Nisarg Shah 0004

dblp:320/7654 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

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

Systems, architecture and hardware · 1 · 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 · 33% Storage systems · 33% Processor architecture and microarchitecture · 33%

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

TopicWeightPapersLastEvidence papers
Storage systems
crash recovery
0.612022
ASAP: A Speculative Approach to Persistence · HPCA 2022
Memory systems › non-volatile memory
persistent memory
0.612022
ASAP: A Speculative Approach to Persistence · HPCA 2022
Processor architecture and microarchitecture
speculative execution
0.612022
ASAP: A Speculative Approach to Persistence · HPCA 2022

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

undo logging · 0.6eager persistence · 0.6
YearPublicationVenuePosition
2022 ASAP: A Speculative Approach to Persistence
abstract
Persistent memory enables a new class of applications that have persistent in-memory data structures. Recoverability of these applications imposes constraints on the ordering of writes to persistent memory. But, the cache hierarchy and memory controllers in modern systems may reorder writes to persistent memory. Therefore, programmers have to use expensive flush and fence instructions that stall the processor to enforce such ordering. While prior efforts circumvent stalling on long latency flush instructions, these designs under-perform in large-scale systems with many cores and multiple memory controllers.We propose ASAP, an architectural model in which the hardware takes an optimistic approach by persisting data eagerly, thereby avoiding any ordering stalls and utilizing the total system bandwidth efficiently. ASAP avoids stalling by allowing writes to be persisted out-of-order, speculating that all writes will eventually be persisted. For correctness, ASAP saves recovery information in the memory controllers which is used to undo the effects of speculative writes to memory in the event of a crash.Over a large number of representative workloads, ASAP improves performance over current Intel systems by 2.3 on average and performs within 3.9% of an ideal system.
Sujay Yadalam, Nisarg Shah 0004, Xiangyao Yu, Michael M. Swift
HPCA2