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 0 286 0.000
fib_iter gen 8 927 0.008
modules gen 2 186 0.010
fib_recursive gen 11 896 0.012
asdl_generated gen 11 366 0.030
containers gen 4 118 0.034
parse gen 29 781 0.038
scoped_resource gen 40 1,030 0.038
tuple_return_value gen 17 185 0.091
files gen 7 69 0.109
length gen 42 208 0.202
gc_stack_roots gen 2 8 0.220
cartesian gen 79 327 0.241
escape gen 95 354 0.269
cgi gen 270 509 0.530
varargs gen 12 19 0.608
control_flow gen 208 116 1.794

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 4.6 10.7 0.43
fib_recursive gen 3.5 6.9 0.51
gc_stack_roots gen 3.5 6.9 0.51
parse gen 3.9 7.6 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
loops gen 3.7 6.9 0.53
scoped_resource gen 3.7 6.9 0.53
tuple_return_value gen 3.7 6.9 0.53
files gen 3.8 7.1 0.54
cartesian gen 3.7 6.8 0.54
modules gen 3.7 6.8 0.54
fib_iter gen 3.8 6.9 0.55
length gen 3.8 6.9 0.55
control_flow gen 3.9 6.9 0.57
containers gen 28.6 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 16 0.000
cgi gen 0 8 0.000
fib_recursive gen 0 4 0.000
files gen 0 8 0.000
gc_stack_roots gen 0 4 0.000
modules gen 0 8 0.000
tuple_return_value gen 3 8 0.419
classes gen 4 8 0.470
loops gen 4 8 0.524
containers gen 12 20 0.584
length gen 4 4 0.953
scoped_resource gen 8 8 0.986
varargs gen 55 54 1.014
cartesian gen 12 4 2.960
escape gen 12 4 2.994
control_flow gen 0 0 NA
fib_iter gen 0 0 NA
parse gen 0 0 NA

raw benchmark files