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Georg Madsen

dblp:44/1537 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2001
—ORCID · none

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

Systems, architecture and hardware · 1

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
Parallel and multicore computing · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Parallel and multicore computing › parallel computing › parallel application performance
parallel program performance analysis
0.012001
On using SCALEA for performance analysis of distributed and parallel programs · SC 2001

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

instrumentation · 0.0hardware profiling · 0.0dynamic code region call graph · 0.0
YearPublicationVenuePosition
2001 On using SCALEA for performance analysis of distributed and parallel programs
abstract
In this paper we give an overview of SCALEA, which is a new performance analysis tool for OpenMP, MPI, HPF, and mixed parallel/distributed programs. SCALEA instruments, executes and measures programs and computes a variety of performance overheads based on a novel overhead classification. Source code and HW-profiling is combined in a single system which significantly extends the scope of possible overheads that can be measured and examined, ranging from HW-counters, such as the number of cache misses or floating point operations, to more complex performance metrics, such as control or loss of parallelism. Moreover, SCALEA uses a new representation of code regions, called the dynamic code region call graph, which enables detailed overhead analysis for arbitrary code regions. An instrumentation description file is used to relate performance information to code regions of the input program and to reduce instrumentation overhead. Several experiments with realistic codes that cover MPI, OpenMP, HPF, and mixed OpenMP/MPI codes demonstrate the usefulness of SCALEA.
Hong Linh Truong 0001, Thomas Fahringer, Georg Madsen, Allen D. Malony, Hans Moritsch, Sameer Shende
SC3