Minimizing Communication Overheads in Containerbased Clouds for HPC Applications Although the industry has embraced the cloud computing model, there are still significant challenges to be addressed concerning the quality of cloud services. Networkintensive 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 readytouse 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 networkintensive applications increased the performance up to 38%, other applications with aggregated NICs maintained the same performance or presented slightly worse performance.

SCinet DTNasaService Framework Transferring big data over Wide Area Networks (WANs) is challenging because optimization is dependent on the specifics of multiple parameters. Network services, paths, and technologies have different characteristics, including loss rate, latency, and available capacity. Yet, frameworks currently used to configure and orchestrate transfer systems, measure performance, and analyze results have limited capabilities. We propose a framework, DTNasaService (DaaS), for highperformance network data transfers using and integration of techniques, including virtualization, network provisioning, and performance data analysis. This framework has a modular design for supporting multiple transfer tools, optimizers and orchestrators for the data transfer environment, including textitDocker and textitKubernetes. We present a textitJupyter based workflow for highspeed network data transfer in dataintensive science and evaluate the performance of the transfer with a simple programmable visualizer implemented in the framework. This framework has been implemented as a prototype at two recent SC supercomputing conferences. With the increase in the number and the capacity of WAN links at the conferences (multiple 100 Gbps WAN circuits), the challenges involved in setting up, testing, debugging, verifying and running applications on highperformance systems connecting to the conference SCinet WAN circuits also increase. The SCinet implementation of the DaaS framework for the conference community allowed users to control hardware, software, and network infrastructure for highspeed network data transfer, primarily for large scale applications. Through the evaluation of the framework in our test setup, we demonstrated that NVMe over Fabrics with TCP is twice as efficient compared to using conventional TCP in highspeed NVMetoNVMe transfers. We also implemented a 400 Gbps LAN experiment to evaluate the DaaS framework.