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
modules 0 179 0.000
fib_iter 8 899 0.009
fib_recursive 11 874 0.013
loops 4 288 0.014
asdl_generated 11 382 0.029
containers 4 118 0.033
parse 26 770 0.034
scoped_resource 43 1,017 0.043
files 8 73 0.103
tuple_return_value 20 187 0.108
classes 3 22 0.153
length 37 203 0.182
escape 95 351 0.269
cartesian 91 327 0.279
varargs 8 27 0.291
cgi 267 511 0.523
control_flow 210 112 1.879

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
scoped_resource 3.5 7.1 0.50
parse 3.8 7.5 0.51
asdl_generated 3.7 7.1 0.52
escape 3.7 7.1 0.52
files 3.7 7.1 0.52
cartesian 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
cgi 3.8 6.9 0.55
control_flow 3.8 6.9 0.55
fib_iter 3.8 6.9 0.55
length 3.8 6.9 0.55
tuple_return_value 3.9 6.9 0.57
containers 28.6 47.8 0.60
varargs 5.6 6.9 0.81

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
cartesian 0 4 0.000
classes 0 9 0.000
control_flow 0 4 0.000
fib_iter 0 8 0.000
fib_recursive 0 8 0.000
files 0 4 0.000
loops 0 8 0.000
tuple_return_value 0 8 0.000
scoped_resource 4 16 0.271
modules 2 4 0.522
containers 12 20 0.578
parse 4 4 0.927
cgi 4 4 0.999
varargs 59 46 1.275
length 8 4 2.028
escape 12 4 3.093
asdl_generated 0 0 NA

raw benchmark files