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 0 289 0.000
fib_iter gen 8 1,052 0.007
modules gen 2 181 0.010
fib_recursive gen 11 912 0.012
asdl_generated gen 11 370 0.029
parse gen 25 767 0.032
scoped_resource gen 46 993 0.047
tuple_return_value gen 12 184 0.063
containers gen 7 107 0.069
files gen 7 67 0.110
classes gen 3 22 0.148
gc_stack_roots gen 2 8 0.219
length gen 45 202 0.221
cartesian gen 81 307 0.265
escape gen 98 346 0.285
cgi gen 264 520 0.509
varargs gen 19 24 0.790
control_flow gen 203 112 1.810

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 10.8 0.40
gc_stack_roots gen 3.4 6.9 0.49
parse gen 3.8 7.6 0.50
escape gen 3.5 6.9 0.51
fib_iter gen 3.5 6.9 0.51
asdl_generated gen 3.7 6.9 0.53
cartesian gen 3.7 6.9 0.53
length gen 3.7 6.9 0.53
modules gen 3.7 6.9 0.53
scoped_resource gen 3.7 6.9 0.53
cgi gen 3.8 7.1 0.54
loops gen 3.8 7.1 0.54
fib_recursive gen 3.8 6.9 0.55
files gen 3.8 6.9 0.55
control_flow gen 3.9 7.1 0.56
tuple_return_value gen 3.9 6.9 0.57
containers gen 28.5 47.8 0.59
varargs gen 5.5 6.9 0.79

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
files gen 0 8 0.000
gc_stack_roots gen 0 4 0.000
length gen 0 8 0.000
scoped_resource gen 0 12 0.000
parse gen 4 12 0.345
containers gen 7 20 0.374
loops gen 4 8 0.481
escape gen 8 12 0.660
cartesian gen 8 12 0.680
varargs gen 45 48 0.948
tuple_return_value gen 8 8 0.972
cgi gen 4 4 1.002
control_flow gen 0 0 NA
fib_iter gen 0 0 NA
fib_recursive gen 0 0 NA
modules gen 0 0 NA

raw benchmark files