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Open source cloud technologies provide a wide range of support for creatingcustomized compute node clusters to schedule tasks and managing resources. Incloud infrastructures such as Jetstream and Chameleon, which are used forscientific research, users receive complete control of the Virtual Machines(VM) that are allocated to them. Importantly, users get root access to the VMs.This provides an opportunity for HPC users to experiment with new resourcemanagement technologies such as Apache Mesos that have proven scalability,flexibility, and fault tolerance. To ease the development and deployment of HPCtools on the cloud, the containerization technology has matured and is gaininginterest in the scientific community. In particular, several well knownscientific code bases now have publicly available Docker containers. WhileMesos provides support for Docker containers to execute individually, it doesnot provide support for container inter-communication or orchestration of thecontainers for a parallel or distributed application. In this paper, we presentthe design, implementation, and performance analysis of a Mesos framework,Scylla, which integrates Mesos with Docker Swarm to enable orchestration of MPIjobs on a cluster of VMs acquired from the Chameleon cloud [1]. Scylla usesDocker Swarm for communication between containerized tasks (MPI processes) andApache Mesos for resource pooling and allocation. Scylla allows a policy-drivenapproach to determine how the containers should be distributed across the nodesdepending on the CPU, memory, and network throughput requirement for eachapplication.

Scylla: A Mesos Framework for Container Based MPI Jobs