Paper Info
Title
Persistent Code Caching: Exploiting Code Reuse Across Executions and Applications
Abstract
Run-time compilation systems are challenged with the task of translating a program's instruction stream while maintaining low overhead. While software managed code caches are utilized to amortize translation costs, they are ineffective for programs with short run times or large amounts of cold code. Such program characteristics are prevalent in real-life computing environments, ranging from Graphical User Interface (GUI) programs to large-scale applications such as database management systems. Persistent code caching addresses these issues. It is described and evaluated in an industry-strength dynamic binary instrumentation system - Pin. The proposed approach improves the intra-execution model of code reuse by storing and reusing translations across executions, thereby achieving inter-execution persistence. Dynamically linked programs leverage inter-application persistence by using persistent translations of library code generated by other programs. New translations discovered across executions are automatically accumulated into the persistent code caches, thereby improving performance over time. Inter-execution persistence improves the performance of GUI applications by nearly 90%, while inter-application persistence achieves a 59% improvement. In more specialized uses, the SPEC2K INT benchmark suite experiences a 26% improvement under dynamic binary instrumentation. Finally, a 400% speedup is achieved in translating the Oracle database in a regression testing environment.
Year
DOI
Venue
2007
10.1109/CGO.2007.29
San Jose, CA
Keywords
Field
DocType
persistent code cache,persistent code caching,exploiting code reuse,programs leverage inter-application persistence,cold code,inter-execution persistence,inter-application persistence,persistent translation,library code,code cache,code reuse,graphical user interfaces,database management system,application software,graphical user interface,testing,code generation,regression testing,databases,user interface
Managed code,Source code,Reuse,Computer science,Parallel computing,Redundant code,Regression testing,Code reuse,Application software,Operating system,Speedup
Conference
ISBN
Citations 
PageRank 
0-7695-2764-7
11
0.60
References 
Authors
22
4
Name
Order
Citations
PageRank
Vijay Janapa Reddi12931140.26
Dan Connors226416.78
Robert Cohn333131.29
Michael D. Smith427320.12