EDBT 2026 Demo / reviewers in the wild / expert
Adar Zeitak
dblp:304/2211
· DBLP profile ↗
1ranked-venue papers
1as 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 first-author · 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 |
Memory systems · 87% Performance modeling and evaluation · 13% | |
| Databases, data mining, and information retrieval
1 paper |
Indexing and storage engines · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Indexing and storage engines › access methods
ordered index |
0.5 | 1 | 2021 | Cuckoo Trie: Exploiting Memory-Level Parallelism for Efficient DRAM Indexing · SOSP 2021 |
Memory systems
DRAM |
0.5 | 1 | 2021 | Cuckoo Trie: Exploiting Memory-Level Parallelism for Efficient DRAM Indexing · SOSP 2021 |
Memory systems › memory access optimization
memory-level parallelism |
0.5 | 1 | 2021 | Cuckoo Trie: Exploiting Memory-Level Parallelism for Efficient DRAM Indexing · SOSP 2021 |
Performance modeling and evaluation
workload characterization |
0.1 | 1 | 2021 | Cuckoo Trie: Exploiting Memory-Level Parallelism for Efficient DRAM Indexing · SOSP 2021 |
Methods — techniques the papers use, named apart from their topics
trie · 1.0cuckoo hashing · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Cuckoo Trie: Exploiting Memory-Level Parallelism for Efficient DRAM IndexingabstractWe present the Cuckoo Trie, a fast, memory-efficient ordered index structure. The Cuckoo Trie is designed to have memory-level parallelism---which a modern out-of-order processor can exploit to execute DRAM accesses in parallel--- without sacrificing memory efficiency. The Cuckoo Trie thus breaks a fundamental performance barrier faced by current indexes, whose bottleneck is a series of dependent pointer-chasing DRAM accesses---e.g., traversing a search tree path--- which the processor cannot parallelize. Our evaluation shows that the Cuckoo Trie outperforms state-of-the-art-indexes by up to 20%-360% on a variety of datasets and workloads, typically with a smaller or comparable memory footprint. Adar Zeitak, Adam Morrison 0001 |
SOSP | 1 |