97 citations · 99 across the 2 of their papers we have counts for
4 papers
Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search
Kartik Hegde, Po-An Tsai, Sitao Huang +3
Modern day computing increasingly relies on specialization to satiate growing performance and efficiency requirements. A core challenge in designing such specialized hardware archi…
HTS: A Hardware Task Scheduler for Heterogeneous Systems
Kartik Hegde, Abhishek Srivastava, Rohit Agrawal
As the Moore's scaling era comes to an end, application specific hardware accelerators appear as an attractive way to improve the performance and power efficiency of our computing…
Morph: Flexible Acceleration for 3D CNN-based Video Understanding
Kartik Hegde, Rohit Agrawal, Yulun Yao +1
The past several years have seen both an explosion in the use of Convolutional Neural Networks (CNNs) and the design of accelerators to make CNN inference practical. In the archite…
UCNN: Exploiting Computational Reuse in Deep Neural Networks via Weight Repetition
Kartik Hegde, Jiyong Yu, Rohit Agrawal +3
Convolutional Neural Networks (CNNs) have begun to permeate all corners of electronic society (from voice recognition to scene generation) due to their high accuracy and machine ef…