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
fib_iter 8 900 0.008
modules 2 174 0.011
fib_recursive 11 864 0.012
loops 4 290 0.013
asdl_generated 11 377 0.028
parse 25 771 0.033
scoped_resource 44 1,086 0.040
containers 5 111 0.046
tuple_return_value 16 190 0.085
files 8 77 0.100
length 41 204 0.199
classes 3 15 0.211
cartesian 87 330 0.262
escape 102 348 0.294
cgi 265 516 0.513
varargs 23 12 1.974
control_flow 211 102 2.059

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 4.5 10.7 0.41
asdl_generated 3.5 7.1 0.50
cartesian 3.5 7.1 0.50
parse 3.9 7.6 0.52
modules 3.5 6.8 0.52
cgi 3.7 6.9 0.53
escape 3.7 6.9 0.53
length 3.7 6.9 0.53
control_flow 3.8 7.1 0.54
scoped_resource 3.8 7.1 0.54
fib_iter 3.8 6.9 0.55
fib_recursive 3.8 6.9 0.55
loops 3.8 6.9 0.55
tuple_return_value 3.8 6.9 0.55
files 3.8 6.8 0.56
containers 28.8 47.8 0.60
varargs 5.5 6.9 0.79

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
asdl_generated 0 8 0.000
classes 0 15 0.000
control_flow 0 12 0.000
fib_recursive 0 16 0.000
loops 0 8 0.000
modules 0 8 0.000
scoped_resource 4 12 0.329
parse 4 12 0.349
containers 10 25 0.412
length 4 8 0.508
tuple_return_value 4 8 0.512
varargs 43 59 0.724
escape 4 4 0.984
cgi 4 4 1.002
cartesian 4 0 inf
fib_iter 0 0 NA
files 0 0 NA

raw benchmark files