Shadow Profiling Hiding Instrumentation Costs with Parallelism

In profiling, a tradeoff exists between information and overhead. For example, hardware-sampling profilers incur negligible overhead, but the information they collect is consequently very coarse. Other profilers use instrumentation tools to gather temporal traces such as path profiles and hot memory...

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Vydáno v:Proceedings of the International Symposium on Code Generation and Optimization s. 198 - 208
Hlavní autoři: Moseley, Tipp, Shye, Alex, Reddi, Vijay Janapa, Grunwald, Dirk, Peri, Ramesh
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: Washington, DC, USA IEEE Computer Society 11.03.2007
IEEE
Edice:ACM Conferences
Témata:
Computer science
Cost function
Environmental management
General and reference > Cross-computing tools and techniques > Performance
Hardware
Instruments
Operating systems
Optimizing compilers
Parallel processing
Runtime
Sampling methods
Software and its engineering > Software creation and management > Software verification and validation > Operational analysis
Software and its engineering > Software notations and tools > Compilers
Software and its engineering > Software notations and tools > Compilers > Runtime environments
Software and its engineering > Software notations and tools > Compilers > Source code generation
Theory of computation > Models of computation > Concurrency
Theory of computation > Models of computation > Concurrency > Parallel computing models
ISBN:9780769527642, 0769527647
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Shrnutí:In profiling, a tradeoff exists between information and overhead. For example, hardware-sampling profilers incur negligible overhead, but the information they collect is consequently very coarse. Other profilers use instrumentation tools to gather temporal traces such as path profiles and hot memory streams, but they have high overhead. Runtime and feedback-directed compilation systems need detailed information to aggressively optimize, but the cost of gathering profiles can outweigh the benefits. Shadow profiling is a novel method for sampling long traces of instrumented code in parallel with normal execution, taking advantage of the trend of increasing numbers of cores. Each instrumented sample can be many millions of instructions in length. The primary goal is to incur negligible overhead, yet attain profile information that is nearly as accurate as a perfect profile. The profiler requires no modifications to the operating system or hardware, and is tunable to allow for greater coverage or lower overhead. We evaluate the performance and accuracy of this new profiling technique for two common types of instrumentation-based profiles: interprocedural path profiling and value profiling. Overall, profiles collected using the shadow profiling framework are 94% accurate versus perfect value profiles, while incurring less than 1% overhead. Consequently, this technique increases the viability of dynamic and continuous optimization systems by hiding the high overhead of instrumentation and enabling the online collection of many types of profiles that were previously too costly.
Bibliografie:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:9780769527642
0769527647
DOI:10.1109/CGO.2007.35