Publication
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, Salt Lake City, UT, USA, November 2016
MeteoSwiss, the Swiss national weather forecast institute, has selected densely populated accelerator servers as their primary system to compute weather forecast simulation. Servers with multiple accelerator devices that are primarily connected by a PCI-Express (PCIe) network achieve a significantly higher energy efficiency. Memory transfers between accelerators in such a system are subjected to PCIe arbitration policies. In this paper, we study the impact of PCIe topology and develop a congestion-aware performance model for PCIe communication. We present an algorithm for computing congestion factors of every communication in a congestion graph that characterizes the dynamic usage of network resources by an application. Our model applies to any PCIe tree topology. Our validation results on two different topologies of 8 GPU devices demonstrate that our model achieves an accuracy of over 97% within the PCIe network. We demonstrate the model on a weather forecast application to identify the best algorithms for its communication patterns among GPUs.
@inproceedings{abc, abstract = {MeteoSwiss, the Swiss national weather forecast institute, has selected densely populated accelerator servers as their primary system to compute weather forecast simulation. Servers with multiple accelerator devices that are primarily connected by a PCI-Express (PCIe) network achieve a significantly higher energy efficiency. Memory transfers between accelerators in such a system are subjected to PCIe arbitration policies. In this paper, we study the impact of PCIe topology and develop a congestion-aware performance model for PCIe communication. We present an algorithm for computing congestion factors of every communication in a congestion graph that characterizes the dynamic usage of network resources by an application. Our model applies to any PCIe tree topology. Our validation results on two different topologies of 8 GPU devices demonstrate that our model achieves an accuracy of over 97\% within the PCIe network. We demonstrate the model on a weather forecast application to identify the best algorithms for its communication patterns among GPUs.}, author = {Maxime Martinasso and Grzegorz Kwasniewski and Sadaf R. Alam}, booktitle = {Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis}, title = {A PCIe congestion-aware performance model for densely populated accelerator servers}, venue = {Salt Lake City, UT, USA}, year = {2016} }