Universities and hospitals like TGen and NMTRC are seeing an entirely new reality in patient care leveraging HPC clusters. Here are some success stories on on advances in personalized medicine.
“An increasing number of GPU enabled applications are available to the HPC community. The key issues are understanding the enhanced application performance and corresponding increase in power consumption due to GPUs. In most cases these depend on the CPU to GPU ratio and the way GPUs and connected to CPUs. Latest compute node designs allow flexibility to select the number of GPUs and how they are connected CPUs. This offers users a unique opportunity to select the a suitable operating point according to their application characteristics. This talk is about studying the performance vs. power tradeoff on a few common HPC applications.”
The University of Cambridge plans to transition their HPC workloads to Intel’s Xeon Phi co-processors. The deal will see Intel work along with Dell staff to upgrade the high performance infrastructure used to serve research departments within the university, working in areas such as genomics and astronomy, as well as a growing number of businesses with large compute demands.