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 0 184 0.000
fib_iter 8 893 0.009
loops 4 296 0.012
fib_recursive 11 870 0.012
asdl_generated 11 379 0.028
parse 25 757 0.034
scoped_resource 39 1,021 0.038
tuple_return_value 16 190 0.084
files 8 73 0.109
containers 12 105 0.111
classes 3 26 0.122
length 41 212 0.192
cartesian 90 347 0.258
escape 99 349 0.283
cgi 264 517 0.510
varargs 20 12 1.704
control_flow 208 107 1.938

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
fib_recursive 3.5 6.9 0.51
asdl_generated 3.7 7.1 0.52
scoped_resource 3.7 7.1 0.52
cartesian 3.7 6.9 0.53
fib_iter 3.7 6.9 0.53
escape 3.7 6.8 0.54
cgi 3.8 6.9 0.55
control_flow 3.8 6.9 0.55
files 3.8 6.9 0.55
length 3.8 6.9 0.55
loops 3.8 6.9 0.55
tuple_return_value 3.8 6.9 0.55
modules 3.9 6.8 0.58
containers 28.5 48.0 0.59
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
cartesian 0 4 0.000
classes 0 4 0.000
control_flow 0 4 0.000
fib_iter 0 4 0.000
fib_recursive 0 12 0.000
files 0 4 0.000
loops 0 8 0.000
containers 4 28 0.137
parse 4 16 0.265
varargs 45 60 0.750
scoped_resource 8 8 0.973
cgi 4 4 0.997
tuple_return_value 4 4 1.013
escape 8 4 1.970
length 4 0 inf
modules 2 0 inf

raw benchmark files