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Adar Zeitak

dblp:304/2211 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Indexing and storage engines › access methods
ordered index
0.512021
Cuckoo Trie: Exploiting Memory-Level Parallelism for Efficient DRAM Indexing · SOSP 2021
Memory systems
DRAM
0.512021
Cuckoo Trie: Exploiting Memory-Level Parallelism for Efficient DRAM Indexing · SOSP 2021
Memory systems › memory access optimization
memory-level parallelism
0.512021
Cuckoo Trie: Exploiting Memory-Level Parallelism for Efficient DRAM Indexing · SOSP 2021
Performance modeling and evaluation
workload characterization
0.112021
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
YearPublicationVenuePosition
2021 Cuckoo Trie: Exploiting Memory-Level Parallelism for Efficient DRAM Indexing
abstract
We 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
SOSP1