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
fib_iter 8 893 0.009
modules 2 179 0.010
fib_recursive 11 877 0.012
loops 4 294 0.013
asdl_generated 11 374 0.029
parse 29 776 0.038
scoped_resource 43 1,029 0.041
containers 8 122 0.065
tuple_return_value 20 190 0.106
files 8 68 0.111
length 41 243 0.167
classes 3 17 0.190
cartesian 87 326 0.266
escape 103 342 0.300
cgi 265 523 0.506
control_flow 200 105 1.906
varargs 29 8 3.583

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 4.5 10.7 0.41
parse 3.8 7.6 0.50
cartesian 3.5 6.9 0.51
asdl_generated 3.7 7.1 0.52
scoped_resource 3.7 7.1 0.52
cgi 3.7 6.9 0.53
escape 3.7 6.9 0.53
modules 3.7 6.9 0.53
fib_recursive 3.8 7.1 0.54
loops 3.8 7.1 0.54
files 3.8 6.9 0.55
tuple_return_value 3.8 6.9 0.55
control_flow 3.9 7.1 0.56
fib_iter 3.8 6.8 0.56
length 3.9 6.9 0.57
containers 28.7 47.8 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 4 0.000
cgi 0 8 0.000
classes 0 13 0.000
fib_iter 0 4 0.000
fib_recursive 0 4 0.000
files 0 8 0.000
modules 0 8 0.000
parse 0 12 0.000
tuple_return_value 0 4 0.000
escape 4 12 0.330
cartesian 4 8 0.495
length 4 8 0.501
varargs 37 64 0.576
containers 8 12 0.655
scoped_resource 4 4 0.969
control_flow 8 8 1.009
loops 0 0 NA

raw benchmark files