Demo Data from EDBT 2026 / reviewers in the wild / expert
Rendong Liang
dblp:331/1702
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0003-1405-503XORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Compilers and program optimization · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
GPUs and heterogeneous computing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Compilers and program optimization
code generation |
0.6 | 1 | 2022 | Romou: rapidly generate high-performance tensor kernels for mobile GPUs · MobiCom 2022 |
GPUs and heterogeneous computing › embedded GPU
mobile GPU |
0.2 | 1 | 2022 | Romou: rapidly generate high-performance tensor kernels for mobile GPUs · MobiCom 2022 |
Methods — techniques the papers use, named apart from their topics
automatic kernel generation · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Romou: rapidly generate high-performance tensor kernels for mobile GPUsabstractMobile GPU, as a ubiquitous and powerful accelerator, plays an important role in accelerating on-device DNN (Deep Neural Network) inference. The frequent-upgrade and diversity of mobile GPUs require automatic kernel generation to empower fast DNN deployment. However, current generated kernels have poor performance. Rendong Liang, Ting Cao 0003, Jicheng Wen, Manni Wang, Yang Wang 0053, Jianhua Zou, Yunxin Liu 0001 |
MobiCom | 1 |