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
classes gen 0 31 0.000
modules gen 0 180 0.000
fib_iter gen 4 889 0.004
fib_recursive gen 7 885 0.008
loops gen 4 293 0.013
asdl_generated gen 11 377 0.030
parse gen 25 768 0.033
scoped_resource gen 48 1,026 0.046
containers gen 8 110 0.073
tuple_return_value gen 13 185 0.073
files gen 8 71 0.107
gc_stack_roots gen 2 12 0.155
length gen 36 200 0.181
cartesian gen 83 330 0.251
escape gen 102 356 0.287
cgi gen 246 511 0.482
varargs gen 31 32 0.972
control_flow gen 204 106 1.918

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 7.1 0.50
files gen 3.5 6.9 0.51
gc_stack_roots gen 3.5 6.9 0.51
parse gen 3.9 7.6 0.52
fib_iter gen 3.7 7.1 0.52
scoped_resource gen 3.7 7.1 0.52
asdl_generated gen 3.7 6.9 0.53
fib_recursive gen 3.7 6.9 0.53
modules gen 3.7 6.9 0.53
loops gen 3.8 7.1 0.54
cgi gen 3.7 6.8 0.54
escape gen 3.7 6.8 0.54
control_flow gen 3.9 6.9 0.57
length gen 3.9 6.9 0.57
tuple_return_value gen 3.9 6.9 0.57
containers gen 28.6 47.8 0.60
varargs gen 5.5 6.9 0.79

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
asdl_generated gen 0 8 0.000
files gen 0 12 0.000
loops gen 0 4 0.000
scoped_resource gen 0 12 0.000
containers gen 8 24 0.328
fib_recursive gen 4 8 0.451
modules gen 2 4 0.462
fib_iter gen 4 8 0.477
control_flow gen 4 8 0.508
tuple_return_value gen 7 8 0.858
varargs gen 35 40 0.875
length gen 8 8 1.003
escape gen 4 4 1.023
parse gen 4 4 1.047
cartesian gen 8 4 1.961
cgi gen 8 4 1.989
classes gen 3 0 inf
gc_stack_roots gen 0 0 NA

raw benchmark files