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https://doi.org/10.1109/isqed....
Article . 2011 . Peer-reviewed
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Floorplanning for High Utilization of Heterogeneous FPGAs

Authors: Nan Liu 0002; Song Chen 0001; Takeshi Yoshimura;

Floorplanning for High Utilization of Heterogeneous FPGAs

Abstract

Heterogeneous resources such as configurable logic blocks (CLBs), multiplier blocks (MULs) and ram blocks (RAMs) where millions of logic gates (a growing trend to implement larger and more complex functions) included have been added to field programmable gate arrays (FPGAs). And floorplanning for this, hierarchical approach is recognized as the most effective method. The FPGA architecture shows that CLBs hold the maximum quantity much more than other resources. Therefore, making a high utilization of them means an enhancement of the FPGA densities. This paper presents a three-phase floorplanning method for heterogeneous FPGAs. The proposed method can make the resource requirement of functional modules satisfied with a high resource utilization. First, we use a non-slicing floorplanning method to optimize the wirelength, however, in this phase, the satisfaction of resource requirements from functional modules might fail. Second, a min-cost-max-flow algorithm is used to tune the assignment of CLBs to functional modules, such that all the functional modules get CLB requirements satisfied. Finally, the MULs and RAMs are allocated to modules by a network flow model. The results show that about 7%-85% wirelength reduction is obtained, and CLB utilization is improved by about 25%.

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Keywords

field programmable gate array, high utilization, floorplanning

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average