism for arbitrary neural networks, arithmetic compute microarchitecture, and sparsity for training mechanism
E Nurvitadhi, A Bleiweiss, D Marr, E Wang, S Dwarakapuram, ...
US Patent 11,636,327, 2023
612023
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