Accelerating the calculation of the Dunn index for clustering validation

• Eduardo S. Grün UFG
• Wellington S. Martins UFG
• Ricardo Franco UFG

DOI: https://doi.org/10.5753/eradco.2024.4532

Abstract

This paper presents a parallel implementation of the Dunn index, utilizing GPUs to accelerate its computation. The Dunn index is a commonly used metric to evaluate the quality of clustering. By exploiting the parallelism of GPUs, we were able to significantly accelerate the calculation of this index, enabling the analysis of larger and more complex datasets. Comparing the parallel implementation with the sequential one, we observed substantial performance gains, demonstrating the effectiveness of the proposed approach.

References

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