“In this session we describe how GPUs can be used within virtual environments with near-native performance. We begin by showing GPU performance across four hypervisors: VMWare ESXi, KVM, Xen, and LXC. After showing that performance characteristics of each platform, we extend the results to the multi-node case with nodes interconnected by QDR InfiniBand. We demonstrate multi-node GPU performance using GPUDirect-enabled MPI, achieving efficiencies of 97-99% of a non-virtualized system.”
The Fastway Store on the UberCloud Marketplace is designed to provide exclusive training classes specifically designed to teach participants how to use the latest Computer Aided Engineering (CAE) software on the cloud for Designers and Design Engineers. “Never before has a more complete curriculum been created to bring newcomers into the world of Computer Aided Engineering (CAE) and High Performance Computing.” says Fastway Engineering’s managing director, Jim Shaw.
Today ANSYS announced that the company is making its flagship engineering simulation software available on the cloud via Amazon Web Services. The new ANSYS Enterprise Cloud running on AWS enables customers to scale their simulation capacity – including infrastructure and software assets – on demand, in response to changing business requirements, optimizing efficiency and cost while responding to the growing demand for wider use of the technology.
“Based on a containerized HPC environment this talk shows of a state-of-the-art stack including performance monitoring, log event handling and GraphDB based inventory to provide insights into what is going on within a SLURM cluster. The framework used is QNIBTerminal incorporating the ELK stack, a graphite backend and neo4j as a GraphDB.”
Today the Square Kilometre Array (SKA) Organization announced that it is teaming up with Amazon Web Services (AWS) to use cloud computing to explore ever-increasing amounts of astronomy data. To kick things off, they just issued a Call for Proposals for AstroCompute in the Cloud, a grant program to accelerate the development of innovative tools and techniques for processing, storing and analyzing the global astronomy community’s vast amounts of astronomic data.