EDBT 2026 Demo / reviewers in the wild / expert
Uri Silbershtein
dblp:08/5665
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1
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 · 50% Runtime systems and virtual machines · 50% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Operating systems › resource management
memory management |
0.0 | 1 | 2004 | An efficient parallel heap compaction algorithm · OOPSLA 2004 |
Runtime systems and virtual machines › garbage collection
parallel garbage collection |
0.0 | 1 | 2004 | An efficient parallel heap compaction algorithm · OOPSLA 2004 |
Parallel and multicore computing › multiprocessor system
shared-memory multiprocessor |
0.0 | 1 | 2004 | An efficient parallel heap compaction algorithm · OOPSLA 2004 |
Methods — techniques the papers use, named apart from their topics
parallel moving strategy · 0.1forwarding pointer · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2004 | An efficient parallel heap compaction algorithmabstractWe propose a heap compaction algorithm appropriate for modern computing environments. Our algorithm is targeted at SMP platforms. It demonstrates high scalability when running in parallel but is also extremely efficient when running single-threaded on a uniprocessor. Instead of using the standard forwarding pointer mechanism for updating pointers to moved objects, the algorithm saves information for a pack of objects. It then does a small computation to process this information and determine each object's new location. In addition, using a smart parallel moving strategy, the algorithm achieves (almost) perfect compaction in the lower addresses of the heap, whereas previous algorithms achieved parallelism by compacting within several predetermined segments. Diab Abuaiadh, Yoav Ossia, Erez Petrank, Uri Silbershtein |
OOPSLA | 4 |