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| Content Provider | ACM Digital Library |
|---|---|
| Author | Dwarkadas, Sandhya Zhang, Chengliang Ogihara, Mitsunori Scott, Michael L. Ding, Chen Shen, Xipeng |
| Abstract | Utility programs, which perform similar and largely independent operations on a sequence of inputs, include such common applications as compilers, interpreters, and document parsers; databases; and compression and encoding tools. The repetitive behavior of these programs, while often clear to users, has been difficult to capture automatically. We present an active profiling technique in which controlled inputs to utility programs are used to expose execution phases, which are then marked, automatically, through binary instrumentation, enabling us to exploit phase transitions in production runs with arbitrary inputs. We demonstrate the effectiveness and programmability of active profiling via experiments with six utility programs from the SPEC benchmark suite; compare to code and interval phases; and describe applications of active profiling to memory management and memory leak detection. |
| File Format | |
| ISBN | 9781595937513 |
| DOI | 10.1145/1281700.1281705 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2007-06-13 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Active profiling Memory management Dynamic optimization Program phase analysis and prediction |
| Content Type | Text |
| Resource Type | Article |
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