VLDB 2026 Research / reviewers in the wild / expert
Fabien Quilleré
dblp:86/2341
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2000
—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.
| Software engineering, system software, and programming languages
1 paper |
Compilers and program optimization · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Electronic design automation · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Compilers and program optimization › parallelization
automatic parallelization |
0.0 | 1 | 2000 | Optimizing memory usage in the polyhedral model · ACM Trans. Program. Lang. Syst. 2000 |
Compilers and program optimization
code generation |
0.0 | 1 | 2000 | Optimizing memory usage in the polyhedral model · ACM Trans. Program. Lang. Syst. 2000 |
Compilers and program optimization › compiler optimization
memory reuse |
0.0 | 1 | 2000 | Optimizing memory usage in the polyhedral model · ACM Trans. Program. Lang. Syst. 2000 |
Compilers and program optimization
polyhedral model |
0.0 | 1 | 2000 | Optimizing memory usage in the polyhedral model · ACM Trans. Program. Lang. Syst. 2000 |
Electronic design automation › high-level synthesis › accelerator synthesis
systolic array synthesis |
0.0 | 1 | 2000 | Optimizing memory usage in the polyhedral model · ACM Trans. Program. Lang. Syst. 2000 |
Methods — techniques the papers use, named apart from their topics
projection · 0.1modular functions · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | Optimizing memory usage in the polyhedral modelabstractThe polyhedral model provides a single unified foundation for systolic array synthesis and automatic parallelization of loop programs. We investigate the problem of memory reuse when compiling Alpha (a functional language based on this model). Direct compilation would require unacceptably large memory (for example O(n 3 ) for matrix multiplication). Researchers have previously addressed the problem of memory reuse, and the analysis that this entails for projective memory allocations. This paper addresses, for a given schedule, the choice of the projections so as to minimize the volume of the residual memory. We prove tight bounds on the number of linearly independent projection vectors. Our method is constructive, yielding an optimal memory allocation. We extend the method to modular functions, and deal with the subsequent problems of code generation. Our ideas are illustrated on a number of examples generated by the current version of the Alpha compiler. Fabien Quilleré, Sanjay V. Rajopadhye |
ACM Trans. Program. Lang. Syst. | 1 |