As we look to the future applications for exascale-class computers, the grand science challenges are often first on the list. From modeling the climate to the underpinnings of the universe, the problems most often associated with exascale computing are epic in scope. However, the range of complex, multidisciplinary engineering problems that can be solved with Read more…
<img style=”float: left;” src=”http://media2.hpcwire.com/hpcwire/Hyperscale_small.bmp” alt=”” width=”111″ height=”68″ />Since its inception on June 28, the Uber-Cloud Experiment has attracted over 160 industry and research organizations and individuals from 22 countries. They all have one goal: to jointly explore the end-to-end process of remotely accessing technical computing resources sitting in HPC centers and in the cloud. With Round One of the experiment wrapping up, the organizers have generously provided a “half-time” report of the project.
When it comes to running HPC workloads in the cloud, traditional software licensing models have presented a significant barrier to adoption. But as cloud becomes ever more entrenched, this is starting to change. More and more ISVs have started to experiment with cloud computing and are adjusting their licensing models accordingly.
NVIDIA builds its case for GPU computing.