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 20 0.000
fib_recursive 7 970 0.008
fib_iter 8 880 0.009
modules 2 178 0.010
loops 4 283 0.014
asdl_generated 11 378 0.030
parse 26 801 0.032
scoped_resource 44 1,036 0.042
files 7 74 0.101
containers 12 113 0.104
tuple_return_value 20 185 0.109
length 33 204 0.164
cartesian 85 353 0.239
escape 102 363 0.281
cgi 237 515 0.461
varargs 16 20 0.778
control_flow 210 111 1.899

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 4.3 10.7 0.40
parse 3.8 7.7 0.49
cartesian 3.5 6.9 0.51
cgi 3.5 6.9 0.51
scoped_resource 3.7 7.1 0.52
asdl_generated 3.7 6.9 0.53
escape 3.7 6.9 0.53
files 3.7 6.9 0.53
length 3.7 6.9 0.53
loops 3.7 6.9 0.53
fib_recursive 3.8 7.1 0.54
modules 3.8 7.1 0.54
fib_iter 3.8 6.9 0.55
tuple_return_value 3.8 6.9 0.55
control_flow 3.9 6.9 0.57
containers 28.4 47.7 0.60
varargs 5.5 6.9 0.79

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
asdl_generated 0 4 0.000
control_flow 0 4 0.000
fib_iter 0 8 0.000
files 0 4 0.000
loops 0 12 0.000
modules 0 4 0.000
tuple_return_value 0 8 0.000
containers 4 27 0.144
classes 3 12 0.276
fib_recursive 4 12 0.313
scoped_resource 4 12 0.332
parse 4 4 0.925
varargs 52 53 0.973
escape 4 4 0.984
length 11 8 1.397
cgi 16 8 2.015
cartesian 8 0 inf

raw benchmark files