Demo Data from EDBT 2026 / reviewers in the wild / expert
Georg Madsen
dblp:44/1537
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Parallel and multicore computing › parallel computing › parallel application performance
parallel program performance analysis |
0.0 | 1 | 2001 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | On using SCALEA for performance analysis of distributed and parallel programsabstractIn 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 |
SC | 3 |