Anzeige
Erschienen in:
2014 | OriginalPaper | Buchkapitel
Parallel Rank Coherence in Networks for Inferring Disease Phenotype and Gene Set Associations
verfasst von : Tao Li, Duo Wang, Shuai Zhang, Yulu Yang
Erschienen in: Advanced Computer Architecture
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The RCNet (Rank Coherence in Networks) algorithm has been used to find out the associations between the gene sets and disease phenotypes. However, it suffers from high computational cost when the size of dataset is very large. In this paper, we design three mechanisms to solve the RCNet algorithm on heterogeneous CPU-GPU system based on CUDA and OpenMP programming model. The pipeline mechanism is much suitable for the collaborative computing on CPU and dual-GPUs, which can achieve more than 33 times performance gains. The work plays an important role in reconstructing the disease phoneme-genome association efficiently.