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 8 895 0.009
modules 2 198 0.009
fib_recursive 11 887 0.012
loops 4 291 0.013
asdl_generated 7 397 0.018
parse 22 780 0.029
scoped_resource 43 1,047 0.041
files 4 69 0.054
containers 8 118 0.066
tuple_return_value 20 186 0.109
classes 3 15 0.208
length 45 207 0.217
cartesian 91 320 0.285
escape 102 346 0.295
cgi 250 520 0.481
varargs 16 20 0.782
control_flow 208 103 2.026

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
escape 3.5 6.9 0.51
parse 3.9 7.6 0.52
files 3.7 7.1 0.52
tuple_return_value 3.7 7.1 0.52
cartesian 3.7 6.9 0.53
scoped_resource 3.7 6.9 0.53
cgi 3.7 6.8 0.54
control_flow 3.8 6.9 0.55
fib_recursive 3.8 6.9 0.55
length 3.8 6.9 0.55
loops 3.8 6.9 0.55
modules 3.8 6.9 0.55
fib_iter 3.8 6.8 0.56
containers 28.4 47.8 0.59
varargs 5.4 7.1 0.76

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
cartesian 0 12 0.000
classes 0 15 0.000
control_flow 0 12 0.000
fib_iter 0 4 0.000
fib_recursive 0 4 0.000
length 0 4 0.000
loops 0 8 0.000
tuple_return_value 0 8 0.000
containers 8 20 0.396
asdl_generated 4 8 0.454
files 4 8 0.460
escape 4 8 0.508
scoped_resource 4 4 0.977
varargs 51 52 0.978
cgi 4 4 0.993
parse 7 4 1.844
modules 0 0 NA

raw benchmark files