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
containers 0 103 0.000
modules 0 176 0.000
fib_iter 8 891 0.008
fib_recursive 11 879 0.012
loops 4 297 0.013
asdl_generated 7 390 0.018
parse 29 781 0.038
scoped_resource 47 1,021 0.046
tuple_return_value 13 192 0.070
files 7 68 0.110
classes 3 23 0.140
length 44 209 0.211
cartesian 86 344 0.251
escape 99 376 0.263
cgi 262 512 0.511
varargs 23 16 1.464
control_flow 207 116 1.793

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 4.6 10.9 0.42
parse 3.7 7.6 0.48
cartesian 3.5 6.9 0.51
loops 3.7 7.1 0.52
modules 3.7 7.1 0.52
scoped_resource 3.7 7.1 0.52
asdl_generated 3.7 6.9 0.53
cgi 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
tuple_return_value 3.7 6.9 0.53
fib_iter 3.8 7.1 0.54
control_flow 3.8 6.9 0.55
files 3.8 6.9 0.55
containers 28.5 47.8 0.60
varargs 5.4 6.9 0.77

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
classes 0 8 0.000
fib_iter 0 8 0.000
fib_recursive 0 8 0.000
files 0 8 0.000
length 0 4 0.000
loops 0 8 0.000
parse 0 4 0.000
scoped_resource 0 4 0.000
modules 2 8 0.237
cartesian 4 12 0.327
cgi 4 8 0.496
containers 16 32 0.500
varargs 43 56 0.767
asdl_generated 4 4 0.905
escape 8 0 inf
tuple_return_value 7 0 inf
control_flow 0 0 NA

raw benchmark files