Speaker
Description
With the increase of power and reduction of cost of GPU accelerated processors a corresponding interest in their uses in the scientific domain has spurred. OSG users are no different and they have shown an interest in accessing GPU resources via their usual workload infrastructures. Grid sites that have these kinds of resources also want to make them grid available. In this talk, we discuss the software and infrastructure challenges and limitations of the OSG implementations to make GPU’s widely accessible over the grid. Two use cases are considered for this. First: Icecube, a big VO with a well-curated software stack taking advantage of GPUs with OpenCL. Second, a more general approach to supporting the grid use of industry and academia maintained machine learning libraries like Tensorflow, and keanos on the grid using Singularity.
