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Home
About
Overview
Objectives
Research
Gender Issues
People
Publications
Downloads
Links
Contacts
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Slides
Highly-Efficient Persistent Data Structures: The performance principles that govern their design - Invited Talk EMERALD, June 2024
Parallel and Distributed Data Series Processing on Modern and Emerging Hardware - Paper Presentation MEDES, May 2023
MultiVersion Concurrent Data Structures - Invited Talk SPTDC, November 2023
Recoverable Computing - Invited Talk, OPODIS, December 2022
Practically and Theoretically Efficient Garbage Collection for Multiversioning - Paper Presentation, PPoPP, February 2023
WP3, Development of new techniques for conducting experimental analyses in NVM settings and for emulating restarts and other types of failures - WIP Slides, October 2023
Videos
Space and Time Bounded Multiversion Garbage Collection - Paper Presentation, DiSC, October 2021
The Performance Power of Software Combining in Persistence - Paper Presentation, PPoPP, July 2022
Tracking in Order to Recover: Detectable Recovery of Lock-Free Data Structures - Paper Presentation, PPoPP, April 2022
Posters
PERSIST Poster - October 2023
FRESH Poster - 2023
Combiner Queues Poster - GEC 2024
Persistent Queues Poster - GEC 2024
ATROPOS Poster - GEC 2024
Press Releases and Articles
PERSIST Article, HiPEAC info, No 69, page 32-33 - October 2023
PERSIST Article, HiPEAC info, No 69, page 29 - July 2023
FORTH Press Release on the Beginning of PERSIST - November 2022
Technical Reports and Deliverables
When Is Recoverable Consensus Harder Than Consensus? - FORTH ICS TR 491 December 2023
Practically and Theoretically Efficient Garbage Collection for Multiversioning - FORTH ICS TR 490 December 2023
FreSh: A Lock-Free Data Series Index - FORTH ICS TR 489 October 2023
FreSh: A Lock-Free Data Series Index - LIPADE-TR-9 October 2022
Space and Time Bounded Multiversion Garbage Collection - FORTH ICS TR 482 October 2022
Tracking in Order to Recover: Detectable Recovery of Lock-Free Data Structures - FORTH ICS TR 481 October 2022
Deliverable D1.1 - Data Management Plan
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