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 20 0.000
fib_iter 8 887 0.009
modules 2 171 0.011
fib_recursive 11 879 0.012
loops 4 288 0.013
asdl_generated 7 373 0.019
containers 4 116 0.035
parse 30 789 0.037
scoped_resource 43 1,058 0.041
files 4 65 0.058
tuple_return_value 16 184 0.088
length 37 202 0.185
cartesian 90 333 0.271
escape 104 347 0.300
cgi 269 511 0.526
varargs 12 19 0.623
control_flow 209 104 2.014

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 0.42
parse 3.7 7.6 0.48
escape 3.5 6.9 0.51
asdl_generated 3.7 7.1 0.52
scoped_resource 3.7 7.1 0.52
cartesian 3.7 6.9 0.53
cgi 3.7 6.9 0.53
fib_iter 3.7 6.9 0.53
fib_recursive 3.7 6.9 0.53
length 3.8 7.1 0.54
loops 3.8 7.1 0.54
control_flow 3.8 6.9 0.55
files 3.8 6.9 0.55
modules 3.8 6.9 0.55
tuple_return_value 3.8 6.9 0.55
containers 28.6 47.7 0.60
varargs 5.5 6.9 0.79

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
fib_iter 0 4 0.000
fib_recursive 0 8 0.000
loops 0 8 0.000
modules 0 12 0.000
parse 0 4 0.000
classes 3 12 0.276
files 4 12 0.307
control_flow 4 12 0.329
asdl_generated 4 8 0.458
escape 4 8 0.502
containers 12 24 0.504
tuple_return_value 4 8 0.508
scoped_resource 4 4 0.983
cgi 4 4 0.990
length 8 8 1.029
varargs 56 54 1.038
cartesian 4 0 inf

raw benchmark files