EDBT 2026 Demo / reviewers in the wild / expert
Nisarg Shah 0004
dblp:320/7654
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems
crash recovery |
0.6 | 1 | 2022 | ASAP: A Speculative Approach to Persistence · HPCA 2022 |
Memory systems › non-volatile memory
persistent memory |
0.6 | 1 | 2022 | ASAP: A Speculative Approach to Persistence · HPCA 2022 |
Processor architecture and microarchitecture
speculative execution |
0.6 | 1 | 2022 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | ASAP: A Speculative Approach to PersistenceabstractPersistent 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 |
HPCA | 2 |