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
loops gen 0 288 0.000
fib_iter gen 8 891 0.008
modules gen 2 166 0.011
fib_recursive gen 11 880 0.012
asdl_generated gen 11 381 0.028
parse gen 25 785 0.032
scoped_resource gen 43 1,032 0.042
files gen 4 68 0.055
containers gen 8 94 0.083
tuple_return_value gen 20 180 0.111
classes gen 3 22 0.146
length gen 40 212 0.190
gc_stack_roots gen 2 8 0.220
cartesian gen 83 326 0.254
escape gen 97 350 0.277
cgi gen 266 507 0.524
varargs gen 33 20 1.673
control_flow gen 207 102 2.030

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 10.8 0.41
parse gen 3.8 7.7 0.49
cartesian gen 3.5 7.1 0.50
gc_stack_roots gen 3.5 6.9 0.51
scoped_resource gen 3.7 7.1 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
length gen 3.7 6.9 0.53
modules gen 3.7 6.9 0.53
fib_recursive gen 3.8 7.1 0.54
fib_iter gen 3.8 6.9 0.55
files gen 3.8 6.9 0.55
loops gen 3.8 6.9 0.55
tuple_return_value gen 3.8 6.9 0.55
control_flow gen 3.9 7.1 0.56
containers gen 28.5 47.8 0.59
varargs gen 5.5 7.1 0.78

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
asdl_generated gen 0 4 0.000
classes gen 0 9 0.000
control_flow gen 0 16 0.000
fib_iter gen 0 8 0.000
fib_recursive gen 0 4 0.000
gc_stack_roots gen 0 4 0.000
modules gen 0 16 0.000
tuple_return_value gen 0 12 0.000
containers gen 8 39 0.199
parse gen 4 12 0.303
loops gen 4 8 0.464
files gen 4 8 0.465
scoped_resource gen 4 8 0.490
varargs gen 33 51 0.643
cartesian gen 8 8 0.991
cgi gen 4 4 1.008
escape gen 8 0 inf
length gen 4 0 inf

raw benchmark files