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Francis Giraldeau

dblp:183/1930 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2016
0000-0002-2121-7589ORCID · reported

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

Systems, architecture and hardware · 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
Distributed systems · 50% Performance modeling and evaluation · 50%
Software engineering, system software, and programming languages
1 paper
Operating systems · 100%

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

TopicWeightPapersLastEvidence papers
Distributed systems
distributed debugging
0.212016
Wait Analysis of Distributed Systems Using Kernel Tracing · IEEE Trans. Parallel Distributed Syst. 2016
Performance modeling and evaluation
tracing and profiling
0.212016
Wait Analysis of Distributed Systems Using Kernel Tracing · IEEE Trans. Parallel Distributed Syst. 2016
Operating systems › kernel instrumentation
kernel tracing
0.112016
Wait Analysis of Distributed Systems Using Kernel Tracing · IEEE Trans. Parallel Distributed Syst. 2016

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

wait cause recovery · 0.5kernel tracing · 0.5
YearPublicationVenuePosition
2016 Wait Analysis of Distributed Systems Using Kernel Tracing
abstract
We propose a new class of profiler for distributed and heterogeneous systems. In these systems, a task may wait for the result of another task, either locally or remotely. Such wait dependencies are invisible to instruction profilers. We propose a host-based, precise method to recover recursively wait causes across machines, using blocking as the fundamental mechanism to detect changes in the control flow. It relies solely on operating system events, namely scheduling, interrupts and network events. It is therefore capable of observing kernel threads interactions and achieves user-space runtime independence. Given a task, the algorithm computes its active path from the trace, which is presented in an interactive viewer for inspection. We validated our new method with workloads representing major architecture and operating conditions found in distributed programs. We then used our method to analyze the execution behavior of five different distributed systems. We found that the worst case tracing overhead for a distributed application is 18 percent and that the typical average overhead is about 5 percent. The analysis implementation has linear runtime according to the trace size.
Francis Giraldeau, Michel R. Dagenais
IEEE Trans. Parallel Distributed Syst.1