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 0 292 0.000
fib_iter 8 933 0.008
fib_recursive 7 872 0.008
modules 2 175 0.010
asdl_generated 11 381 0.029
parse 26 777 0.033
scoped_resource 47 1,015 0.046
tuple_return_value 17 201 0.084
files 7 72 0.103
containers 15 109 0.139
classes 3 23 0.143
length 40 202 0.199
cartesian 77 331 0.233
escape 97 344 0.283
cgi 247 509 0.485
varargs 8 16 0.517
control_flow 211 109 1.930

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 10.8 0.41
length 3.5 6.9 0.51
parse 3.9 7.6 0.52
loops 3.7 7.1 0.52
cartesian 3.7 6.9 0.53
cgi 3.7 6.9 0.53
escape 3.7 6.9 0.53
scoped_resource 3.7 6.9 0.53
fib_recursive 3.8 7.1 0.54
asdl_generated 3.7 6.8 0.54
fib_iter 3.8 6.9 0.55
files 3.8 6.9 0.55
modules 3.8 6.9 0.55
control_flow 3.9 6.9 0.57
tuple_return_value 3.9 6.9 0.57
containers 28.5 47.8 0.60
varargs 5.5 6.8 0.81

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
asdl_generated 0 4 0.000
classes 0 8 0.000
containers 0 24 0.000
control_flow 0 8 0.000
files 0 4 0.000
modules 0 8 0.000
scoped_resource 0 4 0.000
loops 4 12 0.301
fib_recursive 4 8 0.447
length 4 8 0.508
tuple_return_value 3 4 0.839
cgi 4 4 0.993
varargs 55 53 1.035
cartesian 12 4 2.870
escape 12 4 2.920
parse 4 0 inf
fib_iter 0 0 NA

raw benchmark files