Remote specialization for efficient embedded operating systems

  • Authors:
  • Sapan Bhatia;Charles Consel;Calton Pu

  • Affiliations:
  • Princeton University;LaBRI/INRIA;Georgia Institute of Technology

  • Venue:
  • ACM Transactions on Programming Languages and Systems (TOPLAS)
  • Year:
  • 2008

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Abstract

Prior to their deployment on an embedded system, operating systems are commonly tailored to reduce code size and improve runtime performance. Program specialization is a promising match for this process: it is predictable and modules, and it allows the reuse of previously implemented specializations. A specialization engine for embedded systems must overcome three main obstacles: (i) Reusing existing compilers for embedded systems, (ii) supporting specialization on a resource-limited system and (iii) coping with dynamic applications by supporting specialization on demand. In this article, we describe a runtime specialization infrastructure that addresses these problems. Our solution proposes: (i) Specialization in two phases of which the former generates specialized C templates and the latter uses a dedicated compiler to generate efficient native code. (ii) A virtualization mechanism that facilitates specialization of code at a remote location. (iii) An API and supporting OS extensions that allow applications to produce, manage and dispose of specialized code. We evaluate our work through two case studies: (i) The TCP/IP implementation of Linux and (ii) The TUX embedded web server. We report appreciable improvements in code size and performance. We also quantify the overhead of specialization and argue that a specialization server can scale to support a sizable workload.