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Philip J. Hanlon

dblp:27/5549 · also Phil Hanlon · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2003
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 first-authorSoftware engineering, systems software and programming languages · 1Theory of computation · 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
Performance modeling and evaluation · 67% Memory systems · 33%
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

TopicWeightPapersLastEvidence papers
Memory systems › cache
cache behavior
0.012001
Exact Analysis of the Cache Behavior of Nested Loops · PLDI 2001
Performance modeling and evaluation › simulation
cache simulation
0.012001
Exact Analysis of the Cache Behavior of Nested Loops · PLDI 2001
Performance modeling and evaluation
static performance analysis
0.012001
Exact Analysis of the Cache Behavior of Nested Loops · PLDI 2001
Compilers and program optimization › loop optimization
loop nest optimization
0.012001
Exact Analysis of the Cache Behavior of Nested Loops · PLDI 2001

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

presburger arithmetic · 0.1cache simulation · 0.1
YearPublicationVenuePosition
2003 Least-squares fit of genomic data by sums of epistatic effects
Philip J. Hanlon, William Andrew Lorenz, Dave Strenski
J. Parallel Distributed Comput.1
2001 Exact Analysis of the Cache Behavior of Nested Loops
abstract
We develop from first principles an exact model of the behavior of loop nests executing in a memory hicrarchy, by using a nontraditional classification of misses that has the key property of composability. We use Presburger formulas to express various kinds of misses as well as the state of the cache at the end of the loop nest. We use existing tools to simplify these formulas and to count cache misses. The model is powerful enough to handle imperfect loop nests and various flavors of non-linear array layouts based on bit interleaving of array indices. We also indicate how to handle modest levels of associativity, and how to perform limited symbolic analysis of cache behavior. The complexity of the formulas relates to the static structure of the loop nest rather than to its dynamic trip count, allowing our model to gain efficiency in counting cache misses by exploiting repetitive patterns of cache behavior. Validation against cache simulation confirms the exactness of our formulation. Our method can serve as the basis for a static performance predictor to guide program and data transformations to improve performance.
Siddhartha Chatterjee, Erin Parker, Philip J. Hanlon, Alvin R. Lebeck
PLDI3
2001 The Combinatorics of Cache Misses during Matrix Multiplication
Philip J. Hanlon, Dean Chung, Siddhartha Chatterjee, Daniela Genius, Alvin R. Lebeck, Erin Parker
J. Comput. Syst. Sci.1