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
fib_iter 8 873 0.009
modules 2 175 0.011
fib_recursive 11 880 0.012
loops 4 293 0.012
asdl_generated 11 379 0.029
parse 29 786 0.037
scoped_resource 43 1,038 0.041
tuple_return_value 16 184 0.087
files 7 69 0.108
containers 12 103 0.119
length 41 205 0.200
cartesian 78 331 0.236
escape 99 350 0.284
cgi 265 523 0.507
varargs 20 15 1.269
control_flow 204 107 1.908

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 10.8 0.41
parse 3.8 7.6 0.50
asdl_generated 3.5 6.9 0.51
cartesian 3.5 6.9 0.51
escape 3.5 6.9 0.51
tuple_return_value 3.5 6.9 0.51
cgi 3.7 6.9 0.53
fib_recursive 3.8 7.1 0.54
loops 3.8 7.1 0.54
scoped_resource 3.8 7.1 0.54
fib_iter 3.8 6.9 0.55
files 3.8 6.9 0.55
modules 3.8 6.9 0.55
length 3.9 6.9 0.57
control_flow 3.9 6.8 0.58
containers 28.5 47.8 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
fib_iter 0 4 0.000
fib_recursive 0 8 0.000
files 0 8 0.000
modules 0 8 0.000
parse 0 12 0.000
containers 4 36 0.114
cgi 4 12 0.335
tuple_return_value 4 8 0.501
control_flow 4 8 0.505
varargs 47 58 0.812
scoped_resource 4 4 0.977
escape 8 8 1.000
length 4 4 1.019
cartesian 12 8 1.467
classes 3 0 inf
loops 0 0 NA

raw benchmark files