Demo Data from VLDB 2026 / reviewers in the wild / expert
Weiqi Shen
dblp:354/7983
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2026
0000-0001-6203-0182ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2 · 2 since 2021Software engineering, systems software and programming languages · 1 · 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.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 67% Performance modeling and evaluation · 33% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Performance modeling and evaluation › parallel performance evaluation
multicore scalability |
0.7 | 1 | 2023 | Toward Exascale Computation for Turbomachinery Flows · SC 2023 |
High-performance computing
performance optimization at scale |
0.7 | 1 | 2023 | Toward Exascale Computation for Turbomachinery Flows · SC 2023 |
High-performance computing
scientific computing systems |
0.7 | 1 | 2023 | Toward Exascale Computation for Turbomachinery Flows · SC 2023 |
Computational science and engineering › computational fluid dynamics
large eddy simulation |
0.2 | 1 | 2023 | Toward Exascale Computation for Turbomachinery Flows · SC 2023 |
Methods — techniques the papers use, named apart from their topics
high-order unstructured solver · 1.3heterogeneous parallel porting · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | RouterAcc: FPGA Acceleration for VLSI Detailed Router via Hierarchical Storage MappingabstractDetailed routing constitutes a critical phase in the very large-scale integration (VLSI) physical design, widely regarded as the most time-consuming and computationally intensive step in the back-end design process. Due to its iterative nature and strong data dependencies, conventional parallel acceleration techniques often suffer from limited scalability and effectiveness. To address these challenges, we propose RouterAcc, an FPGA-based software–hardware co-design acceleration framework tailored for VLSI detailed routing. RouterAcc incorporates an access analysis mechanism and a termination condition strategy to accelerate convergence. Furthermore, we employ a hierarchical storage mapping scheme and a flexible dimension-partitioning architecture to alleviate memory bottlenecks and enhance data locality. Additionally, RouterAcc leverages a hierarchical comparison pipeline with fully parallelized computing units and a data preprocessing strategy to maximize computational efficiency. Experimental results on the ISPD’18 benchmarks demonstrate that RouterAcc achieves consistent speedups of 2.1×–2.3× over TritonRoute with less than 1% quality degradation. With further co-optimization, RouterAcc attains speedups of 2.7×–11.8× while maintaining routing quality comparable to TritonRoute and surpassing Dr.CU 2.0 as well as the state-of-the-art (SOTA) FPGA-based approaches. Ruiyuan Guo, Zexu Zhang, Da Tang, Weiqi Shen, Haodong Lu 0001, Xiqiong Bai, Kun Wang 0005, Jianli Chen, Jun Yu 0010 |
DATE | 5 |
| 2023 | Toward Exascale Computation for Turbomachinery FlowsabstractA state-of-the-art large eddy simulation code has been developed to solve compressible flows in turbomachinery. The code has been engineered with a high degree of scalability, enabling it to effectively leverage the many-core architecture of the new Sunway system. A consistent performance of 115.8 DP-PFLOPs has been achieved on a high-pressure turbine cascade consisting of over 1.69 billion mesh elements and 865 billion Degree of Freedoms (DOFs). By leveraging a high-order unstructured solver and its portability to large heterogeneous parallel systems, we have progressed towards solving the grand challenge problem outlined by NASA [1], which involves a time-dependent simulation of a complete engine, incorporating all the aerodynamic and heat transfer components. Yuhang Fu, Weiqi Shen, Jiahuan Cui, Yao Zheng 0003, Guangwen Yang 0002, Jifa Zhang, Tingwei Ji, Fangfang Xie, Xiaojing Lv, Guocheng Tao, Paul Tucker, Steven A. E. Miller, Shirui Luo, Seid Koric |
SC | 2 |