Demo Data from SIGIR 2026 / reviewers in the wild / expert
Sridhar Gopal
dblp:94/734
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2001
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 |
Processor architecture and microarchitecture · 56% Memory systems · 44% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Memory systems
cache coherence |
0.1 | 2 | 2001 | Speculative Versioning Cache · IEEE Trans. Parallel Distributed Syst. 2001 Speculative Versioning Cache · HPCA 1998 |
Processor architecture and microarchitecture › speculative execution
memory dependence speculation |
0.1 | 2 | 2001 | Speculative Versioning Cache · IEEE Trans. Parallel Distributed Syst. 2001 Speculative Versioning Cache · HPCA 1998 |
Processor architecture and microarchitecture
instruction-level parallelism |
0.0 | 1 | 2001 | Speculative Versioning Cache · IEEE Trans. Parallel Distributed Syst. 2001 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.1performance evaluation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | Speculative Versioning CacheabstractDependences among loads and stores whose addresses are unknown hinder the extraction of instruction level parallelism during the execution of a sequential program. Such ambiguous memory dependences can be overcome by memory dependence speculation which enables a load or store to be speculatively executed before the addresses of all preceding loads and stores are known. Furthermore, multiple speculative stores to a memory location create multiple speculative versions of the location. Program order among the speculative versions must be tracked to maintain sequential semantics. A previously proposed approach, the Address Resolution Buffer (ARB) uses a centralized buffer to support speculative versions. Our proposal, called the Speculative Versioning Cache (SVC), uses distributed caches to eliminate the latency and bandwidth problems of the ARB. The SVC conceptually unifies cache coherence and speculative versioning by using an organization similar to snooping bus-based coherent caches. Our evaluation for the Multiscalar architecture shows that hit latency is an important factor affecting performance and private cache solutions trade-off hit rate for hit latency. T. N. Vijaykumar, Sridhar Gopal, James E. Smith 0001, Gurindar S. Sohi |
IEEE Trans. Parallel Distributed Syst. | 2 |
| 1998 | Speculative Versioning CacheabstractDependences among loads and stores whose addresses are unknown hinder the extraction of instruction level parallelism during the execution of a sequential program. Such ambiguous memory dependences can be overcome by memory dependence speculation which enables a load or store to be speculatively executed before the addresses of all preceding loads and stores are known. Furthermore, multiple speculative stores to a memory location create multiple speculative versions of the location. Program order among the speculative versions must be tracked to maintain sequential semantics. A previously proposed approach, the address resolution buffer (ARB) uses a centralized buffer to support speculative versions. Our proposal, called the speculative versioning cache (SVC), uses distributed caches to eliminate the latency and bandwidth problems of the ARB. The SVC conceptually unifies cache coherence and speculative versioning by using an organization similar to snooping bus-based coherent caches. A preliminary evaluation for the multiscalar architecture shows that hit latency is an important factor affecting performance, and private cache solutions trade-off hit rate for hit latency. Sridhar Gopal, T. N. Vijaykumar, James E. Smith 0001, Gurindar S. Sohi |
HPCA | 1 |