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 8 895 0.008
modules gen 2 175 0.010
fib_recursive gen 11 885 0.012
loops gen 4 290 0.013
asdl_generated gen 11 400 0.027
parse gen 29 760 0.038
scoped_resource gen 43 1,030 0.041
tuple_return_value gen 8 191 0.042
files gen 7 72 0.102
containers gen 12 100 0.118
classes gen 3 23 0.141
gc_stack_roots gen 2 8 0.217
length gen 45 205 0.220
cartesian gen 85 332 0.257
escape gen 107 344 0.310
cgi gen 263 514 0.512
control_flow gen 208 111 1.870
varargs gen 29 8 3.629

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 10.9 0.40
fib_recursive gen 3.5 7.1 0.50
asdl_generated gen 3.5 6.9 0.51
cgi 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
cartesian gen 3.7 7.1 0.52
loops gen 3.7 7.1 0.52
escape gen 3.7 6.9 0.53
scoped_resource gen 3.7 6.9 0.53
control_flow gen 3.8 7.1 0.54
tuple_return_value gen 3.8 7.1 0.54
files gen 3.8 6.9 0.55
modules gen 3.8 6.9 0.55
length gen 3.8 6.8 0.56
fib_iter gen 3.9 6.9 0.57
containers gen 28.7 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 8 0.000
control_flow gen 0 4 0.000
escape gen 0 8 0.000
fib_iter gen 0 4 0.000
files gen 0 4 0.000
gc_stack_roots gen 0 4 0.000
length gen 0 4 0.000
loops gen 0 4 0.000
modules gen 0 8 0.000
parse gen 0 16 0.000
containers gen 4 36 0.109
cgi gen 4 8 0.500
scoped_resource gen 4 8 0.533
varargs gen 38 64 0.583
cartesian gen 4 4 1.017
tuple_return_value gen 12 4 3.035
fib_recursive gen 0 0 NA

raw benchmark files