Random sampling with a reservoir
ACM Transactions on Mathematical Software (TOMS)
Proceedings of the 29th annual ACM/IEEE international symposium on Microarchitecture
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Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
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SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Proceedings of the ACM SIGPLAN 1999 conference on Programming language design and implementation
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PLDI '00 Proceedings of the ACM SIGPLAN 2000 conference on Programming language design and implementation
A framework for reducing the cost of instrumented code
Proceedings of the ACM SIGPLAN 2001 conference on Programming language design and implementation
Efficient and flexible value sampling
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Software profiling for hot path prediction: less is more
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Rapid profiling via stratified sampling
ISCA '01 Proceedings of the 28th annual international symposium on Computer architecture
Interprocedural Path Profiling
CC '99 Proceedings of the 8th International Conference on Compiler Construction, Held as Part of the European Joint Conferences on the Theory and Practice of Software, ETAPS'99
Optimizing Java Bytecode Using the Soot Framework: Is It Feasible?
CC '00 Proceedings of the 9th International Conference on Compiler Construction
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We present an efficient online subpath profiling algorithm, OSP, that reports hot subpaths executed by a program in a given run. The hot subpaths can start at arbitrary basic block boundaries, and their identification is important for code optimization; e.g., to locate program traces in which optimizations could be most fruitful, and to help programmers in identifying performance bottlenecks.The OSP algorithm is online in the sense that it reports at any point during execution the hot subpaths as observed so far. It has very low memory and runtime overheads, and exhibits high accuracy in reports for benchmarks such as JLex and FFT. These features make the OSP algorithm potentially attractive for use in just-in-time (JIT) optimizing compilers, in which profiling performance is crucial and it is useful to locate hot subpaths as early as possible.The OSP algorithm is based on an adaptive sampling technique that makes effective utilization of memory with small overhead. Both memory and runtime overheads can be controlled, and the OSP algorithm can therefore be used for arbitrarily large applications, realizing a tradeoff between report accuracy and performance.We have implemented a Java prototype of the OSP algorithm for Java programs. The implementation was tested on programs from the Java Grande benchmark suite and exhibited a low average runtime overhead.