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 0 293 0.000
modules 0 183 0.000
fib_iter 8 895 0.008
fib_recursive 11 884 0.012
asdl_generated 5 364 0.015
parse 22 761 0.029
scoped_resource 48 1,019 0.047
tuple_return_value 20 192 0.105
files 7 68 0.109
classes 3 26 0.130
containers 15 99 0.155
length 32 202 0.159
cartesian 87 326 0.265
escape 101 350 0.289
varargs 8 16 0.490
cgi 261 504 0.517
control_flow 206 116 1.778

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
control_flow 3.7 7.1 0.52
scoped_resource 3.7 7.1 0.52
parse 3.9 7.5 0.53
asdl_generated 3.7 6.9 0.53
cgi 3.7 6.9 0.53
escape 3.7 6.9 0.53
length 3.7 6.9 0.53
loops 3.8 7.1 0.54
cartesian 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
tuple_return_value 3.8 6.9 0.55
fib_recursive 3.8 6.8 0.56
containers 28.5 47.8 0.59
varargs 5.4 7.1 0.76

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
classes 0 4 0.000
containers 0 36 0.000
fib_iter 0 4 0.000
fib_recursive 0 8 0.000
files 0 8 0.000
scoped_resource 0 8 0.000
asdl_generated 5 16 0.340
loops 4 8 0.460
cartesian 4 8 0.495
escape 4 8 0.509
parse 7 12 0.608
cgi 8 12 0.663
control_flow 4 4 0.992
length 12 12 1.016
varargs 59 56 1.049
modules 2 0 inf
tuple_return_value 0 0 NA

raw benchmark files