Abstract

Recent advances in biomedical research, including Bioinformatics, Computational Biology, and Medical imaging, are generating a huge amount of data to be analyzed. Processing this ensemble of data within a reasonable time is a difficult task that can be addressed relying on High-Performance Computing (HPC) infrastructures, such as multi-core Central Processing Units (CPUs) and Graphics Processing Units (GPUs). On the contrary, other fields of research (e.g., Systems Biology) require computational methods that deal with issues related to the lack of quantitative data, especially in the case of large-scale instances. Computational Intelligence methods can be effectively applied to tackle the complexity of some well-know problems in these fields, such as the Parameter Estimation (PE) problem in Systems Biology and the Haplotype Assembly (HA) problem in Genome Analysis. In this talk, the challenges, the peculiarities and the novel trends in HPC will be described and analyzed. I will start introducing the HPC architectures, focusing especially on multi-core CPUs and GPUs. Afterwards, the PE and the HA problems will be briefly described. To conclude, some recent accelerated methods designed to deal with those problems will be presented and discussed.

Andrea Tangherloni received his Bachelor’s and Master’s Degrees in Computer Science from the University of Milano-Bicocca, Italy, in 2013 and 2015, respectively. He is currently a Ph.D. Student in Computer Science, under the supervision of Prof. D. Besozzi and Dr. P. Cazzaniga, at the University of Milano-Bicocca, Italy. His main scientific research interests include High-Performance Computing, Systems Biology, Computational Biology, Bioinformatics, Genome Analysis, Computational Intelligence, and Biomedical Image Analysis