|Title||Argo NodeOS: Toward Unified Resource Management for Exascale |
|Publication Type||Conference Paper |
|Year of Publication||2017 |
|Authors||Perarnau, S, Zounmevo, JA, Dreher, M, Van Essen, B |
|Conference Name||International Parallel and Distributed Processing Symposium (IPDPS) |
|Date Published||07/2017 |
|Other Numbers||ANL/MCS-P7010-0217 |
|Abstract||Exascale systems are expected to feature hundreds of thousands of compute nodes with hundreds of hardware threads
and complex memory hierarchies with a mix of on-package and persistent memory modules.
In this context, the Argo project is developing a new operating system for exascale machines. Targeting production workloads using workflows or coupled codes, we improve the Linux kernel on several fronts. We extend the memory management of Linux to be able to subdivide NUMA memory nodes, allowing better resource partitioning among processes running on the same node. We also add support for memory-mapped access to node-local, PCIe-attached NVRAM devices and introduce a new scheduling class targeted at parallel runtimes supporting user-level load balancing. These features are unified into compute containers, a containerization approach focused on providing modern HPC applications with dynamic control over a wide range of kernel interfaces. To keep our approach compatible with industrial containerization products, we also identify contentions points for the adoption of containers in HPC settings.
Each NodeOS feature is evaluated by using a set of parallel benchmarks, miniapps, and coupled applications consisting of
simulation and data analysis components, running on a modern NUMA platform. We observe out-of-the-box performance improvements easily matching, and often exceeding, those observed with expert-optimized configurations on standard OS kernels. Our lightweight approach to resource management retains the many benefits of a full OS kernel that application programmers have learned to depend on, at the same time providing a set of extensions that can be freely mixed and matched to best benefit particular application components. |