activity
20172021
most citedCollaborative Execution of Deep Neural Networks on Internet of Things Devices

19 citations · 39 across the 12 of their papers we have counts for

collaborators

14 papers

cs.AR2021

Vortex: Extending the RISC-V ISA for GPGPU and 3D-GraphicsResearch

Blaise Tine, Fares Elsabbagh, Krishna Yalamarthy +1

The importance of open-source hardware and software has been increasing. However, despite GPUs being one of the more popular accelerators across various applications, there is very…

cs.AR2021

RASA: Efficient Register-Aware Systolic Array Matrix Engine for CPU

Geonhwa Jeong, Eric Qin, Ananda Samajdar +4

As AI-based applications become pervasive, CPU vendors are starting to incorporate matrix engines within the datapath to boost efficiency. Systolic arrays have been the premier arc…

cs.PL20213 cited

Supporting CUDA for an extended RISC-V GPU architecture

Ruobing Han, Blaise Tine, Jaewon Lee +2

With the rapid development of scientific computation, more and more researchers and developers are committed to implementing various workloads/operations on different devices. Amon…

cs.RO2021

Context-Aware Task Handling in Resource-Constrained Robots with Virtualization

Ramyad Hadidi, Nima Shoghi Ghalehshahi, Bahar Asgari +1

Intelligent mobile robots are critical in several scenarios. However, as their computational resources are limited, mobile robots struggle to handle several tasks concurrently and…

cs.DC2021

Creating Robust Deep Neural Networks With Coded Distributed Computing for IoT Systems

Ramyad Hadidi, Jiashen Cao, Hyesoon Kim

The increasing interest in serverless computation and ubiquitous wireless networks has led to numerous connected devices in our surroundings. Among such devices, IoT devices have a…

cs.DB20216 cited

THIA: Accelerating Video Analytics using Early Inference and Fine-Grained Query Planning

Jiashen Cao, Ramyad Hadidi, Joy Arulraj +1

To efficiently process visual data at scale, researchers have proposed two techniques for lowering the computational overhead associated with the underlying deep learning models. T…