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 8 883 0.009
modules 2 185 0.010
fib_recursive 11 873 0.012
loops 4 300 0.012
asdl_generated 11 371 0.029
parse 25 768 0.033
scoped_resource 44 1,021 0.043
files 4 68 0.054
tuple_return_value 16 185 0.087
containers 12 105 0.114
classes 3 27 0.118
length 37 201 0.185
escape 98 351 0.279
cartesian 92 328 0.280
varargs 8 20 0.402
cgi 266 508 0.524
control_flow 207 106 1.955

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 10.8 0.40
parse 3.8 7.6 0.50
asdl_generated 3.5 6.9 0.51
cartesian 3.5 6.9 0.51
loops 3.8 7.2 0.53
cgi 3.7 6.9 0.53
escape 3.7 6.9 0.53
modules 3.7 6.9 0.53
tuple_return_value 3.7 6.9 0.53
scoped_resource 3.8 7.1 0.54
control_flow 3.8 6.9 0.55
fib_iter 3.8 6.9 0.55
files 3.8 6.9 0.55
fib_recursive 3.8 6.8 0.56
length 3.9 6.9 0.57
containers 28.8 47.8 0.60
varargs 5.5 7.1 0.78

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
asdl_generated 0 8 0.000
cartesian 0 8 0.000
classes 0 4 0.000
fib_iter 0 8 0.000
fib_recursive 0 12 0.000
loops 0 4 0.000
containers 4 28 0.141
files 4 8 0.459
scoped_resource 4 8 0.495
cgi 4 8 0.504
tuple_return_value 4 8 0.510
control_flow 4 8 0.517
length 7 8 0.942
escape 8 8 0.981
parse 4 4 1.061
varargs 60 52 1.159
modules 0 0 NA

raw benchmark files