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Pleasures and Pitfalls of Profiling

Pleasures and Pitfalls of Profiling. Primož Gabrijelčič. What? When? How?. What Is profiling?. A form of dynamic analysis that measures some aspect of the program execution, typically: Memory usage Resource usage Frequency and duration of function calls. When to profile?.

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Pleasures and Pitfalls of Profiling

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  1. Pleasures and Pitfalls of Profiling Primož Gabrijelčič

  2. What? When? How?

  3. What Is profiling? • A form of dynamic analysis that measures some aspect of the program execution, typically: • Memory usage • Resource usage • Frequency and duration of function calls

  4. When to profile? “We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil. Yet we should not pass up our opportunities in that critical 3%.” -Donald Knuth

  5. Tools • “Optimization by guesswork” – bad! • Hardcoded time measurement and logging • Profilers

  6. Profilers • Sampling (statistical) • Instrumenting • Source instrumenting • Code instrumenting • (Event based) • (Hypervisor)

  7. Tools

  8. AQTime • smartbear.com/products/development-tools/performance-profiling/ • Delphi, C++ Builder, .NET (incl. Silverlight), Java … • Integration with RAD Studio and Visual Studio – D2006 and newer • 32- and 64- bit • Comes with XE and XE2 (limited version) • $ 599

  9. AQTime • Performance profiler • Allocation (memory) profiler • Coverage profiler • Static analysis profiler • Load library tracer profiler • More …

  10. ProDelphi • www.prodelphi.de • Delphi 5 – XE2 • 32- and 64- bit • Very precise profiling • Free version (20 procedures) • Separate Ansi and Unicode version • Separate 32- and 64- bit version • 50 – 90 €

  11. Sampling Profiler • delphitools.info/samplingprofiler • Delphi 5 – XE (officially), works with XE2 • Measures time spent in OS DLLs • Works at line level • Real-time monitor • Free

  12. DIY • Home-brewed timing and logging • GetTickCount • Now • timeGetTime • QueryPerformanceCounter • RDTSC

  13. Fixing performance problems

  14. Fixing performance problems • Better algorithm  • Less memory allocations • Less string manipulations • Using different Windows controls • Faster code  • Code optimization • Handcrafted assembler; using MMX/SSE • Assembler tricks will not make up for bad design, however, they can make good design go faster.

  15. Profiler FAIL • Distributed algorithms (GUI, messaging) are hard to profile • Optimizing the inner code of an infinite loop doesn’t help • If time is spent in kernel, reason may be hard to find

  16. Hands-on!

  17. Questions?

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