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
fib_iter gen 4 947 0.004
modules gen 2 181 0.010
fib_recursive gen 11 888 0.012
loops gen 4 294 0.012
asdl_generated gen 11 380 0.028
parse gen 26 770 0.033
containers gen 4 106 0.037
scoped_resource gen 48 1,023 0.047
tuple_return_value gen 16 191 0.085
files gen 8 72 0.106
length gen 45 206 0.218
gc_stack_roots gen 2 8 0.223
classes gen 4 15 0.235
cartesian gen 83 340 0.243
escape gen 91 347 0.262
cgi gen 270 513 0.527
varargs gen 19 11 1.716
control_flow gen 211 103 2.043

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 10.8 0.41
gc_stack_roots gen 3.4 7.1 0.48
cartesian gen 3.5 6.9 0.51
parse gen 3.9 7.6 0.52
asdl_generated gen 3.7 7.1 0.52
cgi gen 3.7 7.1 0.52
scoped_resource gen 3.7 7.1 0.52
tuple_return_value gen 3.7 6.9 0.53
files gen 3.8 7.1 0.54
length gen 3.8 7.1 0.54
modules gen 3.8 7.1 0.54
control_flow gen 3.8 6.9 0.55
escape gen 3.8 6.9 0.55
loops gen 3.8 6.9 0.55
fib_iter gen 3.8 6.8 0.56
fib_recursive gen 3.9 6.9 0.57
containers gen 28.5 47.7 0.60
varargs gen 5.4 6.9 0.77

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
classes gen 0 15 0.000
files gen 0 4 0.000
gc_stack_roots gen 0 4 0.000
length gen 0 4 0.000
loops gen 0 4 0.000
modules gen 0 4 0.000
scoped_resource gen 0 4 0.000
parse gen 4 12 0.308
fib_iter gen 4 12 0.314
control_flow gen 4 12 0.334
containers gen 12 31 0.377
cartesian gen 8 12 0.662
varargs gen 47 61 0.772
cgi gen 4 4 0.992
tuple_return_value gen 4 4 0.994
escape gen 16 8 1.982
asdl_generated gen 0 0 NA
fib_recursive gen 0 0 NA

raw benchmark files