en ella se presentará el proyecto y se contará con la presencia de tres de los miembros de este proyecto procedentes de Islandia y Noruega los cuales expondrán sus líneas de trabajo dentro de este proyecto, las cuales están relacionadas directamente con Supercomputación. Luego habrá turno de preguntas y discusión para todos los interesados, estando las charlas abiertas a todo el mundo. El programa es el siguiente:
Horacio Pérez-Sánchez (UCAM)
Title : “Introduction to Nils Project”
The challenge of an aging society with anticoagulant requirements of increasing complexity is a problem of great relevance in health improvement and encourages the search for new anticoagulant molecules. Heparin is widely used as activator of antithrombin, but incurs serious side effects. This research project is motivated by the potentially numerous applications of techniques that have been recently developed by the “Bioinformatics and High Performance Computing” (BIO-HPC) research group and collaborators, and from the promising results obtained. Applying state-of-the-art computational drug discovery methods BIO-HPC group has discovered a compound that, working as heparin cofactor, binds with nanomolar affinity to antithrombin causing partial activation, and which paves the way for the discovery of novel anticoagulants based on its molecular structure.
The main aim of this project is to implement and apply an improved integrated computational-experimental strategy for the discovery of bioactive compounds that uses for the first time hybrid mathematical and artificial intelligence techniques on High Performance Computing architectures, in addition to advanced computational drug discovery methods.
If successful, the range of applicability of this methodology will cover any other drug discovery campaign. As proof of concept we will show its application for the discovery of novel anticoagulants. These results can form the basis of an attractive new generation of drug discovery approaches.
Anil Thapa (Iceland)
Title : “Nordic HPC collaboration and HPC activities in Iceland”
The concept of conventional system operation of large High Performance Computing operations, where all hardware is close to users, administartors and researchers, has changed in recent years. With the evolving high-speed network connection between the countries, such hardware can be hosted away from users, system administartors and researchers, which are transparent to the system.National High Performance Computing centers of Denmark, Norway, Sweden and Iceland own and have operated jointly a supercomputer in Iceland to share computational resources across countiry boundaries.
Nordic HPC has set an example, particularly in Iceland where other individual HPC operation group has joined in centeral HPC operation and collaborations. Computing services of the University of Iceland has been playing an integral role by providing HPC support across nordic region and hosting HPC infrastructure.This presentation will give an overview of the Nordic HPC project collaboration, HPC activities in the university of Iceland, lesson learned and future collaboration in HPC projects.
Steinar Henden (Norway)
Title: “Norwegian Computational Infrastrucutre and HPC in the Arctic”
The Norwegian infrastructure for High Performance computing (HPC) and computational science is to provide a modern, national HPC infrastructure in an internationa and competitive setting, and stimulate compuattional science as the third scientific path.
UIT The Arctic University of Norway is the northernmost university of the world.The Arctic is of increasing global importance. Climate change, the exploitation of Arctic resources and environmental threats are topics of great public concern, and which the UiT takes special interest in. An overview of NOTUR, the HPC activity in Norway, and some aspects of running a HPC center in the arctic region will be given.
Eysteinn Már Sigurðsson (Iceland)
Title: “GPU Implementation of Iterative Constrained Endmember Extraction from Remotely Sensed Hyperspectral Images”
The iterated constrained endmembers (ICE) algorithm is an iterative method that uses the liner model to extract endmembers and abundances simultaneously from hyperspectral images. This apporach does not necessarily require the presence of pixels in the hyperspectral image as it can automatically derive the signatures of endmembers even if these signatures are not present in the data.
As it is the case with other endmember identification algorithms, ICE suffers from high computational complexity. Using GPU’s, significant speed increase is archived over the traditional ICE method and allows for processing of larger data set with an increased number of endmembers.
Os agradecemos vuestra asistencia y si podéis darle difusión al evento.
Horacio Pérez-Sánchez, PhD
Bioinformatics and High Performance Computing Research Group
Universidad Católica San Antonio de Murcia (UCAM), Spain