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 9 883 0.010
modules 2 178 0.010
fib_recursive 11 878 0.012
loops 4 286 0.013
asdl_generated 11 383 0.028
parse 26 750 0.034
scoped_resource 45 1,030 0.044
containers 8 107 0.072
tuple_return_value 20 193 0.104
files 8 68 0.110
classes 3 20 0.166
length 44 198 0.225
cartesian 89 329 0.269
escape 103 352 0.293
cgi 265 510 0.520
varargs 27 20 1.378
control_flow 212 107 1.980

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
scoped_resource 3.5 7.2 0.49
parse 3.8 7.6 0.50
asdl_generated 3.5 6.9 0.51
cartesian 3.7 6.9 0.53
cgi 3.7 6.9 0.53
escape 3.7 6.9 0.53
tuple_return_value 3.7 6.9 0.53
length 3.8 7.1 0.54
loops 3.8 7.1 0.54
modules 3.8 7.1 0.54
fib_iter 3.8 6.9 0.55
files 3.8 6.9 0.55
control_flow 3.9 7.1 0.56
fib_recursive 3.9 7.1 0.56
containers 28.3 47.7 0.59
varargs 5.5 6.9 0.79

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
cgi 0 8 0.000
classes 0 12 0.000
control_flow 0 8 0.000
fib_iter 0 8 0.000
fib_recursive 0 8 0.000
files 0 8 0.000
length 0 12 0.000
loops 0 8 0.000
modules 0 4 0.000
tuple_return_value 0 4 0.000
parse 4 16 0.229
containers 8 28 0.277
scoped_resource 4 12 0.340
varargs 39 52 0.757
escape 4 4 0.990
cartesian 4 4 1.004
asdl_generated 0 0 NA

raw benchmark files