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.

David T. Aksun

dblp:228/5403 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

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

Software engineering, systems software and programming languages · 2Systems, architecture and hardware · 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.

Computer architecture, parallel and distributed computing, and storage systems
2 papers
Memory systems · 48% Storage systems · 39% Distributed systems · 13%
Software engineering, system software, and programming languages
1 paper
Programming languages and type systems · 87% Runtime systems and virtual machines · 13%

Topics — the 10 heaviest of 11, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems
non-volatile memory
0.722019
Fine-Grain Checkpointing with In-Cache-Line Logging · ASPLOS 2019
Object-oriented recovery for non-volatile memory · Proc. ACM Program. Lang. 2018
Distributed systems › fault tolerance
checkpointing
0.412019
Fine-Grain Checkpointing with In-Cache-Line Logging · ASPLOS 2019
Storage systems
crash consistency
0.412019
Fine-Grain Checkpointing with In-Cache-Line Logging · ASPLOS 2019
Storage systems
logging
0.412019
Fine-Grain Checkpointing with In-Cache-Line Logging · ASPLOS 2019
Memory systems › non-volatile memory
persistent memory
0.412019
Fine-Grain Checkpointing with In-Cache-Line Logging · ASPLOS 2019
Storage systems › logging
undo logging
0.412019
Fine-Grain Checkpointing with In-Cache-Line Logging · ASPLOS 2019
Programming languages and type systems › language design
language extension
0.312018
Object-oriented recovery for non-volatile memory · Proc. ACM Program. Lang. 2018
Programming languages and type systems
object-oriented programming
0.312018
Object-oriented recovery for non-volatile memory · Proc. ACM Program. Lang. 2018
Memory systems › non-volatile memory › persistent memory
persistent heap
0.312018
Object-oriented recovery for non-volatile memory · Proc. ACM Program. Lang. 2018
Indexing and storage engines
persistent data structure
0.112019
Fine-Grain Checkpointing with In-Cache-Line Logging · ASPLOS 2019

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

in-cache-line logging · 0.8fine-grained checkpointing · 0.8object migration · 0.7heap compaction · 0.7Clang/LLVM · 0.7
YearPublicationVenuePosition
2019 Fine-Grain Checkpointing with In-Cache-Line Logging
abstract
Non-Volatile Memory offers the possibility of implementing high-performance, durable data structures. However, achieving performance comparable to well-designed data structures in non-persistent (transient) memory is difficult, primarily because of the cost of ensuring the order in which memory writes reach NVM.\@ Often, this requires flushing data to NVM and waiting a full memory round-trip time. In this paper, we introduce two new techniques: Fine-Grained Checkpointing, which ensures a consistent, quickly recoverable data structure in NVM after a system failure, and In-Cache-Line Logging, an undo-logging technique that enables recovery of earlier state without requiring cache-line flushes in the normal case. We implemented these techniques in the Masstree data structure, making it persistent and demonstrating the ease of applying them to a highly optimized system and their low (5.9-15.4%) runtime overhead cost.
Nachshon Cohen, David T. Aksun, Hillel Avni, James R. Larus
ASPLOS2
2018 Object-oriented recovery for non-volatile memory
abstract
New non-volatile memory (NVM) technologies enable direct, durable storage of data in an application's heap. Durable, randomly accessible memory facilitates the construction of applications that do not lose data at system shutdown or power failure. Existing NVM programming frameworks provide mechanisms to consistently capture a running application's state. They do not, however, fully support object-oriented languages or ensure that the persistent heap is consistent with the environment when the application is restarted. In this paper, we propose a new NVM language extension and runtime system that supports object-oriented NVM programming and avoids the pitfalls of prior approaches. At the heart of our technique is object reconstruction, which transparently restores and reconstructs a persistent object's state during program restart. It is implemented in NVMReconstruction, a Clang/LLVM extension and runtime library that provides: (i) transient fields in persistent objects, (ii) support for virtual functions and function pointers, (iii) direct representation of persistent pointers as virtual addresses, and (iv) type-specific reconstruction of a persistent object during program restart. In addition, NVMReconstruction supports updating an application's code, even if this causes objects to expand, by providing object migration. NVMReconstruction also can compact the persistent heap to reduce fragmentation. In experiments, we demonstrate the versatility and usability of object reconstruction and its low runtime performance cost.
Nachshon Cohen, David T. Aksun, James R. Larus
Proc. ACM Program. Lang.2