AESOP: Expressing Concurrency in High-Performance System Software

TitleAESOP: Expressing Concurrency in High-Performance System Software
Publication TypeConference Paper
Year of Publication2012
AuthorsKimpe, D, Carns, PH, Harms, K, Wozniak, JM, Lang, S, Ross, RB
Conference NameNetworking, Architecture and Storage (NAS)
Date Published06/2012
Other NumbersANL/MCS-P2068-0312

High-performance computing (HPC) and distributed systems rely on a diverse collection of system software to provide application services, including file systems, schedulers, and web services. Such system software services must manage highly concurrent requests, interact with a wide range of resources, and scale well in order to be successful. Unfortunately, no single programming model for distributed system software currently offers optimal performance and productivity for all these tasks. While numerous libraries, languages, and language extensions have been developed in recent years to simplify parallel computation, they do not address the challenges of distributed system software in which concurrency control involves a variety of hardware and network devices, not just computational resources. In this work we present AESOP, a new programming language and programming model designed to implement distributed system software with high development productivity and run-time efficiency. AESOP is a superset of the C language that describes blocks of code to be executed concurrently without dictating whether that concurrency will be provided by a threading, event, or other model. This decoupling enables system software to adjust to different architectures, device APIs, and workloads without any change to the core algorithm implementation. AESOP also provides additional language constructs to simplify common system software development tasks. We evaluate AESOP by implementing a basic file server and comparing its performance, memory efficiency, and developer productivity with several thread-based and event-based implementations. AESOP is shown to provide competitive performance to traditional distributed system software development models while at the same time reducing code complexity and enhancing developer productivity.