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 8 898 0.009
modules gen 2 184 0.011
fib_recursive gen 11 888 0.012
loops gen 4 296 0.013
asdl_generated gen 11 383 0.028
scoped_resource gen 32 1,033 0.031
parse gen 26 767 0.034
files gen 4 72 0.052
containers gen 8 120 0.067
tuple_return_value gen 21 184 0.113
classes gen 3 24 0.137
length gen 44 203 0.219
gc_stack_roots gen 2 8 0.246
cartesian gen 90 327 0.277
escape gen 99 342 0.289
varargs gen 8 16 0.478
cgi gen 270 508 0.532
control_flow gen 201 112 1.797

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 10.6 0.42
gc_stack_roots gen 3.4 6.9 0.49
parse gen 3.8 7.6 0.50
cartesian gen 3.5 6.9 0.51
cgi gen 3.5 6.9 0.51
modules gen 3.5 6.9 0.51
asdl_generated gen 3.7 7.1 0.52
scoped_resource gen 3.7 7.1 0.52
loops gen 3.8 7.2 0.53
files gen 3.7 6.9 0.53
fib_iter gen 3.8 7.1 0.54
escape gen 3.7 6.8 0.54
control_flow gen 3.8 6.9 0.55
fib_recursive gen 3.8 6.9 0.55
tuple_return_value gen 3.8 6.9 0.55
length gen 3.9 6.9 0.57
containers gen 28.5 47.8 0.59
varargs gen 5.4 6.9 0.77

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
cartesian gen 0 4 0.000
cgi gen 0 8 0.000
classes gen 0 8 0.000
fib_iter gen 0 4 0.000
gc_stack_roots gen 0 4 0.000
length gen 0 8 0.000
loops gen 0 4 0.000
modules gen 0 8 0.000
tuple_return_value gen 0 8 0.000
containers gen 8 20 0.400
escape gen 8 12 0.664
parse gen 4 4 0.919
files gen 4 4 0.932
varargs gen 59 57 1.024
control_flow gen 8 4 1.974
scoped_resource gen 16 8 2.004
asdl_generated gen 0 0 NA
fib_recursive gen 0 0 NA

raw benchmark files