This can be used to compute the cost of coroutine operations. In the
end the cost of the function call is a few clock cycles, so it's pretty
cheap for now, but it may become more relevant as the coroutine code
is optimized.
For example, here are the results on my machine:
Function call
100000000 iterations: 0.173884 s
Yield
100000000 iterations: 8.445064 s
Lifecycle
1000000 iterations: 0.098445 s
Nesting 10000 iterations of 1000 depth each: 7.406431 s
One yield takes 83 nanoseconds, one enter takes 97 nanoseconds,
one coroutine allocation takes (roughly, since some of the allocations
in the nesting test do hit the pool) 739 nanoseconds:
(8.445064 - 0.173884) * 10^9 /
100000000 = 82.7
(0.098445 * 100 - 0.173884) * 10^9 /
100000000 = 96.7
(7.406431 * 10 - 0.173884) * 10^9 /
100000000 = 738.9
Signed-off-by: Paolo Bonzini <pbonzini@redhat.com>
Reviewed-by: Stefan Hajnoczi <stefanha@redhat.com>
Signed-off-by: Kevin Wolf <kwolf@redhat.com>
maxcycles, duration);
}
+static __attribute__((noinline)) void dummy(unsigned *i)
+{
+ (*i)--;
+}
+
+static void perf_baseline(void)
+{
+ unsigned int i, maxcycles;
+ double duration;
+
+ maxcycles = 100000000;
+ i = maxcycles;
+
+ g_test_timer_start();
+ while (i > 0) {
+ dummy(&i);
+ }
+ duration = g_test_timer_elapsed();
+
+ g_test_message("Function call %u iterations: %f s\n",
+ maxcycles, duration);
+}
+
int main(int argc, char **argv)
{
g_test_init(&argc, &argv, NULL);
g_test_add_func("/perf/lifecycle", perf_lifecycle);
g_test_add_func("/perf/nesting", perf_nesting);
g_test_add_func("/perf/yield", perf_yield);
+ g_test_add_func("/perf/function-call", perf_baseline);
}
return g_test_run();
}