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 8 892 0.008
modules 2 188 0.009
fib_recursive 11 875 0.012
loops 4 278 0.013
parse 17 769 0.022
asdl_generated 11 379 0.028
scoped_resource 44 1,014 0.043
tuple_return_value 16 189 0.085
files 7 71 0.105
containers 15 110 0.139
classes 3 23 0.141
length 36 208 0.173
cartesian 90 353 0.255
escape 104 354 0.293
cgi 263 514 0.511
varargs 12 8 1.451
control_flow 209 107 1.950

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 10.7 0.41
parse 3.8 7.6 0.50
fib_iter 3.5 6.9 0.51
escape 3.7 7.1 0.52
cartesian 3.5 6.8 0.52
asdl_generated 3.7 6.9 0.53
cgi 3.7 6.9 0.53
modules 3.7 6.9 0.53
control_flow 3.8 7.1 0.54
fib_recursive 3.8 7.1 0.54
loops 3.8 7.1 0.54
scoped_resource 3.8 7.1 0.54
files 3.8 6.9 0.55
length 3.8 6.9 0.55
tuple_return_value 3.8 6.9 0.55
containers 28.6 47.8 0.60
varargs 5.6 7.1 0.80

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
cartesian 0 4 0.000
classes 0 8 0.000
containers 0 24 0.000
control_flow 0 8 0.000
fib_iter 0 4 0.000
fib_recursive 0 12 0.000
files 0 4 0.000
loops 0 16 0.000
modules 0 4 0.000
scoped_resource 4 12 0.333
tuple_return_value 4 8 0.499
escape 4 8 0.501
varargs 54 63 0.846
parse 12 8 1.560
length 8 4 1.995
cgi 8 0 inf
asdl_generated 0 0 NA

raw benchmark files