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 24 0.000
loops gen 0 283 0.000
fib_recursive gen 7 849 0.008
fib_iter gen 7 850 0.008
asdl_generated gen 4 358 0.010
modules gen 2 164 0.010
parse gen 28 732 0.038
scoped_resource gen 45 1,006 0.045
containers gen 8 110 0.069
tuple_return_value gen 19 181 0.105
files gen 7 66 0.111
length gen 31 202 0.152
cartesian gen 81 310 0.260
escape gen 101 352 0.287
cgi gen 233 484 0.480
varargs gen 12 16 0.729
control_flow gen 188 102 1.842
gc_stack_roots gen 2 0 inf

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 3.8 7.6 0.50
cartesian gen 3.5 6.9 0.51
gc_stack_roots gen 3.5 6.9 0.51
loops gen 3.7 7.1 0.52
asdl_generated gen 3.7 6.9 0.53
cgi gen 3.7 6.9 0.53
escape gen 3.7 6.9 0.53
fib_iter gen 3.7 6.9 0.53
fib_recursive gen 3.7 6.9 0.53
scoped_resource gen 3.8 7.1 0.54
control_flow gen 3.8 6.9 0.55
files gen 3.8 6.9 0.55
length gen 3.8 6.9 0.55
modules gen 3.8 6.9 0.55
tuple_return_value gen 3.8 6.9 0.55
containers gen 28.6 47.8 0.60
varargs gen 5.5 7.1 0.78

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
fib_iter gen 0 8 0.000
files gen 0 8 0.000
gc_stack_roots gen 0 11 0.000
modules gen 0 12 0.000
parse gen 0 8 0.000
scoped_resource gen 0 8 0.000
tuple_return_value gen 0 4 0.000
fib_recursive gen 3 12 0.280
loops gen 3 12 0.291
containers gen 8 20 0.385
cgi gen 8 12 0.673
classes gen 3 4 0.752
varargs gen 50 52 0.972
asdl_generated gen 7 4 1.801
control_flow gen 8 4 1.960
length gen 12 4 2.843
cartesian gen 8 0 inf
escape gen 0 0 NA

raw benchmark files