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_recursive 8 907 0.008
fib_iter 8 889 0.009
modules 2 182 0.010
loops 4 290 0.013
asdl_generated 11 393 0.029
parse 30 788 0.038
scoped_resource 44 1,079 0.041
tuple_return_value 21 191 0.109
files 8 66 0.115
containers 16 102 0.156
classes 3 20 0.168
length 37 203 0.183
cartesian 91 332 0.274
escape 101 349 0.289
cgi 265 521 0.509
varargs 19 33 0.598
control_flow 211 101 2.082

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
cartesian 3.5 7.1 0.50
parse 3.8 7.5 0.51
asdl_generated 3.5 6.9 0.51
cgi 3.7 6.9 0.53
control_flow 3.7 6.9 0.53
escape 3.7 6.9 0.53
loops 3.7 6.9 0.53
scoped_resource 3.7 6.9 0.53
fib_iter 3.8 6.9 0.55
fib_recursive 3.8 6.9 0.55
files 3.8 6.9 0.55
length 3.8 6.9 0.55
modules 3.8 6.9 0.55
tuple_return_value 3.8 6.9 0.55
containers 28.6 47.8 0.60
varargs 5.6 6.8 0.83

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
asdl_generated 0 4 0.000
classes 0 12 0.000
containers 0 37 0.000
control_flow 0 12 0.000
fib_iter 0 8 0.000
files 0 12 0.000
loops 0 4 0.000
modules 0 4 0.000
parse 0 8 0.000
tuple_return_value 0 4 0.000
fib_recursive 4 8 0.475
length 7 8 0.932
escape 4 4 0.966
cgi 4 4 1.003
varargs 47 41 1.147
scoped_resource 4 0 inf
cartesian 0 0 NA

raw benchmark files