Demo Data from VLDB 2026 / reviewers in the wild / expert
Stephanie Coleman
dblp:02/4230
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1995
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 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
1 paper |
Memory systems · 44% Parallel and multicore computing · 44% Performance modeling and evaluation · 13% | |
| Software engineering, system software, and programming languages
1 paper |
Compilers and program optimization · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Compilers and program optimization
loop optimization |
0.0 | 1 | 1995 | Tile Size Selection Using Cache Organization and Data Layout · PLDI 1995 |
Memory systems › cache
cache optimization |
0.0 | 1 | 1995 | Tile Size Selection Using Cache Organization and Data Layout · PLDI 1995 |
Parallel and multicore computing › loop transformation
tile size selection |
0.0 | 1 | 1995 | Tile Size Selection Using Cache Organization and Data Layout · PLDI 1995 |
Performance modeling and evaluation › simulation
cache simulation |
0.0 | 1 | 1995 | Tile Size Selection Using Cache Organization and Data Layout · PLDI 1995 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.0cache miss modeling · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1995 | Tile Size Selection Using Cache Organization and Data LayoutabstractWhen dense matrix computations are too large to fit in cache, previous research proposes tiling to reduce or eliminate capacity misses. This paper presents a new algorithm for choosing problem-size dependent tile sizes based on the cache size and cache line size for a direct-mapped cache. The algorithm eliminates both capacity and self-interference misses and reduces cross-interference misses. We measured simulated miss rates and execution times for our algorithm and two others on a variety of problem sizes and cache organizations. At higher set associativity, our algorithm does not always achieve the best performance. However on direct-mapped caches, our algorithm improves simulated miss rates and measured execution times when compared with previous work. Stephanie Coleman, Kathryn S. McKinley |
PLDI | 1 |