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Peter Bergner

dblp:17/3607 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1997
—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%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Compilers and program optimization › register allocation
graph coloring register allocation
0.011997
Spill Code Minimization via Interference Region Spilling · PLDI 1997
Compilers and program optimization
register allocation
0.011997
Spill Code Minimization via Interference Region Spilling · PLDI 1997
Compilers and program optimization › register allocation
spill code minimization
0.011997
Spill Code Minimization via Interference Region Spilling · PLDI 1997

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

interference region spilling · 0.0
YearPublicationVenuePosition
1997 Spill Code Minimization via Interference Region Spilling
abstract
Many optimizing compilers perform global register allocation using a Chaitin-style graph coloring algorithm. Live ranges that cannot be allocated to registers are spilled to memory. The amount of code required to spill the live range depends on the spilling heuristic used. Chaitin's spilling heuristic offers some guidance in reducing the amount of spill code produced. However, this heuristic does not allow the partial spilling of live ranges and the reduction in spill code is limited to a local level. In this paper, we present a global technique called interference region spilling that improves the spilling granularity of any local spilling heuristic. Our technique works above the local spilling heuristic, limiting the normal insertion of spill code to a portion of each spilled live range. By partially spilling live ranges, we can achieve large reductions in dynamically executed spill code; up to 75% in some cases and an average of 33.6% across the benchmarks tested. 1 Introduction Gl...
Peter Bergner, Peter Dahl, David Engebretsen, Matthew T. O'Keefe
PLDI1