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 0 287 0.000
fib_iter gen 8 946 0.008
fib_recursive gen 7 879 0.008
modules gen 2 175 0.010
asdl_generated gen 11 376 0.029
parse gen 29 753 0.039
scoped_resource gen 48 1,069 0.045
containers gen 8 115 0.068
tuple_return_value gen 20 190 0.106
classes gen 3 30 0.110
files gen 8 66 0.114
length gen 33 208 0.161
gc_stack_roots gen 2 8 0.212
cartesian gen 87 332 0.263
escape gen 103 349 0.294
cgi gen 262 511 0.512
varargs gen 12 20 0.587
control_flow gen 207 108 1.922

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 10.8 0.41
gc_stack_roots gen 3.4 6.8 0.50
asdl_generated gen 3.5 6.9 0.51
escape gen 3.5 6.9 0.51
parse gen 3.9 7.6 0.52
length gen 3.7 6.9 0.53
scoped_resource gen 3.7 6.9 0.53
cartesian gen 3.5 6.7 0.53
fib_iter gen 3.8 7.1 0.54
fib_recursive gen 3.8 7.1 0.54
loops gen 3.8 7.1 0.54
cgi gen 3.8 6.9 0.55
files gen 3.8 6.9 0.55
tuple_return_value gen 3.8 6.9 0.55
control_flow gen 3.9 7.1 0.56
modules gen 3.8 6.8 0.56
containers gen 28.7 47.8 0.60
varargs gen 5.6 7.1 0.80

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
asdl_generated gen 0 8 0.000
classes gen 0 4 0.000
files gen 0 12 0.000
gc_stack_roots gen 0 4 0.000
modules gen 0 8 0.000
parse gen 0 12 0.000
scoped_resource gen 0 8 0.000
tuple_return_value gen 0 4 0.000
containers gen 8 24 0.331
fib_recursive gen 4 8 0.448
loops gen 4 8 0.477
control_flow gen 4 8 0.509
cgi gen 8 12 0.672
escape gen 4 4 0.984
cartesian gen 4 4 0.991
varargs gen 55 52 1.054
length gen 11 8 1.393
fib_iter gen 0 0 NA

raw benchmark files