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Friedhelm Ramme

dblp:27/601 · DBLP profile ↗
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5ranked-venue papers
2as first author
0since 2021 · last 1998
—ORCID · none

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

Systems, architecture and hardware · 3 · 2 first-authorTheory of computation · 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
Cloud and datacenter computing · 100%

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

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing
bin packing
0.011994
Scheduling a Metacomputer by an Implicit Voting System · HPDC 1994
Cloud and datacenter computing
resource management
0.011994
Scheduling a Metacomputer by an Implicit Voting System · HPDC 1994

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

simulation · 0.0bin packing · 0.0
YearPublicationVenuePosition
1998 Specifying Resources and Services in Metacomputing Environments
Matthias Brune, Jörn Gehring, Axel Keller, Burkhard Monien, Friedhelm Ramme, Alexander Reinefeld
Parallel Comput.5
1996 Architecture-Independent Request-Scheduling with Tight Waiting-Time Estimations
Jörn Gehring, Friedhelm Ramme
JSSPP2
1995 A Parallel Simulated Annealing Algorithm for Generating 3D Layouts of Undirected Graphs
Burkhard Monien, Friedhelm Ramme, Helmut Salmen
GD2
1995 Building a virtual machine-room - a focal point in metacomputing
Friedhelm Ramme
Future Gener. Comput. Syst.1
1994 Scheduling a Metacomputer by an Implicit Voting System
abstract
We address the problem of scheduling hardware requests to a metacomputer environment. The environment may consist of a heterogeneous set of computing resources. A high level abstraction of the metacomputer is assumed to take care of the heterogeneity. The scheduling problem is considered in two parts. Some requests are extracted from the waiting room at first and scheduled afterwards by using bin packing to allocate the hardware resources. The bin packing algorithm is dynamically turned by the current mixture of the requests to tradeoff utilization versus response time. The extraction algorithm ensures prioritizing without starving lower priority jobs. The Implicit Voting System is compared to a well known bin packing algorithm by simulation. IVS improves the system utilization by 30% and simultaneously the average waiting time by 9%. Its behavior is also validated by integration into the Computing Center Software, CCS. Currently, this software package serves a pool of different transputer based MPP-systems to a large user community.>
Friedhelm Ramme, Kurt Kremer
HPDC1