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 8 905 0.008
modules gen 2 178 0.010
fib_recursive gen 11 896 0.012
loops gen 4 298 0.012
asdl_generated gen 11 374 0.029
parse gen 25 771 0.033
scoped_resource gen 47 1,043 0.045
containers gen 8 119 0.063
tuple_return_value gen 20 183 0.110
files gen 8 67 0.112
classes gen 4 22 0.167
length gen 45 200 0.222
cartesian gen 86 345 0.249
escape gen 99 349 0.285
cgi gen 263 513 0.511
varargs gen 16 20 0.790
control_flow gen 208 109 1.908
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 4.3 10.7 0.40
gc_stack_roots gen 3.4 7.1 0.48
parse gen 3.7 7.5 0.49
cartesian gen 3.5 6.9 0.51
escape gen 3.5 6.9 0.51
cgi gen 3.7 7.1 0.52
asdl_generated gen 3.7 6.9 0.53
fib_iter gen 3.7 6.9 0.53
length gen 3.7 6.9 0.53
control_flow gen 3.8 7.1 0.54
loops gen 3.8 7.1 0.54
scoped_resource gen 3.8 7.1 0.54
fib_recursive gen 3.8 6.9 0.55
files 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 28.5 47.8 0.60
varargs gen 5.6 6.9 0.81

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
asdl_generated gen 0 8 0.000
classes gen 0 9 0.000
fib_iter gen 0 8 0.000
fib_recursive gen 0 8 0.000
files gen 0 8 0.000
gc_stack_roots gen 0 12 0.000
length gen 0 8 0.000
loops gen 0 4 0.000
modules gen 0 4 0.000
scoped_resource gen 0 8 0.000
tuple_return_value gen 0 8 0.000
containers gen 8 16 0.476
parse gen 4 4 0.909
cartesian gen 4 4 0.974
varargs gen 51 52 0.987
control_flow gen 4 4 0.991
cgi gen 8 8 0.992
escape gen 8 4 1.982

raw benchmark files