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
fib_iter gen 8 891 0.008
modules gen 2 175 0.010
loops gen 4 299 0.012
fib_recursive gen 11 902 0.012
asdl_generated gen 11 377 0.029
parse gen 29 766 0.038
scoped_resource gen 47 1,032 0.046
containers gen 12 122 0.097
tuple_return_value gen 21 182 0.114
files gen 8 67 0.116
classes gen 3 22 0.144
length gen 40 200 0.200
gc_stack_roots gen 2 8 0.209
escape gen 87 357 0.244
cartesian gen 83 326 0.254
varargs gen 8 16 0.487
cgi gen 265 515 0.514
control_flow gen 208 107 1.948

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 10.7 0.40
gc_stack_roots gen 3.5 7.1 0.50
parse gen 3.8 7.6 0.50
cartesian gen 3.5 6.9 0.51
escape gen 3.5 6.9 0.51
cgi gen 3.7 7.1 0.52
loops gen 3.8 7.2 0.53
fib_recursive gen 3.7 6.9 0.53
files gen 3.7 6.9 0.53
length gen 3.8 7.1 0.54
tuple_return_value gen 3.7 6.8 0.54
asdl_generated gen 3.8 6.9 0.55
control_flow gen 3.8 6.9 0.55
fib_iter gen 3.8 6.9 0.55
modules gen 3.8 6.9 0.55
scoped_resource gen 3.8 6.9 0.55
containers gen 28.5 47.7 0.60
varargs gen 5.4 7.1 0.76

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
asdl_generated gen 0 4 0.000
classes gen 0 9 0.000
control_flow gen 0 8 0.000
fib_iter gen 0 4 0.000
fib_recursive gen 0 8 0.000
files gen 0 8 0.000
gc_stack_roots gen 0 4 0.000
loops gen 0 4 0.000
modules gen 0 8 0.000
parse gen 0 12 0.000
scoped_resource gen 0 12 0.000
tuple_return_value gen 0 12 0.000
containers gen 4 20 0.199
cgi gen 4 8 0.499
length gen 4 8 0.511
cartesian gen 8 8 0.991
varargs gen 59 56 1.044
escape gen 20 0 inf

raw benchmark files