Demo Data from EDBT 2026 / reviewers in the wild / expert
Hervé Avril
dblp:68/3848
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2001
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 |
Performance modeling and evaluation · 70% Distributed systems · 30% |
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 › simulation › discrete-event simulation
parallel discrete event simulation |
0.0 | 1 | 2001 | On Rolling Back and Checkpointing in Time Warp · IEEE Trans. Parallel Distributed Syst. 2001 |
Distributed systems › fault tolerance
rollback recovery |
0.0 | 1 | 2001 | On Rolling Back and Checkpointing in Time Warp · IEEE Trans. Parallel Distributed Syst. 2001 |
Performance modeling and evaluation › simulation › discrete-event simulation › parallel discrete event simulation › optimistic simulation
time warp |
0.0 | 1 | 2001 | On Rolling Back and Checkpointing in Time Warp · IEEE Trans. Parallel Distributed Syst. 2001 |
Performance modeling and evaluation
simulation |
0.0 | 1 | 2001 | On Rolling Back and Checkpointing in Time Warp · IEEE Trans. Parallel Distributed Syst. 2001 |
Methods — techniques the papers use, named apart from their topics
rollback · 0.0clustering · 0.0checkpointing · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | On Rolling Back and Checkpointing in Time WarpabstractIn this paper, we present a family of three algorithms which serve to perform checkpoints and to roll back time warp. These algorithms are primarily intended for use in simulations in which there are a large number of LPs and in which events have a small computational granularity. Important representatives of this class are VLSI and computer network simulations. In each of our algorithms, LPs are gathered into clusters via algorithms which are application dependent. In order to examine the performance of our algorithms and to compare them to Time Warp, we made use of two of the largest digital logic circuits available from the ISCAS89 benchmark series of combinational circuits. The execution time, number of states saved, and maximal memory consumption were compared to the same quantities for time warp. Our results indicated that each of the algorithms occupies a different point in the spectrum of possible trade-offs between memory usage and execution time, ranging from substantial memory savings (at a comparable cost in speed) to memory savings and a comparable speed to time warp. Hence, an important benefit of our algorithms is the ability to trade off memory requirements with execution time. Hervé Avril, Carl Tropper |
IEEE Trans. Parallel Distributed Syst. | 1 |