Demo Data from VLDB 2026 / reviewers in the wild / expert
HyunMi Kim
dblp:216/7151
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2018
0000-0003-4105-7639ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
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.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Hardware accelerators and domain-specific architectures · 77% Parallel and multicore computing · 23% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Hardware accelerators and domain-specific architectures
video coding accelerator |
0.3 | 1 | 2018 | An Efficient Architecture of In-Loop Filters for Multicore Scalable HEVC Hardware Decoders · IEEE Trans. Multim. 2018 |
Methods — techniques the papers use, named apart from their topics
window-based parallel SAO · 0.3skip mode pipelining · 0.3adaptive deblocking filtering order · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | An Efficient Architecture of In-Loop Filters for Multicore Scalable HEVC Hardware DecodersabstractThis paper proposes an efficient architecture of HEVC in-loop filters (ILFs) with the target of providing effective multicore utilization for ultra-high definition video applications. While HEVC allows for a high level of parallelization, the issue of data dependencies at the ILF leads to inefficient parallel processing performance. The novel memory organization and management techniques address the data dependence-related issues between multiple processing units and enable to filter the flexible area on multicore decoder. In addition, we introduce the adaptive deblocking filtering order (ADFO) to minimize the impact of bus congestion when multiple cores interoperate for processing very large data. Furthermore, we design the deblocking filter with skip mode pipelining to achieve the high performance minimizing the increased cost and the power consumption. For SAO, we apply the window-based parallel SAO filtering scheme. The resource sharing is considered throughout the entire architecture. Based on both experimental and analytical results, our proposed design can achieve more than 1.31 Gpixels/s and less than 2.6 Gpixels/s at maximum frequency 660 MHz in single core, and consumes 56.2 Kgates including 10.6 Kgates for memory management architecture, which supports multicore decoder, and about 20.8 mW power on average when synthesizing with the 28 nm CMOS library. Moreover, the skip modes of DF improve both the performance and the power dissipation. The ADFO improves the performance of ~9.17% when decoding 8 K sequence on octacore at 400 MHz frequency. TpG (Throughput per Gate) is the highest among the related works. HyunMi Kim, JeongGil Ko, Seongmo Park |
IEEE Trans. Multim. | 1 |