DocumentCode :
3074781
Title :
VMAD: A virtual machine for advanced dynamic analysis of programs
Author :
Jimborean, Alexandra ; Herrmann, Matthieu ; Loechner, Vincent ; Clauss, Philippe
Author_Institution :
LSIIT Lab., Univ. of Strasbourg, Strasbourg, France
fYear :
2011
fDate :
10-12 April 2011
Firstpage :
125
Lastpage :
126
Abstract :
Runtime code analysis and optimization is becoming a main strategy used to face the ever extending and changing variety of processor architectures and execution environments that an application can meet. Particularly with the advent of multicore processors, efficient program optimizations, such as adaptive and speculative parallelism, require accurate and advanced runtime analyses, which inevitably incur a time overhead that has to be minimized. In this paper, we present VMAD, a virtual machine (VM) that handles x86_54 binary files, which are especially tailored at compile time to include instructions and data for code instrumentation and for the VM. VMAD enables low level profiling initiated by the programmer from the source code, through the insertion of a dedicated pragma delimiting the regions of interest. This approach provides the programmer a direct view of the actual execution behavior of the source code. To our knowledge, VMAD is the first proposal providing low-level instrumentation initiated from the source code, with almost negligible runtime overhead.
Keywords :
multiprocessing systems; program compilers; program diagnostics; source coding; virtual machines; VMAD; binary files; code instrumentation; low-level instrumentation; multicore processors; processor architectures; program analysis; program optimization; runtime code analysis; source code; virtual machine for advanced dynamic analysis; Assembly; Benchmark testing; Instruments; Linux; Optimization; Runtime; Virtual machining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Performance Analysis of Systems and Software (ISPASS), 2011 IEEE International Symposium on
Conference_Location :
Austin, TX
Print_ISBN :
978-1-61284-367-4
Electronic_ISBN :
978-1-61284-368-1
Type :
conf
DOI :
10.1109/ISPASS.2011.5762725
Filename :
5762725
Link To Document :
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