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 19 0.000
fib_iter gen 8 898 0.008
modules gen 2 173 0.010
fib_recursive gen 11 871 0.012
loops gen 4 285 0.013
asdl_generated gen 7 374 0.019
scoped_resource gen 43 1,016 0.042
parse gen 37 768 0.048
containers gen 10 102 0.096
tuple_return_value gen 20 186 0.108
files gen 8 69 0.110
length gen 44 199 0.223
cartesian gen 86 323 0.267
escape gen 95 350 0.272
gc_stack_roots gen 2 4 0.442
cgi gen 248 496 0.500
varargs gen 16 24 0.677
control_flow gen 210 109 1.926

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 4.6 10.9 0.42
cartesian gen 3.5 6.9 0.51
cgi 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
fib_recursive gen 3.7 7.1 0.52
parse gen 3.9 7.5 0.53
asdl_generated gen 3.7 6.9 0.53
control_flow gen 3.8 7.1 0.54
fib_iter gen 3.8 7.1 0.54
scoped_resource gen 3.8 7.1 0.54
escape gen 3.7 6.8 0.54
files gen 3.8 6.9 0.55
loops gen 3.9 7.1 0.56
tuple_return_value gen 3.9 7.1 0.56
modules 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
control_flow gen 0 4 0.000
fib_iter gen 0 8 0.000
fib_recursive gen 0 8 0.000
files gen 0 8 0.000
gc_stack_roots gen 0 8 0.000
length gen 0 8 0.000
loops gen 0 4 0.000
modules gen 0 8 0.000
parse gen 0 12 0.000
tuple_return_value gen 0 8 0.000
containers gen 5 33 0.150
cgi gen 4 16 0.252
classes gen 3 11 0.277
asdl_generated gen 4 8 0.448
cartesian gen 4 8 0.514
varargs gen 48 48 1.016
escape gen 12 8 1.494
scoped_resource gen 4 0 inf

raw benchmark files