对切换时间进行性能分析非常困难，但是内核内延迟性能分析工具以及oprofile（可以对内核本身进行性能分析）将为您提供帮助。
为了对交互式应用程序的性能进行基准测试，我编写了一个名为latencybench的小工具，用于测量意外的延迟峰值：
// Compile with g++ latencybench.cc -o latencybench -lboost_thread-mt// Should also work on MSVC and other platforms supported by Boost.#include <boost/format.hpp>#include <boost/thread/thread.hpp>#include <boost/date_time.hpp>#include <algorithm>#include <cstdlib>#include <csignal>volatile bool m_quit = false;extern "C" void sighandler(int) { m_quit = true;}std::string num(unsigned val) { if (val == 1) return "one occurrence"; return boost::lexical_cast<std::string>(val) + " occurrences";}int main(int argc, char** argv) { using namespace boost::posix_time; std::signal(SIGINT, sighandler); std::signal(SIGTERM, sighandler); time_duration duration = milliseconds(10); if (argc > 1) { try { if (argc != 2) throw 1; unsigned ms = boost::lexical_cast<unsigned>(argv[1]); if (ms > 1000) throw 2; duration = milliseconds(ms); } catch (...) { std::cerr << "Usage: " << argv[0] << " milliseconds" << std::endl; return EXIT_FAILURE; } } typedef std::map<long, unsigned> Durations; Durations durations; unsigned samples = 0, wrongsamples = 0; unsigned max = 0; long last = -1; std::cout << "Measuring actual sleep delays when requesting " << duration.total_milliseconds() << " ms: (Ctrl+C when done)" << std::endl; ptime begin = boost::get_system_time(); while (!m_quit) { ptime start = boost::get_system_time(); boost::this_thread::sleep(start + duration); long actual = (boost::get_system_time() - start).total_milliseconds(); ++samples; unsigned num = ++durations[actual]; if (actual != last) { std::cout << "r " << actual << " ms " << std::flush; last = actual; } if (actual != duration.total_milliseconds()) { ++wrongsamples; if (num > max) max = num; std::cout << "spike at " << start - begin << std::endl; last = -1; } } if (samples == 0) return 0; std::cout << "rTotal measurement duration: " << boost::get_system_time() - begin << "n"; std::cout << "Number of samples collected: " << samples << "n"; std::cout << "Incorrect delay count: " << wrongsamples << boost::format(" (%.2f %%)") % (100.0 * wrongsamples / samples) << "nn"; std::cout << "Histogram of actual delays:nn"; unsigned correctsamples = samples - wrongsamples; const unsigned line = 60; double scale = 1.0; char ch = '+'; if (max > line) { scale = double(line) / max; ch = '*'; } double correctscale = 1.0; if (correctsamples > line) correctscale = double(line) / correctsamples; for (Durations::const_iterator it = durations.begin(); it != durations.end(); ++it) { std::string bar; if (it->first == duration.total_milliseconds()) bar = std::string(correctscale * it->second, '>'); else bar = std::string(scale * it->second, ch); std::cout << boost::format("%5d ms | %s %d") % it->first % bar % it->second << std::endl; } std::cout << "n"; std::string indent(30, ' '); std::cout << indent << "+-- Legend ----------------------------------n"; std::cout << indent << "| > " << num(1.0 / correctscale) << " (of " << duration.total_milliseconds() << " ms delay)n"; if (wrongsamples > 0) std::cout << indent << "| " << ch << " " << num(1.0 / scale) << " (of any other delay)n";}在Ubuntu 2.6.32-14-通用内核上的结果。在测量时，我正在编译具有四个核心的C ++代码，并同时玩OpenGL图形游戏（使之更有趣）：
Total measurement duration: 00:01:45.191465Number of samples collected: 10383Incorrect delay count: 196 (1.89 %)Histogram of actual delays: 10 ms | >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> 10187 11 ms | *************************************************** 70 12 ms | ************************************************************ 82 13 ms | ********* 13 14 ms | ********* 13 15 ms | ** 4 17 ms | *** 5 18 ms | * 2 19 ms | **** 6 20 ms | 1 +-- Legend ---------------------------------- | > 169 occurrences (of 10 ms delay) | * one occurrence (of any other delay)
使用rt修补的内核，我可以获得更好的结果，仅10-12 ms。
打印输出中的图例似乎存在舍入错误或某些错误（并且粘贴的源代码不是完全相同的版本）。我从未真正完善过此应用程序的发行版…
