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 0 291 0.000
fib_iter 8 912 0.008
modules 2 174 0.010
fib_recursive 11 903 0.012
asdl_generated 7 367 0.020
scoped_resource 40 1,029 0.039
containers 4 100 0.039
parse 30 756 0.039
files 7 69 0.108
tuple_return_value 20 184 0.110
length 42 195 0.213
cartesian 79 333 0.236
classes 3 11 0.286
escape 104 357 0.293
cgi 265 509 0.520
control_flow 205 112 1.827
varargs 31 12 2.609

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
parse 3.8 7.6 0.50
escape 3.5 6.9 0.51
fib_iter 3.5 6.9 0.51
asdl_generated 3.7 7.1 0.52
scoped_resource 3.7 7.1 0.52
tuple_return_value 3.7 7.1 0.52
cartesian 3.7 6.9 0.53
cgi 3.7 6.9 0.53
control_flow 3.7 6.9 0.53
modules 3.7 6.9 0.53
loops 3.8 7.1 0.54
files 3.8 6.9 0.55
length 3.8 6.9 0.55
fib_recursive 3.8 6.8 0.56
containers 28.7 47.8 0.60
varargs 5.6 6.8 0.83

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
classes 0 19 0.000
escape 0 4 0.000
files 0 8 0.000
modules 0 8 0.000
parse 0 12 0.000
tuple_return_value 0 8 0.000
asdl_generated 4 12 0.300
length 4 12 0.317
containers 12 36 0.322
loops 4 8 0.461
cgi 4 8 0.500
varargs 35 60 0.587
control_flow 4 4 0.984
scoped_resource 8 8 0.994
cartesian 12 0 inf
fib_iter 0 0 NA
fib_recursive 0 0 NA

raw benchmark files