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 8 881 0.009
asdl_generated 4 368 0.010
modules 2 188 0.010
fib_recursive 11 895 0.012
loops 4 293 0.013
parse 26 762 0.034
scoped_resource 44 1,021 0.043
containers 8 110 0.072
tuple_return_value 16 193 0.084
files 8 64 0.118
classes 3 22 0.151
length 45 214 0.212
cartesian 87 326 0.266
escape 98 347 0.283
cgi 262 511 0.512
varargs 15 20 0.770
control_flow 206 112 1.829

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
asdl_generated 3.5 7.1 0.50
cartesian 3.5 7.1 0.50
length 3.5 7.1 0.50
scoped_resource 3.7 7.1 0.52
cgi 3.7 6.9 0.53
tuple_return_value 3.7 6.9 0.53
loops 3.8 7.1 0.54
escape 3.7 6.8 0.54
control_flow 3.8 6.9 0.55
fib_iter 3.8 6.9 0.55
fib_recursive 3.8 6.9 0.55
files 3.8 6.9 0.55
modules 3.8 6.9 0.55
containers 28.7 47.8 0.60
varargs 5.5 6.9 0.79

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
classes 0 9 0.000
fib_iter 0 12 0.000
fib_recursive 0 12 0.000
files 0 12 0.000
length 0 12 0.000
containers 8 25 0.325
scoped_resource 4 12 0.331
parse 4 8 0.455
cartesian 4 8 0.489
cgi 4 8 0.497
asdl_generated 7 8 0.894
varargs 50 52 0.963
escape 8 8 1.028
control_flow 4 0 inf
tuple_return_value 4 0 inf
loops 0 0 NA
modules 0 0 NA

raw benchmark files