12 citations · 22 across the 7 of their papers we have counts for
7 papers
SWAM: Revisiting Swap and OOMK for Improving Application Responsiveness on Mobile Devices
Geunsik Lim, Donghyun Kang, MyungJoo Ham +1
Existing memory reclamation policies on mobile devices may be no longer valid because they have negative effects on the response time of running applications. In this paper, we pro…
Toward Among-Device AI from On-Device AI with Stream Pipelines
MyungJoo Ham, Sangjung Woo, Jaeyun Jung +4
Modern consumer electronic devices often provide intelligence services with deep neural networks. We have started migrating the computing locations of intelligence services from cl…
LightSys: Lightweight and Efficient CI System for Improving Integration Speed of Software
Geunsik Lim, MyungJoo Ham, Jijoong Moon +1
The complexity and size increase of software has extended the delay for developers as they wait for code analysis and code merge. With the larger and more complex software, more de…
BB: Booting Booster for Consumer Electronics with Modern OS
Geunsik Lim, MyungJoo Ham
Unconventional computing platforms have spread widely and rapidly following smart phones and tablets: consumer electronics such as smart TVs and digital cameras. For such devices,…
TAOS-CI: Lightweight & Modular Continuous Integration System for Edge Computing
Geunsik Lim, MyungJoo Ham, Jijoong Moon +3
With the proliferation of IoT and edge devices, we are observing a lot of consumer electronics becoming yet another IoT and edge devices. Unlike traditional smart devices, such as…
NNStreamer: Efficient and Agile Development of On-Device AI Systems
MyungJoo Ham, Jijoong Moon, Geunsik Lim +9
We propose NNStreamer, a software system that handles neural networks as filters of stream pipelines, applying the stream processing paradigm to deep neural network applications. A…