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
loops gen 0 290 0.000
fib_iter gen 4 900 0.004
modules gen 2 178 0.010
fib_recursive gen 11 877 0.012
asdl_generated gen 5 375 0.015
parse gen 26 770 0.033
scoped_resource gen 44 1,032 0.042
containers gen 8 122 0.065
tuple_return_value gen 16 182 0.089
files gen 8 65 0.116
gc_stack_roots gen 2 12 0.145
classes gen 3 19 0.169
length gen 41 204 0.203
varargs gen 4 15 0.253
cartesian gen 87 329 0.265
escape gen 103 359 0.286
cgi gen 254 528 0.481
control_flow gen 208 113 1.844

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 4.3 10.8 0.40
gc_stack_roots gen 3.4 6.9 0.49
parse gen 3.8 7.7 0.49
cartesian gen 3.5 7.1 0.50
tuple_return_value gen 3.5 7.1 0.50
cgi gen 3.5 6.9 0.51
scoped_resource gen 3.7 7.1 0.52
loops gen 3.8 7.2 0.53
asdl_generated gen 3.7 6.9 0.53
escape gen 3.7 6.9 0.53
length gen 3.8 7.1 0.54
fib_iter gen 3.7 6.8 0.54
control_flow gen 3.8 6.9 0.55
modules gen 3.8 6.9 0.55
fib_recursive gen 3.8 6.8 0.56
files gen 3.9 6.9 0.57
containers gen 28.5 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
cgi gen 0 4 0.000
classes gen 0 12 0.000
control_flow gen 0 4 0.000
fib_recursive gen 0 8 0.000
files gen 0 11 0.000
modules gen 0 4 0.000
parse gen 4 12 0.306
tuple_return_value gen 4 12 0.341
containers gen 8 20 0.400
cartesian gen 4 8 0.500
length gen 4 8 0.518
asdl_generated gen 5 8 0.683
loops gen 4 4 0.904
escape gen 4 4 0.988
scoped_resource gen 4 4 0.993
varargs gen 63 58 1.081
fib_iter gen 4 0 inf
gc_stack_roots gen 0 0 NA

raw benchmark files