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Kumud Bhandari

dblp:14/6029 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none

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

Software engineering, systems software and programming languages · 2 · 1 first-author

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 · 56% Storage systems · 44%
Software engineering, system software, and programming languages
1 paper
Concurrent programming · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems
non-volatile memory
0.422016
Makalu: fast recoverable allocation of non-volatile memory · OOPSLA 2016
Atlas: leveraging locks for non-volatile memory consistency · OOPSLA 2014
Storage systems
crash recovery
0.212016
Makalu: fast recoverable allocation of non-volatile memory · OOPSLA 2016
Memory systems › non-volatile memory
non-volatile memory management
0.212016
Makalu: fast recoverable allocation of non-volatile memory · OOPSLA 2016
Storage systems
storage reliability
0.212016
Makalu: fast recoverable allocation of non-volatile memory · OOPSLA 2016
Storage systems
crash consistency
0.212014
Atlas: leveraging locks for non-volatile memory consistency · OOPSLA 2014
Memory systems › non-volatile memory
persistent memory
0.212014
Atlas: leveraging locks for non-volatile memory consistency · OOPSLA 2014
Concurrent programming
synchronization
0.112014
Atlas: leveraging locks for non-volatile memory consistency · OOPSLA 2014

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

lock-based consistency protocol · 0.4recovery-time garbage collection · 0.2allocator design · 0.2
YearPublicationVenuePosition
2016 Makalu: fast recoverable allocation of non-volatile memory
abstract
Byte addressable non-volatile memory (NVRAM) is likely to supplement, and perhaps eventually replace, DRAM. Applications can then persist data structures directly in memory instead of serializing them and storing them onto a durable block device. However, failures during execution can leave data structures in NVRAM unreachable or corrupt. In this paper, we present Makalu, a system that addresses non-volatile memory management. Makalu offers an integrated allocator and recovery-time garbage collector that maintains internal consistency, avoids NVRAM memory leaks, and is efficient, all in the face of failures.
Kumud Bhandari, Dhruva R. Chakrabarti, Hans-Juergen Boehm
OOPSLA1
2014 Atlas: leveraging locks for non-volatile memory consistency
abstract
Non-volatile main memory, such as memristors or phase change memory, can revolutionize the way programs persist data. In-memory objects can themselves be persistent without the need for a separate persistent data storage format. However, the challenge is to ensure that such data remains consistent if a failure occurs during execution.
Dhruva R. Chakrabarti, Hans-Juergen Boehm, Kumud Bhandari
OOPSLA3