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 C++ Python C++ : Python
classes 0 31 0.000
modules 0 176 0.000
fib_recursive 7 877 0.008
fib_iter 8 887 0.009
loops 4 303 0.012
asdl_generated 11 371 0.029
parse 29 769 0.038
scoped_resource 43 1,039 0.041
files 4 63 0.059
tuple_return_value 20 190 0.106
containers 12 111 0.107
cartesian 73 343 0.213
length 44 201 0.219
escape 106 370 0.287
varargs 11 28 0.407
cgi 268 509 0.527
control_flow 209 112 1.868

Max Resident Set Size (MB)

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

example name C++ Python C++ : Python
classes 4.6 10.6 0.43
parse 3.8 7.6 0.50
asdl_generated 3.5 6.9 0.51
cartesian 3.5 6.9 0.51
length 3.7 7.1 0.52
loops 3.8 7.2 0.53
control_flow 3.7 6.9 0.53
escape 3.7 6.9 0.53
fib_iter 3.7 6.9 0.53
modules 3.7 6.9 0.53
scoped_resource 3.7 6.9 0.53
tuple_return_value 3.7 6.9 0.53
cgi 3.8 6.9 0.55
files 3.9 7.1 0.56
fib_recursive 3.9 6.9 0.57
containers 28.5 47.7 0.60
varargs 5.6 6.9 0.81

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
asdl_generated 0 8 0.000
cgi 0 12 0.000
control_flow 0 8 0.000
escape 0 8 0.000
fib_iter 0 8 0.000
length 0 12 0.000
loops 0 4 0.000
parse 0 8 0.000
tuple_return_value 0 4 0.000
containers 4 32 0.124
modules 2 8 0.223
files 4 12 0.312
fib_recursive 4 8 0.452
scoped_resource 4 8 0.532
varargs 57 44 1.295
cartesian 16 12 1.359
classes 3 0 inf

raw benchmark files