VLDB 2026 Research / reviewers in the wild / expert
Wei Kuai
dblp:311/8885
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software 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.
| Software engineering, system software, and programming languages
1 paper |
Compilers and program optimization · 67% Runtime systems and virtual machines · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Compilers and program optimization › compiler construction
ahead-of-time compilation |
0.5 | 1 | 2021 | Towards a Serverless Java Runtime · ASE 2021 |
Runtime systems and virtual machines › virtual machine implementation
java virtual machine |
0.5 | 1 | 2021 | Towards a Serverless Java Runtime · ASE 2021 |
Compilers and program optimization › dynamic optimization
profile-guided optimization |
0.5 | 1 | 2021 | Towards a Serverless Java Runtime · ASE 2021 |
Methods — techniques the papers use, named apart from their topics
just-in-time compilation · 0.5class data sharing · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Towards a Serverless Java RuntimeabstractJava virtual machine (JVM) has the well-known slow startup and warmup issues. This is because the JVM needs to dynamically create many runtime data before reaching peak performance, including class metadata, method profile data, and just-in-time (JIT) compiled native code, for each run of even the same application. Many techniques are then proposed to reuse and share these runtime data across different runs. For example, Class Data Sharing (CDS) and Ahead-of-time (AOT) compilation aim to save and share class metadata and compiled native code, respectively. Unfortunately, these techniques are developed independently and cannot leverage the ability of each other well. This paper presents an approach that systematically reuses JVM runtime data to accelerate application startup and warmup. We first propose and implement JWarmup, a technique that can record and reuse JIT compilation data (e.g., compiled methods and their profile data). Then, we feed JIT compilation data to the AOT compiler to perform profile-guided optimization (PGO). We also integrate existing CDS and AOT techniques to further optimize application startup. Evaluation on real-world applications shows that our approach can bring a 41.35% improvement to the application startup. Moreover, our approach can trigger JIT compilation in advance and reduce CPU load at peak time. Yifei Zhang 0001, Tianxiao Gu, Wei Kuai, Sanhong Li |
ASE | 5 |