mycpp Code Generation

Measure the speedup from mycpp, and the resource usage.

Source code: oil/mycpp/examples

User Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
classes gen 0 16 0.000
fib_iter gen 8 902 0.008
modules gen 2 183 0.010
fib_recursive gen 11 880 0.013
loops gen 4 288 0.013
asdl_generated gen 11 375 0.029
scoped_resource gen 36 1,031 0.034
parse gen 29 774 0.038
files gen 4 75 0.050
tuple_return_value gen 17 194 0.086
containers gen 10 112 0.088
length gen 41 210 0.195
cartesian gen 72 348 0.206
gc_stack_roots gen 2 8 0.216
escape gen 103 354 0.290
cgi gen 270 499 0.541
varargs gen 23 24 0.975
control_flow gen 212 109 1.943

Max Resident Set Size (MB)

Lower ratios are better. We use MB (powers of 10), not MiB (powers of 2).

example name gen C++ Python C++ : Python
classes gen 4.5 10.8 0.41
parse gen 3.8 7.6 0.50
scoped_resource gen 3.5 7.1 0.50
asdl_generated gen 3.5 6.9 0.51
cartesian gen 3.5 6.9 0.51
cgi gen 3.5 6.9 0.51
loops gen 3.7 7.1 0.52
escape gen 3.7 6.9 0.53
gc_stack_roots gen 3.7 6.9 0.53
modules gen 3.7 6.9 0.53
tuple_return_value gen 3.7 6.9 0.53
fib_iter gen 3.8 6.9 0.55
control_flow gen 3.8 6.8 0.56
files gen 3.8 6.8 0.56
length gen 3.8 6.8 0.56
fib_recursive gen 3.9 6.9 0.57
containers gen 28.8 47.8 0.60
varargs gen 5.5 6.9 0.79

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
asdl_generated gen 0 4 0.000
cgi gen 0 8 0.000
control_flow gen 0 8 0.000
fib_iter gen 0 4 0.000
fib_recursive gen 0 4 0.000
gc_stack_roots gen 0 4 0.000
loops gen 0 8 0.000
modules gen 0 4 0.000
parse gen 0 12 0.000
classes gen 3 16 0.205
containers gen 5 24 0.206
tuple_return_value gen 3 4 0.829
varargs gen 43 48 0.894
scoped_resource gen 12 12 0.989
length gen 4 4 1.015
escape gen 4 4 1.021
cartesian gen 20 0 inf
files gen 4 0 inf

raw benchmark files