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Omri Traub

dblp:60/1077 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1998
—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 · 91% Runtime systems and virtual machines · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Compilers and program optimization › register allocation
graph coloring register allocation
0.011998
Quality and Speed in Linear-scan Register Allocation · PLDI 1998
Compilers and program optimization › register allocation
linear scan register allocation
0.011998
Quality and Speed in Linear-scan Register Allocation · PLDI 1998
Compilers and program optimization
register allocation
0.011998
Quality and Speed in Linear-scan Register Allocation · PLDI 1998
Runtime systems and virtual machines
dynamic compilation
0.011998
Quality and Speed in Linear-scan Register Allocation · PLDI 1998

Methods — techniques the papers use, named apart from their topics

linear sweep · 0.0graph coloring · 0.0
YearPublicationVenuePosition
1998 Quality and Speed in Linear-scan Register Allocation
abstract
A linear-scan algorithm directs the global allocation of register candidates to registers based on a simple linear sweep over the program being compiled. This approach to register allocation makes sense for systems, such as those for dynamic compilation, where compilation speed is important. In contrast, most commercial and research optimizing compilers rely on a graph-coloring approach to global register allocation. In this paper, we compare the performance of a linear-scan method against a modern graph-coloring method. We implement both register allocators within the Machine SUIF extension of the Stanford SUIF compiler system. Experimental results show that linear scan is much faster than coloring on benchmarks with large numbers of register candidates. We also describe improvements to the linear-scan approach that do not change its linear character, but allow it to produce code of a quality near to that produced by graph coloring.
Omri Traub, Glenn H. Holloway, Michael D. Smith 0001
PLDI1