Section: New Results
Simulation of Large Scale Distributed Systems
Participants : Frédéric Desprez, Jonathan Rouzaud-Cornabas, Frédéric Suter.
Toward Better Simulation of MPI Applications on Ethernet/TCP Networks
Simulation and modeling for performance prediction and profiling is essential for developing and maintaining HPC code that is expected to scale for next-generation exascale systems, and correctly modeling network behavior is essential for creating realistic simulations. In [11] , we proposed an implementation of a flow-based hybrid network model that accounts for factors such as network topology and contention, which are commonly ignored by other approaches. We focused on large-scale, Ethernet-connected systems, as these currently compose 37.8% of the TOP500 index, and this share is expected to increase as higher-speed 10 and 100GbE become more available. The European Mont-Blanc project that studies exascale computing by developing prototype systems with low-power embedded devices will also use Ethernet-based interconnect. Our model is implemented within SMPI, an open-source MPI implementation that connects real applications to the SimGrid simulation framework (cf Section 5.5 ). SMPI provides implementations of collective communications based on current versions of both OpenMPI and MPICH. SMPI and SimGrid also provide methods for easing the simulation of large-scale systems, including shadow execution, memory folding, and support for both online and offline simulation. We validated our proposed model by comparing traces produced by SMPI with those from real world experiments, as well as with those obtained using other established network models. Our study shows that SMPI has a consistently better predictive power than classical LogP-based models for a wide range of scenarios including both established HPC benchmarks and real applications.
SimGrid : a Sustained Effort for the Versatile Simulation of Large Scale Distributed Systems
SimGrid (cf Section 5.5 ) is a toolkit for the versatile simulation of large scale distributed systems, whose development effort has been sustained for the last fifteen years. Over this time period SimGrid has evolved from a one-laboratory project in the U.S. into a scientific instrument developed by an international collaboration. The keys to making this evolution possible have been securing of funding, improving the quality of the software, and increasing the user base. We detailed in [55] how we have been able to make advances on all three fronts, on which we plan to intensify our efforts over the upcoming years.
Simulating Multiple Clouds from a Client Point of View: SGCB an AWS Simulator
Validating a new application over a Cloud is not an easy task and it can be costly over public Clouds. Simulation is a good solution if the simulator is accurate enough and if it provides all the features of the target Cloud. In [49] , we have proposed an extension of the SimGrid simulation toolkit to simulate the Amazon IaaS Cloud. Based on an extensive study of the Amazon platform and previous evaluations, we have integrated models into the SimGrid Cloud Broker and exposed the same API as Amazon to the users. Our experimental results have shown that our simulator is able to simulate different parts of Amazon for different applications.