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_recursive gen 7 887 0.008
fib_iter gen 8 882 0.009
modules gen 2 182 0.010
loops gen 4 295 0.014
asdl_generated gen 7 384 0.019
containers gen 4 113 0.035
parse gen 29 768 0.038
scoped_resource gen 44 1,030 0.042
files gen 4 74 0.053
tuple_return_value gen 20 184 0.109
classes gen 3 28 0.117
length gen 41 205 0.199
gc_stack_roots gen 2 9 0.209
cartesian gen 87 327 0.267
escape gen 103 348 0.297
cgi gen 265 510 0.520
varargs gen 17 16 1.036
control_flow gen 209 107 1.950

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
cartesian gen 3.5 7.1 0.50
gc_stack_roots gen 3.5 7.1 0.50
parse gen 3.8 7.6 0.50
loops gen 3.7 7.2 0.51
scoped_resource gen 3.5 6.9 0.51
modules gen 3.7 7.1 0.52
cgi gen 3.7 6.9 0.53
escape gen 3.7 6.9 0.53
fib_recursive gen 3.7 6.9 0.53
tuple_return_value gen 3.7 6.9 0.53
fib_iter gen 3.8 7.1 0.54
asdl_generated gen 3.7 6.8 0.54
files gen 3.8 6.9 0.55
length gen 3.8 6.8 0.56
control_flow gen 3.9 6.9 0.57
containers gen 28.6 47.7 0.60
varargs gen 5.5 6.9 0.79

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
classes gen 0 4 0.000
control_flow gen 0 8 0.000
fib_iter gen 0 16 0.000
gc_stack_roots gen 0 4 0.000
loops gen 0 4 0.000
modules gen 0 4 0.000
parse gen 0 12 0.000
tuple_return_value gen 0 12 0.000
cartesian gen 4 12 0.331
scoped_resource gen 4 12 0.332
containers gen 12 28 0.425
cgi gen 4 8 0.504
varargs gen 50 56 0.888
asdl_generated gen 4 4 0.903
fib_recursive gen 4 4 0.916
escape gen 4 4 0.992
files gen 4 4 1.011
length gen 4 4 1.032

raw benchmark files