Abstract: This work shows how the results of netlist placement for island style FPGAs can be improved by the use of a self-organizing map.
Improving FPGA-Placement with a Self-Organizing Map. Accelerated by GPU-Computing. Timm Bostelmann, Philipp Kewisch, Lennart Bublies and Sergei Sawitzki. FH ...
Abstract—This work shows how the results of netlist place- ment for island style FPGAs can be improved by the use of a self-organizing map.
In this work a method to improve the results of the netlist placement for FPGAs with a self-organizing map is presented, and a new metric to generate ...
In this work a method to improve the results of the netlist placement for FPGAs with a self-organizing map is presented. The admittedly high computational ...
Although some SOM-based FPGA placement algorithms [6, 7] have been studied, most tools are used under limited conditions. In contrast, there are few studies.
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Results in this paper show complementary SEU mitigation techniques working together to improve fault-tolerance. The results also suggest that fault injection ...
In this paper we present a novel placement algorithm for. FPGAs. This algorithm is based upon the self=organizing map used in unsupervised learning algorithms ...
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Improving the Performance of a SOM-Based FPGA-Placement ...
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This conceptual work presents and evaluates different approaches to exploit the inherent parallelism of the SOM to increase the computation-speed, based on ...
In this paper, we introduce a new neural network approach to place- ment problem of FPGA. The used network is a Koho- nen self-organization Map. A connection ...