Details
| Original language | English |
|---|---|
| Pages | 294-303 |
| Number of pages | 10 |
| Publication status | Published - 1997 |
| Event | 1997 IEEE International Conference on Application-Specific Systems, Architectures and Processors, ASAP'97 - Zurich, Switzerland Duration: 14 Jul 1997 → 16 Jul 1997 |
Conference
| Conference | 1997 IEEE International Conference on Application-Specific Systems, Architectures and Processors, ASAP'97 |
|---|---|
| Country/Territory | Switzerland |
| City | Zurich |
| Period | 14 Jul 1997 → 16 Jul 1997 |
Abstract
We propose a novel stochastic approach for the problem of multiprocessor scheduling and allocation under timing and resource constraints using an evolutionary algorithm (EA). For composite schemes of DSP algorithms a compact problem encoding has been developed with emphasis on the allocation/binding part of the problem as well as an efficient problem transformation-decoding scheme in order to avoid infeasible solutions and therefore time consuming repair mechanisms. Thus, the algorithm is able to handle even large size problems within moderate computation time. Simulation results comparing the proposed EA with optimal results provided by mixed integer linear programming (MILP) show, that the EA is suitable to achieve the same or similar results but in much less time as problem size increases.
ASJC Scopus subject areas
- Computer Science(all)
- Hardware and Architecture
- Computer Science(all)
- Computer Networks and Communications
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1997. 294-303 Paper presented at 1997 IEEE International Conference on Application-Specific Systems, Architectures and Processors, ASAP'97, Zurich, Switzerland.
Research output: Contribution to conference › Paper › Research › peer review
}
TY - CONF
T1 - Heterogeneous multiprocessor scheduling and allocation using evolutionary algorithms
AU - Reuter, C.
AU - Schwiegershausen, M.
AU - Pirsch, P.
PY - 1997
Y1 - 1997
N2 - We propose a novel stochastic approach for the problem of multiprocessor scheduling and allocation under timing and resource constraints using an evolutionary algorithm (EA). For composite schemes of DSP algorithms a compact problem encoding has been developed with emphasis on the allocation/binding part of the problem as well as an efficient problem transformation-decoding scheme in order to avoid infeasible solutions and therefore time consuming repair mechanisms. Thus, the algorithm is able to handle even large size problems within moderate computation time. Simulation results comparing the proposed EA with optimal results provided by mixed integer linear programming (MILP) show, that the EA is suitable to achieve the same or similar results but in much less time as problem size increases.
AB - We propose a novel stochastic approach for the problem of multiprocessor scheduling and allocation under timing and resource constraints using an evolutionary algorithm (EA). For composite schemes of DSP algorithms a compact problem encoding has been developed with emphasis on the allocation/binding part of the problem as well as an efficient problem transformation-decoding scheme in order to avoid infeasible solutions and therefore time consuming repair mechanisms. Thus, the algorithm is able to handle even large size problems within moderate computation time. Simulation results comparing the proposed EA with optimal results provided by mixed integer linear programming (MILP) show, that the EA is suitable to achieve the same or similar results but in much less time as problem size increases.
UR - http://www.scopus.com/inward/record.url?scp=0030708495&partnerID=8YFLogxK
M3 - Paper
AN - SCOPUS:0030708495
SP - 294
EP - 303
T2 - 1997 IEEE International Conference on Application-Specific Systems, Architectures and Processors, ASAP'97
Y2 - 14 July 1997 through 16 July 1997
ER -