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 gen C++ Python C++ : Python
containers gen 0 115 0.000
fib_iter gen 8 886 0.009
modules gen 2 176 0.011
fib_recursive gen 11 921 0.012
loops gen 4 287 0.014
asdl_generated gen 8 390 0.019
parse gen 30 794 0.037
scoped_resource gen 43 1,071 0.040
tuple_return_value gen 16 185 0.089
files gen 8 69 0.117
classes gen 3 24 0.141
length gen 41 205 0.198
cartesian gen 79 323 0.245
escape gen 107 344 0.312
cgi gen 247 513 0.481
varargs gen 20 20 0.963
control_flow gen 204 116 1.759
gc_stack_roots gen 2 0 inf

Max Resident Set Size (MB)

Lower ratios are better. We use MB (powers of 10), not MiB (powers of 2).

example name gen C++ Python C++ : Python
classes gen 4.5 10.7 0.41
cartesian gen 3.5 6.9 0.51
gc_stack_roots gen 3.5 6.9 0.51
length gen 3.5 6.9 0.51
parse gen 3.9 7.6 0.52
loops gen 3.7 7.1 0.52
asdl_generated gen 3.7 6.9 0.53
cgi gen 3.7 6.9 0.53
control_flow gen 3.7 6.9 0.53
escape gen 3.7 6.9 0.53
files gen 3.7 6.9 0.53
modules gen 3.7 6.9 0.53
tuple_return_value gen 3.7 6.9 0.53
fib_recursive gen 3.8 7.1 0.54
scoped_resource gen 3.8 6.9 0.55
fib_iter gen 3.9 7.1 0.56
containers gen 28.7 47.7 0.60
varargs gen 5.5 6.9 0.79

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
classes gen 0 8 0.000
escape gen 0 8 0.000
fib_iter gen 0 8 0.000
files gen 0 8 0.000
gc_stack_roots gen 0 13 0.000
loops gen 0 12 0.000
modules gen 0 8 0.000
parse gen 0 12 0.000
asdl_generated gen 4 8 0.469
tuple_return_value gen 4 8 0.510
length gen 4 8 0.514
containers gen 16 24 0.681
varargs gen 47 53 0.888
cartesian gen 12 12 0.991
cgi gen 8 4 1.986
control_flow gen 4 0 inf
scoped_resource gen 4 0 inf
fib_recursive gen 0 0 NA

raw benchmark files