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 0.009
modules 2 190 0.010
fib_recursive 11 898 0.012
loops 4 297 0.012
asdl_generated 7 378 0.019
parse 22 754 0.030
scoped_resource 47 1,016 0.046
tuple_return_value 14 182 0.074
files 8 73 0.104
containers 12 109 0.110
classes 3 26 0.123
length 41 200 0.205
cartesian 79 325 0.242
escape 99 344 0.286
cgi 265 508 0.522
varargs 19 28 0.678
control_flow 208 116 1.784

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
scoped_resource 3.5 7.1 0.50
fib_iter 3.5 6.9 0.51
loops 3.7 7.1 0.52
asdl_generated 3.7 6.9 0.53
cartesian 3.7 6.9 0.53
cgi 3.7 6.9 0.53
control_flow 3.7 6.9 0.53
escape 3.7 6.9 0.53
files 3.7 6.9 0.53
modules 3.8 7.1 0.54
fib_recursive 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 6.9 0.81

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
classes 0 4 0.000
fib_iter 0 4 0.000
fib_recursive 0 8 0.000
files 0 4 0.000
modules 0 4 0.000
scoped_resource 0 8 0.000
containers 4 28 0.141
length 4 12 0.311
cgi 4 12 0.335
parse 7 16 0.466
tuple_return_value 7 12 0.568
asdl_generated 4 4 0.899
escape 8 8 0.985
varargs 46 44 1.035
cartesian 12 8 1.491
control_flow 4 0 inf
loops 0 0 NA

raw benchmark files