Kamyar Givaki
Cited by
Cited by
Skippynn: An embedded stochastic-computing accelerator for convolutional neural networks
R Hojabr, K Givaki, SMR Tayaranian, P Esfahanian, A Khonsari, ...
2019 56th ACM/IEEE Design Automation Conference (DAC), 1-6, 2019
On the resilience of deep learning for reduced-voltage FPGAs
K Givaki, B Salami, R Hojabr, SMR Tayaranian, A Khonsari, D Rahmati, ...
2020 28th Euromicro International Conference on Parallel, Distributed and …, 2020
Using residue number systems to accelerate deterministic bit-stream multiplication
K Givaki, R Hojabr, MH Najafi, A Khonsari, MH Gholamrezayi, S Gorgin, ...
2019 IEEE 30th International Conference on Application-specific Systems …, 2019
Machine learning based impedance estimation in power system
K Givaki, S Seyedzadeh, K Givaki
IET Digital Library, 2019
Embedded stochastic-computing accelerator architecture and method for convolutional neural networks
M Najafi, SR Hojabrossadati, K Givaki, SMR Tayaranian, P Esfahanian, ...
US Patent App. 17/159,347, 2021
Method and architecture for accelerating deterministic stochastic computing using residue number system
M Najafi, K Givaki, SR Hojabrossadati, MH Gholamrezayi, A Khonsari, ...
US Patent App. 17/166,378, 2021
High-Performance Deterministic Stochastic Computing Using Residue Number System
K Givaki, R Hojabr, MH Gholamrezaei, A Khonsari, S Gorgin, D Rahmati, ...
IEEE Design & Test 38 (6), 60-68, 2021
TaxoNN: A Light-Weight Accelerator for Deep Neural Network Training
R Hojabr, K Givaki, K Pourahmadi, P Nooralinejad, A Khonsari, ...
2020 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2020
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