Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Grégoire Gomes

dblp:204/3608 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 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.

Databases, data mining, and information retrieval
1 paper
Database system architecture and tuning · 50% Indexing and storage engines · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Indexing and storage engines › b+-tree
persistent b+-tree
0.312017
Memory Management Techniques for Large-Scale Persistent-Main-Memory Systems · Proc. VLDB Endow. 2017
Memory systems
non-volatile memory
0.112017
Memory Management Techniques for Large-Scale Persistent-Main-Memory Systems · Proc. VLDB Endow. 2017
Memory systems › non-volatile memory
storage class memory
0.112017
Memory Management Techniques for Large-Scale Persistent-Main-Memory Systems · Proc. VLDB Endow. 2017

Methods — techniques the papers use, named apart from their topics

defragmentation · 0.6concurrency control · 0.6
YearPublicationVenuePosition
2017 Memory Management Techniques for Large-Scale Persistent-Main-Memory Systems
abstract
Storage Class Memory (SCM) is a novel class of memory technologies that promise to revolutionize database architectures. SCM is byte-addressable and exhibits latencies similar to those of DRAM, while being non-volatile. Hence, SCM could replace both main memory and storage, enabling a novel single-level database architecture without the traditional I/O bottleneck. Fail-safe persistent SCM allocation can be considered conditio sine qua non for enabling this novel architecture paradigm for database management systems. In this paper we present PAllocator, a fail-safe persistent SCM allocator whose design emphasizes high concurrency and capacity scalability. Contrary to previous works, PAllocator thoroughly addresses the important challenge of persistent memory fragmentation by implementing an efficient defragmentation algorithm. We show that PAllocator outperforms state-of-the-art persistent allocators by up to one order of magnitude, both in operation throughput and recovery time, and enables up to 2.39x higher operation throughput on a persistent B-Tree.
Ismail Oukid, Daniel Booss, Adrien Lespinasse, Wolfgang Lehner, Thomas Willhalm, Grégoire Gomes
Proc. VLDB Endow.6