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 0 290 0.000
fib_iter gen 4 924 0.004
fib_recursive gen 7 883 0.008
asdl_generated gen 4 379 0.009
modules gen 2 173 0.010
parse gen 26 772 0.033
scoped_resource gen 45 1,024 0.044
tuple_return_value gen 16 184 0.088
files gen 8 68 0.115
classes gen 3 22 0.149
containers gen 17 112 0.149
length gen 40 206 0.196
varargs gen 4 19 0.204
cartesian gen 87 322 0.269
escape gen 104 342 0.305
gc_stack_roots gen 2 4 0.437
cgi gen 246 520 0.473
control_flow gen 208 104 2.001

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
parse gen 3.8 7.7 0.49
escape gen 3.5 6.9 0.51
gc_stack_roots gen 3.5 6.9 0.51
tuple_return_value gen 3.5 6.9 0.51
cartesian gen 3.5 6.8 0.52
asdl_generated gen 3.7 6.9 0.53
cgi gen 3.7 6.9 0.53
control_flow gen 3.7 6.9 0.53
fib_recursive gen 3.7 6.9 0.53
loops gen 3.7 6.9 0.53
fib_iter gen 3.8 7.1 0.54
modules gen 3.7 6.8 0.54
files gen 3.8 6.9 0.55
length gen 3.8 6.9 0.55
scoped_resource gen 3.8 6.9 0.55
containers gen 28.5 47.7 0.60
varargs gen 5.5 6.8 0.81

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
classes gen 0 9 0.000
containers gen 0 24 0.000
control_flow gen 0 12 0.000
escape gen 0 12 0.000
files gen 0 8 0.000
gc_stack_roots gen 0 8 0.000
modules gen 0 12 0.000
parse gen 4 12 0.306
tuple_return_value gen 4 8 0.507
length gen 4 8 0.509
scoped_resource gen 4 8 0.513
cartesian gen 4 8 0.519
fib_recursive gen 4 4 0.899
loops gen 4 4 0.915
varargs gen 62 53 1.168
asdl_generated gen 7 4 1.799
cgi gen 8 0 inf
fib_iter gen 4 0 inf

raw benchmark files