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 C++ Python C++ : Python
loops 0 295 0.000
fib_recursive 7 875 0.008
fib_iter 8 885 0.009
asdl_generated 4 374 0.010
modules 2 179 0.011
parse 29 778 0.038
scoped_resource 44 1,043 0.042
files 4 68 0.057
tuple_return_value 20 192 0.105
containers 15 113 0.135
classes 3 20 0.162
length 40 199 0.200
cartesian 91 323 0.281
escape 99 350 0.283
cgi 246 521 0.472
varargs 12 16 0.738
control_flow 207 106 1.946

Max Resident Set Size (MB)

Lower ratios are better. We use MB (powers of 10), not MiB (powers of 2).

example name C++ Python C++ : Python
classes 4.3 10.7 0.40
parse 3.7 7.6 0.48
cartesian 3.5 6.9 0.51
cgi 3.5 6.9 0.51
asdl_generated 3.7 6.9 0.53
escape 3.7 6.9 0.53
scoped_resource 3.7 6.9 0.53
fib_recursive 3.8 7.1 0.54
loops 3.8 7.1 0.54
files 3.8 6.9 0.55
control_flow 3.7 6.7 0.55
fib_iter 3.9 6.9 0.57
length 3.9 6.9 0.57
modules 3.9 6.9 0.57
tuple_return_value 3.9 6.9 0.57
containers 28.5 47.8 0.60
varargs 5.5 6.9 0.79

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
cartesian 0 8 0.000
classes 0 12 0.000
containers 0 20 0.000
control_flow 0 8 0.000
fib_iter 0 12 0.000
modules 0 4 0.000
parse 0 8 0.000
fib_recursive 4 12 0.300
cgi 4 12 0.330
files 4 8 0.483
scoped_resource 4 8 0.496
length 4 8 0.500
asdl_generated 7 8 0.891
loops 4 4 0.913
varargs 55 56 0.984
escape 8 4 1.967
tuple_return_value 0 0 NA

raw benchmark files