Ganesh Dasika

According to our database, Ganesh Dasika authored at least 13 papers between 2016 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Compressing RNNs to Kilobyte Budget for IoT Devices Using Kronecker Products.

Urmish Thakker, Igor Fedorov, Chu Zhou, Dibakar Gope, Matthew Mattina, Ganesh Dasika, Jesse G. Beu

ACM J. Emerg. Technol. Comput. Syst., 2021

2020

Rank and run-time aware compression of NLP Applications.

Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina

Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing, 2020

2019

Compressing RNNs for IoT devices by 15-38x using Kronecker Products.

Urmish Thakker, Jesse G. Beu, Dibakar Gope, Chu Zhou, Igor Fedorov, Ganesh Dasika, Matthew Mattina

CoRR, 2019

Measuring scheduling efficiency of RNNs for NLP applications.

Urmish Thakker, Ganesh Dasika, Jesse G. Beu, Matthew Mattina

CoRR, 2019

Skipping RNN State Updates without Retraining the Original Model.

Jin Tao, Urmish Thakker, Ganesh Dasika, Jesse G. Beu

Proceedings of the 1st Workshop on Machine Learning on Edge in Sensor Systems, 2019

Pushing the limits of RNN Compression.

Urmish Thakker, Igor Fedorov, Jesse G. Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina

Proceedings of the Fifth Workshop on Energy Efficient Machine Learning and Cognitive Computing, 2019

Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications.

Dibakar Gope, Ganesh Dasika, Matthew Mattina

Proceedings of Machine Learning and Systems 2019, 2019

Run-Time Efficient RNN Compression for Inference on Edge Devices.

Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina

Proceedings of the 2nd Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications, 2019

Efficient Winograd or Cook-Toom Convolution Kernel Implementation on Widely Used Mobile CPUs.

Partha Maji, Andrew Mundy, Ganesh Dasika, Jesse G. Beu, Matthew Mattina, Robert D. Mullins

Proceedings of the 2nd Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications, 2019

2018

Guest Editors' Introduction: Frontiers of Hardware and Algorithms for On-chip Learning.

Yu Cao, Xin Li, Jae-sun Seo, Ganesh Dasika

ACM J. Emerg. Technol. Comput. Syst., 2018

2017

BONSEYES: Platform for Open Development of Systems of Artificial Intelligence: Invited paper.

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

Proceedings of the Computing Frontiers Conference, 2017

2016

Predicting room occupancy with a single passive infrared (PIR) sensor through behavior extraction.

Yordan P. Raykov, Emre Ozer, Ganesh Dasika, Alexis Boukouvalas, Max A. Little

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2016

Throughput-Optimized OpenCL-based FPGA Accelerator for Large-Scale Convolutional Neural Networks.

Naveen Suda, Vikas Chandra, Ganesh Dasika, Abinash Mohanty, Yufei Ma, Sarma B. K. Vrudhula, Jae-sun Seo, Yu Cao

Proceedings of the 2016 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2016