High-Performance Computing (HPC) in the cloud has reached the mainstream and is currently a hot topic in the research community and the industry. The attractiveness of cloud for HPC is the capability to run large applications on powerful, scalable hardware without needing to actually own or maintain this hardware. In this paper, we conduct a detailed comparison of HPC applications running on three cloud providers, Amazon EC2, Microsoft Azure and Rackspace. We analyze three important characteristics of HPC, deployment facilities, performance and cost efficiency and compare them to a cluster of machines.For the experiments, we used the well-known NAS parallel benchmarks as an example of general scientific HPC applications to examine the computational and communication performance. Our results show that HPC applications can run efficiently on the cloud. However, care must be taken when choosing the provider, as the differences between them are large. The best cloud provider depends on the type and behavior of the application, as well as the intended usage scenario. Furthermore, our results show that HPC in the cloud can have a higher performance and cost efficiency than a traditional cluster, up to 27% and 41%, respectively. C OpenMP, MPI LU Lower and Upper Triangular Regular communication Fortran OpenMP, MPI MG Multigrid Regular communication Fortran OpenMP, MPI SP Scalar Pentadiagonal Floating point performance Fortran OpenMP, MPI UA Unstructured Adaptive Irregular communication Fortran OpenMP B. Machines

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Although the industry has embraced the cloud computing model, there are still significant challenges to be addressed concerning the quality of cloud services. Network-intensive applications may not scale in the cloud due to the sharing of the network infrastructure. In the literature, performance evaluation studies are showing that the network tends to limit the scalability and performance of HPC applications. Therefore, we proposed the aggregation of Network Interface Cards (NICs) in a ready-touse integration with the OpenNebula cloud manager using Linux containers. We perform a set of experiments using a network microbenchmark to get specific network performance metrics and NAS parallel benchmarks to analyze the performance impact on HPC applications. Our results highlight that the implementation of NIC aggregation improves network performance in terms of throughput and latency. Moreover, HPC applications have different patterns of behavior when using our approach, which depends on communication and the amount of data transferring. While network-intensive applications increased the performance up to 38%, other applications with aggregated NICs maintained the same performance or presented slightly worse performance.