An operating system for multicore and clouds: mechanisms and implementation

By David Wentzlaff, Charles Gruenwald, N. Beckmann, Kevin Modzelewski, A. Belay, Lamia Youseff, Jason E. Miller, Anant Agarwal. 2010

116 citations recorded by the source corpus.

Cloud computers and multicore processors are two emerging classes of computational hardware that have the potential to provide unprecedented compute capacity to the average user. In order for the user to effectively harness all of this computational power, operating systems (OSes) for these new hardware platforms are needed. Existing multicore operating systems do not scale to large numbers of cores, and do not support clouds. Consequently, current day cloud systems push much complexity onto the user, requiring the user to manage individual Virtual Machines (VMs) and deal with many system-level concerns. In this work we describe the mechanisms and implementation of a factored operating system named fos. fos is a single system image operating system across both multicore and Infrastructure as a Service (IaaS) cloud systems. fos tackles OS scalability challenges by factoring the OS into its component system services. Each system service is further factored into a collection of Internet-inspired servers which communicate via messaging. Although designed in a manner similar to distributed Internet services, OS services instead provide traditional kernel services such as file systems, scheduling, memory management, and access to hardware. fos also implements new classes of OS services like fault tolerance and demand elasticity. In this work, we describe our working fos implementation, and provide early performance measurements of fos for both intra-machine and inter-machine operations.

Subfields: Evaluation & Benchmarks

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1. Aakanksha Chowdhery
2. Ruoming Pang
3. Ryan Sepassi
4. Yonghui Wu
5. Joseph Dean

Citations in the corpus

• Pathways: Asynchronous Distributed Dataflow for ML (2022, background): “For example, general-purpose virtualization enables cloud applications to efficiently share multi-tenant resources with performance isolation (Angel et al., 2014; Wentzlaff et al., 2010; Shahrad and Wentzlaff, 2016; Baumann et al., 2009), but cloud providers dedicate accelerators to individual users.”
• Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks (2020, background): “In fact, the broader research community invested more than a decade of efforts to develop solutions across the computing stack to bring forth seamless and scalable multi-tenant cloud execution models [26–48].”
• Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud (2011, background): “The FOS project [28] recently presented an operating system for multicore and clouds which is also capable of on-demand VM allocation.”