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 gen C++ Python C++ : Python
classes gen 0 20 0.000
modules gen 0 179 0.000
fib_recursive gen 7 913 0.008
fib_iter gen 8 892 0.009
loops gen 4 294 0.012
asdl_generated gen 7 373 0.019
parse gen 23 772 0.030
scoped_resource gen 35 1,037 0.034
containers gen 8 117 0.067
tuple_return_value gen 16 196 0.082
files gen 7 64 0.117
length gen 40 202 0.199
cartesian gen 86 351 0.247
escape gen 103 351 0.293
cgi gen 269 511 0.526
varargs gen 21 12 1.731
control_flow gen 205 106 1.942

Max Resident Set Size (MB)

Lower ratios are better. We use MB (powers of 10), not MiB (powers of 2).

example name gen C++ Python C++ : Python
classes gen 4.5 10.9 0.41
cartesian gen 3.5 6.9 0.51
files gen 3.7 7.1 0.52
parse gen 3.9 7.5 0.53
asdl_generated gen 3.7 6.9 0.53
cgi gen 3.7 6.9 0.53
escape gen 3.7 6.9 0.53
fib_recursive gen 3.7 6.9 0.53
fib_iter gen 3.8 7.1 0.54
loops gen 3.8 7.1 0.54
control_flow gen 3.8 6.9 0.55
length gen 3.8 6.9 0.55
modules gen 3.8 6.9 0.55
scoped_resource gen 3.8 6.9 0.55
tuple_return_value gen 3.8 6.9 0.55
containers gen 28.6 47.7 0.60
varargs gen 5.5 6.9 0.79

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
cgi gen 0 4 0.000
fib_iter gen 0 4 0.000
files gen 0 12 0.000
loops gen 0 4 0.000
classes gen 3 12 0.280
asdl_generated gen 4 8 0.450
modules gen 2 4 0.452
control_flow gen 4 8 0.486
containers gen 8 16 0.488
length gen 4 8 0.498
tuple_return_value gen 4 8 0.503
varargs gen 46 60 0.762
fib_recursive gen 4 4 0.906
escape gen 4 4 0.990
cartesian gen 4 4 1.033
scoped_resource gen 12 8 1.460
parse gen 8 4 1.929

raw benchmark files