Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data.

Fabien Quilleré

dblp:86/2341 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Compilers and program optimization › parallelization
automatic parallelization
0.012000
Optimizing memory usage in the polyhedral model · ACM Trans. Program. Lang. Syst. 2000
Compilers and program optimization
code generation
0.012000
Optimizing memory usage in the polyhedral model · ACM Trans. Program. Lang. Syst. 2000
Compilers and program optimization › compiler optimization
memory reuse
0.012000
Optimizing memory usage in the polyhedral model · ACM Trans. Program. Lang. Syst. 2000
Compilers and program optimization
polyhedral model
0.012000
Optimizing memory usage in the polyhedral model · ACM Trans. Program. Lang. Syst. 2000
Electronic design automation › high-level synthesis › accelerator synthesis
systolic array synthesis
0.012000
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
YearPublicationVenuePosition
2000 Optimizing memory usage in the polyhedral model
abstract
The 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