VLDB 2026 Research / reviewers in the wild / expert
David Koufaty
dblp:354/6049
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 |
Operating systems · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 77% Parallel and multicore computing · 23% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Operating systems › resource management › process management
CPU scheduling |
0.8 | 1 | 2024 | LibPreemptible: Enabling Fast, Adaptive, and Hardware-Assisted User-Space Scheduling · HPCA 2024 |
Operating systems › resource management › process management › CPU scheduling
user-space scheduling |
0.8 | 1 | 2024 | LibPreemptible: Enabling Fast, Adaptive, and Hardware-Assisted User-Space Scheduling · HPCA 2024 |
Parallel and multicore computing › parallel scheduling
thread scheduling |
0.2 | 1 | 2024 | LibPreemptible: Enabling Fast, Adaptive, and Hardware-Assisted User-Space Scheduling · HPCA 2024 |
Methods — techniques the papers use, named apart from their topics
hardware-assisted interrupts · 1.5adaptive scheduling policies · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | LibPreemptible: Enabling Fast, Adaptive, and Hardware-Assisted User-Space SchedulingabstractModern cloud applications are prone to high tail latencies since their requests typically follow highly-dispersive distributions. Prior work has proposed both OS- and systemlevel solutions to reduce tail latencies for microsecond-scale workloads through better scheduling. Unfortunately, existing approaches like customized dataplane OSes, require significant OS changes, experience scalability limitations, or do not reach the full performance capabilities hardware offers. We propose LibPreemptible, a preemptive user-level threading library that is flexible, lightweight, and scalable. LibPreemptible is based on three key techniques: 1) a fast and lightweight hardware mechanism for delivery of timed interrupts, 2) a general-purpose user-level scheduling interface, and 3) an API for users to express adaptive scheduling policies tailored to the needs of their applications. Compared to the prior state-of-the-art scheduling system Shinjuku, our system achieves significant tail latency and throughput improvements for various workloads without the need to modify the kernel. We also demonstrate the flexibility of LibPreemptible across scheduling policies for real applications experiencing varying load levels and characteristics. Nikita Lazarev, David Koufaty, Tenny Yin, Andy Anderson, Zhiru Zhang, G. Edward Suh, Kostis Kaffes, Christina Delimitrou |
HPCA | 3 |