Ganesh Dasika

Publication Activity (10 Years)

Years Active: 2016-2021
Publications (10 Years): 18

Top Topics

Kronecker Product

Text Compression

Top Venues

EMC2@HPCA/CVPR/ISCA

ACM J. Emerg. Technol. Comput. Syst.

Conf. Computing Frontiers

Publications

Urmish Thakker, Igor Fedorov, Chu Zhou, Dibakar Gope, Matthew Mattina, Ganesh Dasika, Jesse G. Beu
Compressing RNNs to Kilobyte Budget for IoT Devices Using Kronecker Products. ACM J. Emerg. Technol. Comput. Syst. 17 (4) (2021)
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina
Rank and run-time aware compression of NLP Applications. CoRR (2020)
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina
Rank and run-time aware compression of NLP Applications. SustaiNLP@EMNLP (2020)
Dibakar Gope, Ganesh Dasika, Matthew Mattina
Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications. CoRR (2019)
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Chu Zhou, Igor Fedorov, Ganesh Dasika, Matthew Mattina
Compressing RNNs for IoT devices by 15-38x using Kronecker Products. CoRR (2019)
Jin Tao, Urmish Thakker, Ganesh Dasika, Jesse G. Beu
Skipping RNN State Updates without Retraining the Original Model. SenSys-ML (2019)
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina
Run-Time Efficient RNN Compression for Inference on Edge Devices. EMC2@HPCA/CVPR/ISCA (2019)
Dibakar Gope, Ganesh Dasika, Matthew Mattina
Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications. MLSys (2019)
Urmish Thakker, Igor Fedorov, Jesse G. Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina
Pushing the limits of RNN Compression. CoRR (2019)
Urmish Thakker, Igor Fedorov, Jesse G. Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina
Pushing the limits of RNN Compression. EMC2@NeurIPS (2019)
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina
Run-Time Efficient RNN Compression for Inference on Edge Devices. CoRR (2019)
Partha Maji, Andrew Mundy, Ganesh Dasika, Jesse G. Beu, Matthew Mattina, Robert D. Mullins
Efficient Winograd or Cook-Toom Convolution Kernel Implementation on Widely Used Mobile CPUs. EMC2@HPCA/CVPR/ISCA (2019)
Urmish Thakker, Ganesh Dasika, Jesse G. Beu, Matthew Mattina
Measuring scheduling efficiency of RNNs for NLP applications. CoRR (2019)
Partha Maji, Andrew Mundy, Ganesh Dasika, Jesse G. Beu, Matthew Mattina, Robert D. Mullins
Efficient Winograd or Cook-Toom Convolution Kernel Implementation on Widely Used Mobile CPUs. CoRR (2019)
Yu Cao, Xin Li, Jae-sun Seo, Ganesh Dasika
Guest Editors' Introduction: Frontiers of Hardware and Algorithms for On-chip Learning. ACM J. Emerg. Technol. Comput. Syst. 14 (2) (2018)
Tim Llewellynn, Maria del Milagro Fernández-Carrobles, Oscar Déniz, Samuel Fricker, Amos J. Storkey, Nuria Pazos, Gordana Velikic, Kirsten Leufgen, Rozenn Dahyot, Sebastian Koller, Georgios I. Goumas, Peter Leitner, Ganesh Dasika, Lei Wang, Kurt Tutschku
BONSEYES: Platform for Open Development of Systems of Artificial Intelligence: Invited paper. Conf. Computing Frontiers (2017)
Yordan P. Raykov, Emre Ozer, Ganesh Dasika, Alexis Boukouvalas, Max A. Little
Predicting room occupancy with a single passive infrared (PIR) sensor through behavior extraction. UbiComp (2016)
Naveen Suda, Vikas Chandra, Ganesh Dasika, Abinash Mohanty, Yufei Ma, Sarma B. K. Vrudhula, Jae-sun Seo, Yu Cao
Throughput-Optimized OpenCL-based FPGA Accelerator for Large-Scale Convolutional Neural Networks. FPGA (2016)