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
classes 0 16 0.000
fib_iter 8 891 0.008
modules 2 181 0.010
loops 4 304 0.012
fib_recursive 11 896 0.012
asdl_generated 11 378 0.030
parse 25 774 0.032
scoped_resource 43 1,035 0.042
files 4 64 0.057
tuple_return_value 13 182 0.074
containers 11 128 0.090
length 40 204 0.196
cartesian 86 335 0.258
escape 103 351 0.293
cgi 253 511 0.495
varargs 12 16 0.779
control_flow 205 111 1.851

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 10.6 0.41
cartesian 3.5 7.1 0.50
parse 3.8 7.6 0.50
cgi 3.5 6.9 0.51
fib_iter 3.5 6.9 0.51
scoped_resource 3.7 7.1 0.52
tuple_return_value 3.7 7.1 0.52
asdl_generated 3.7 6.9 0.53
escape 3.7 6.9 0.53
fib_recursive 3.7 6.9 0.53
length 3.7 6.9 0.53
modules 3.7 6.9 0.53
loops 3.8 7.1 0.54
control_flow 3.8 6.9 0.55
files 3.8 6.9 0.55
containers 28.7 47.6 0.60
varargs 5.6 6.9 0.81

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
asdl_generated 0 4 0.000
cgi 0 4 0.000
fib_recursive 0 4 0.000
loops 0 8 0.000
modules 0 4 0.000
classes 3 16 0.201
files 4 11 0.325
parse 4 12 0.349
containers 4 8 0.478
cartesian 4 8 0.515
tuple_return_value 7 8 0.848
varargs 53 55 0.964
escape 4 4 0.992
control_flow 4 4 0.997
length 4 4 1.000
scoped_resource 4 0 inf
fib_iter 0 0 NA

raw benchmark files