|From high-level deep neural models to FPGAs|
H Sharma, J Park, D Mahajan, E Amaro, JK Kim, C Shao, A Mishra, ...
2016 49th Annual IEEE/ACM International Symposium on Microarchitecture …, 2016
|Bit fusion: Bit-level dynamically composable architecture for accelerating deep neural network|
H Sharma, J Park, N Suda, L Lai, B Chau, V Chandra, H Esmaeilzadeh
2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture …, 2018
|Tabla: A unified template-based framework for accelerating statistical machine learning|
D Mahajan, J Park, E Amaro, H Sharma, A Yazdanbakhsh, JK Kim, ...
2016 IEEE International Symposium on High Performance Computer Architecture …, 2016
|Neural acceleration for gpu throughput processors|
A Yazdanbakhsh, J Park, H Sharma, P Lotfi-Kamran, H Esmaeilzadeh
Proceedings of the 48th International Symposium on Microarchitecture, 482-493, 2015
|Dnnweaver: From high-level deep network models to fpga acceleration|
H Sharma, J Park, E Amaro, B Thwaites, P Kotha, A Gupta, JK Kim, ...
the Workshop on Cognitive Architectures, 2016
|Scale-out acceleration for machine learning|
J Park, H Sharma, D Mahajan, JK Kim, P Olds, H Esmaeilzadeh
Proceedings of the 50th Annual IEEE/ACM International Symposium on …, 2017
|Bit-Parallel Vector Composability for Neural Acceleration|
S Ghodrati, H Sharma, C Young, NS Kim, H Esmaeilzadeh
arXiv preprint arXiv:2004.05333, 2020
|Processing artificial neural network weights|
AE Chalfin, H Sharma, TJ Olson
US Patent 10,599,935, 2020
|Mixed-signal charge-domain acceleration of deep neural networks through interleaved bit-partitioned arithmetic|
S Ghodrati, H Sharma, S Kinzer, A Yazdanbakhsh, J Park, NS Kim, ...
Proceedings of the ACM International Conference on Parallel Architectures …, 2020
|The impact of 3D stacking on GPU-accelerated deep neural networks: An experimental study|
W Wahby, T Sarvey, H Sharma, H Esmaeilzadeh, MS Bakir
2016 IEEE International 3D Systems Integration Conference (3DIC), 1-4, 2016
|Accelerated deep learning for the edge-to-cloud continuum: A specialized full stack derived from algorithms|
Georgia Institute of Technology, 2019
|Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks|
S Ghodrati, BH Ahn, JK Kim, S Kinzer, BR Yatham, N Alla, H Sharma, ...
2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture …, 2020
|Systems, apparatus, methods, and architecture for precision heterogeneity in accelerating neural networks for inference and training|
H Sharma, J Park
US Patent App. 16/744,037, 2020
|Systems, apparatus, methods, and architectures for heterogeneous precision acceleration of quantized neural networks|
H Sharma, J Park
US Patent App. 16/744,039, 2020
|Systems, apparatus, methods, and architectures for a neural network workflow to generate a hardware acceletator|
H Sharma, J Park
US Patent App. 16/744,040, 2020
|Selecting encoding options|
S Pratapa, H Sharma, TJ Olson, AE Chalfin
US Patent 10,559,093, 2020
|From Tensors to FPGAs: Accelerating Deep Learning|
H Sharma, J Park, B Samynathan, B Robatmili, S Mirkhani, ...
Hot Chips: A Symposium on High Performance Chips, 2018
|Approximate Computing and Microfluidic Cooling for Enhanced Machine Learning|
H Sharma, W Wahby, T Sarvey, MS Bakir, H Esmailzadeh
Workshop on Approximate Computing Across the System Stack (WAX), 2016
|Gamma-ray Spectroscopy of Spontaneous Ternary Fission of 252 Cf|
YN Kopatch, M Mutterer, P Jesinger, J Von Kalben, I Kojouharov, ...
|TABLA: A Unified Template-based Framework for Accelerating Statistical Machine Learning|
DMJPE Amaro, H Sharma, AYJK Kim, H Esmaeilzadeh