Pin: building customized program analysis tools with dynamic instrumentation

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Pin: building customized program analysis tools with dynamic instrumentation (2005)

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by Chi-keung Luk , Robert Cohn , Robert Muth , Harish Patil , Artur Klauser , Geoff Lowney , Steven Wallace , Vijay Janapa Reddi , Kim Hazelwood

Venue:	IN PLDI ’05: PROCEEDINGS OF THE 2005 ACM SIGPLAN CONFERENCE ON PROGRAMMING LANGUAGE DESIGN AND IMPLEMENTATION
Citations:	953 - 34 self

BibTeX

@INPROCEEDINGS{Luk05pin:building,
    author = {Chi-keung Luk and Robert Cohn and Robert Muth and Harish Patil and Artur Klauser and Geoff Lowney and Steven Wallace and Vijay Janapa Reddi and Kim Hazelwood},
    title = {Pin: building customized program analysis tools with dynamic instrumentation},
    booktitle = {IN PLDI ’05: PROCEEDINGS OF THE 2005 ACM SIGPLAN CONFERENCE ON PROGRAMMING LANGUAGE DESIGN AND IMPLEMENTATION},
    year = {2005},
    pages = {190--200},
    publisher = {ACM Press}
}

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Abstract

Robust and powerful software instrumentation tools are essential for program analysis tasks such as profiling, performance evaluation, and bug detection. To meet this need, we have developed a new instrumentation system called Pin. Our goals are to provide easy-to-use, portable, transparent, and efficient instrumentation. Instrumentation tools (called Pintools) are written in C/C++ using Pin’s rich API. Pin follows the model of ATOM, allowing the tool writer to analyze an application at the instruction level without the need for detailed knowledge of the underlying instruction set. The API is designed to be architecture independent whenever possible, making Pintools source compatible across different architectures. However, a Pintool can access architecture-specific details when necessary. Instrumentation with Pin is mostly transparent as the application and Pintool observe the application’s original, uninstrumented behavior. Pin uses dynamic compilation to instrument executables while they are running. For efficiency, Pin uses several techniques, including inlining, register re-allocation, liveness analysis, and instruction scheduling to optimize instrumentation. This fully automated approach delivers significantly better instrumentation performance than similar tools. For example, Pin is 3.3x faster than Valgrind and 2x faster than DynamoRIO for basic-block counting. To illustrate Pin’s versatility, we describe two Pintools in daily use to analyze production software. Pin is publicly available for Linux platforms on four architectures: IA32 (32-bit x86), EM64T (64-bit x86), Itanium R ○ , and ARM. In the ten months since Pin 2 was released in July 2004, there have been over 3000 downloads from its website.

Keyphrases

dynamic instrumentation building customized program analysis tool instruction scheduling performance evaluation detailed knowledge pin rich api instrumentation tool pin versatility subject descriptor new instrumentation system 64-bit x86 tool writer pintools source dynamic compilation access architecture-specific detail liveness analysis production software program analysis task powerful software instrumentation tool linux platform instrumentation performance ten month approach delivers similar tool software engineering underlying instruction debugging-code inspection efficient instrumentation several technique uninstrumented behavior bug detection instruction level different architecture 32-bit x86 basic-block counting daily use

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