Oncode GPU infrastructure to enable Artificial Intelligence and Deep Learning applications (NKI)
Keywords: large and complex datasets, using AI
Contact person: Anastassis Perrakis
For more information about access, please contact Anastassis Perrakis through the Oncode community platform.
How it can help you
A distributed GPU infrastructure to enable Artificial Intelligence and Deep Learning applications in Cancer Genomics, Proteomics, and Structural Cell Biology. The revolution in AI technology is based on parallelizable algorithms and is thus largely driven by Graphical Processor Units (GPU). Unlike Central Processing Units (CPUs), which are rather limited in the number of concurrent executions of software commands (threads), GPUs process thousands of threads in parallel, opening opportunities for many novel AI applications.
Oncode therefore supports a GPU cluster, distributed amongst three Oncode institutes. This distributed infrastructure with common login and job execution procedures, ensures immediate local availability to enable new science, provides a testbed for distributed (cloud, grid, federated) computing, allows to evaluate solutions for data security/privacy and storage, ensures local extensibility, and offers the possibility to leverage local resources for Oncode use.
For further information, please contact Jacqueline Staring, programme manager at Oncode.