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 22 0.000
fib_iter gen 4 895 0.004
fib_recursive gen 7 876 0.008
loops gen 4 431 0.009
modules gen 2 178 0.011
asdl_generated gen 11 376 0.030
scoped_resource gen 39 1,048 0.038
parse gen 30 767 0.039
files gen 4 68 0.055
containers gen 14 127 0.107
varargs gen 4 35 0.111
tuple_return_value gen 21 186 0.112
length gen 41 209 0.197
gc_stack_roots gen 2 7 0.268
cartesian gen 91 329 0.278
escape gen 103 343 0.300
cgi gen 254 508 0.500
control_flow gen 213 103 2.064

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
parse gen 3.7 7.6 0.48
gc_stack_roots gen 3.5 7.1 0.50
asdl_generated gen 3.7 7.1 0.52
scoped_resource gen 3.7 7.1 0.52
cartesian gen 3.7 6.9 0.53
escape gen 3.7 6.9 0.53
modules gen 3.7 6.9 0.53
control_flow gen 3.8 7.1 0.54
fib_recursive gen 3.8 7.1 0.54
files gen 3.8 7.1 0.54
cgi gen 3.8 6.9 0.55
fib_iter gen 3.8 6.9 0.55
length gen 3.8 6.9 0.55
loops gen 3.8 6.9 0.55
tuple_return_value gen 3.9 7.1 0.56
containers gen 28.6 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 4 0.000
cartesian gen 0 8 0.000
cgi gen 0 4 0.000
control_flow gen 0 12 0.000
gc_stack_roots gen 0 7 0.000
modules gen 0 4 0.000
parse gen 0 12 0.000
tuple_return_value gen 0 8 0.000
containers gen 3 16 0.213
classes gen 3 11 0.311
fib_iter gen 4 12 0.321
fib_recursive gen 4 8 0.454
files gen 4 8 0.471
escape gen 4 8 0.497
varargs gen 63 39 1.604
length gen 4 0 inf
scoped_resource gen 8 0 inf
loops gen 0 0 NA

raw benchmark files