User-space Services Research Articles

Enabling Scalable and Extensible Memory-Mapped Datastores in Userspace

Exascale workloads are expected to incorporate data-intensive processing in close coordination with traditional physics simulations. These emerging scientific, data-analytics and machine learning applications need to access a wide variety of datastores in flat files and structured databases. Programmer productivity is greatly enhanced by mapping datastores into the application process's virtual memory space to provide a unified “in-memory” interface. Currently, memory mapping is provided by system software primarily designed for generality and reliability. However, scalability at high concurrency is a formidable challenge on exascale systems. Also, there is a need for extensibility to support new datastores potentially requiring HPC data transfer services. In this article, we present <i>UMap</i> , a scalable and extensible userspace service for memory-mapping datastores. Through decoupled queue management, concurrency aware adaptation, and dynamic load balancing, <i>UMap</i> enables application performance to scale even at high concurrency. We evaluate <i>UMap</i> in data-intensive applications, including sorting, graph traversal, database operations, and metagenomic analytics. Our results show that <i>UMap</i> as a userspace service outperforms an optimized kernel-based service across a wide range of intra-node concurrency by 1.22-1.9 <inline-formula><tex-math notation="LaTeX">${\times}$</tex-math></inline-formula> . We performed two case studies to demonstrate <i>UMap</i> 's extensibility. First, a new datastore residing in remote memory is incorporated into <i>UMap</i> as an application-specific plugin. Second, we present a persistent memory allocator <i>Metall</i> built atop <i>UMap</i> for unified storage/memory.

Predictable and configurable component-based scheduling in the C omposite OS

This article presents the design of user-level scheduling hierarchies in the C omposite component-based system. The motivation for this is centered around the design of a system that is both dependable and predictable, and which is configurable to the needs of specific applications. Untrusted application developers can safely develop services and policies, that are isolated in protection domains outside the kernel. To ensure predictability, C omposite enforces timing control over user-space services. Moreover, it must provide a means by which asynchronous events, such as interrupts, are handled in a timely manner without jeopardizing the system. Towards this end, we describe the features of C omposite that allow user-defined scheduling policies to be composed for the purposes of combined interrupt and task management. A significant challenge arises from the need to synchronize access to shared data structures (e.g., scheduling queues), without allowing untrusted code to disable interrupts. Additionally, efficient upcall mechanisms are needed to deliver asynchronous event notifications in accordance with policy-specific priorities, without undue recourse to schedulers. We show how these issues are addressed in C omposite , by comparing several hierarchies of scheduling polices, to manage both tasks and the interrupts on which they depend. Studies show how it is possible to implement guaranteed differentiated services as part of the handling of I/O requests from a network device while diminishing livelock. Microbenchmarks indicate that the costs of implementing and invoking user-level schedulers in C omposite are on par with, or less than, those in other systems, with thread switches more than twice as fast as in Linux.