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 8 887 0.008
modules 2 172 0.010
fib_recursive 11 880 0.012
loops 4 294 0.012
asdl_generated 7 374 0.019
parse 22 762 0.029
scoped_resource 48 1,026 0.046
files 4 71 0.052
tuple_return_value 12 188 0.065
containers 8 117 0.066
classes 3 22 0.146
length 41 199 0.206
varargs 4 20 0.208
cartesian 86 329 0.262
escape 102 344 0.296
cgi 250 506 0.494
control_flow 207 115 1.798

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 3.9 7.7 0.51
cartesian 3.7 7.1 0.52
cgi 3.7 7.1 0.52
escape 3.7 7.1 0.52
scoped_resource 3.7 7.1 0.52
loops 3.8 7.2 0.53
fib_recursive 3.7 6.9 0.53
tuple_return_value 3.7 6.9 0.53
asdl_generated 3.7 6.8 0.54
control_flow 3.8 6.9 0.55
files 3.8 6.9 0.55
length 3.8 6.9 0.55
modules 3.8 6.9 0.55
fib_iter 3.8 6.8 0.56
containers 28.5 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
control_flow 0 4 0.000
fib_recursive 0 4 0.000
loops 0 4 0.000
modules 0 8 0.000
scoped_resource 0 4 0.000
length 4 12 0.343
asdl_generated 4 8 0.447
containers 8 16 0.475
cgi 4 8 0.506
escape 4 8 0.510
cartesian 4 8 0.511
tuple_return_value 8 12 0.696
files 4 4 0.931
varargs 62 51 1.199
parse 7 4 1.819
fib_iter 0 0 NA

raw benchmark files