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 8 890 0.009
modules gen 2 185 0.009
fib_recursive gen 11 883 0.012
loops gen 4 295 0.013
asdl_generated gen 11 380 0.028
parse gen 29 777 0.037
scoped_resource gen 43 1,038 0.041
containers gen 8 117 0.065
files gen 8 75 0.100
tuple_return_value gen 20 189 0.108
classes gen 3 27 0.121
length gen 45 208 0.215
cartesian gen 87 324 0.269
escape gen 97 349 0.279
gc_stack_roots gen 2 4 0.443
cgi gen 269 505 0.533
varargs gen 25 24 1.024
control_flow gen 205 115 1.782

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 10.9 0.41
gc_stack_roots gen 3.4 7.1 0.48
parse gen 3.8 7.6 0.50
cartesian gen 3.7 7.1 0.52
cgi gen 3.7 6.9 0.53
escape gen 3.7 6.9 0.53
fib_iter gen 3.7 6.9 0.53
length gen 3.7 6.9 0.53
loops gen 3.8 7.1 0.54
scoped_resource gen 3.8 7.1 0.54
modules gen 3.7 6.8 0.54
asdl_generated gen 3.8 6.9 0.55
control_flow gen 3.8 6.9 0.55
files gen 3.8 6.9 0.55
tuple_return_value gen 3.8 6.9 0.55
fib_recursive gen 3.8 6.8 0.56
containers gen 28.5 47.8 0.60
varargs gen 5.5 6.8 0.81

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
asdl_generated gen 0 4 0.000
cgi gen 0 12 0.000
classes gen 0 4 0.000
fib_iter gen 0 8 0.000
files gen 0 4 0.000
gc_stack_roots gen 0 8 0.000
length gen 0 8 0.000
loops gen 0 8 0.000
parse gen 0 4 0.000
tuple_return_value gen 0 4 0.000
containers gen 8 16 0.473
scoped_resource gen 4 8 0.484
cartesian gen 4 8 0.496
varargs gen 41 48 0.853
escape gen 8 4 2.025
control_flow gen 0 0 NA
fib_recursive gen 0 0 NA
modules gen 0 0 NA

raw benchmark files