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
loops gen 0 291 0.000
fib_iter gen 4 898 0.004
modules gen 2 181 0.010
fib_recursive gen 11 884 0.012
asdl_generated gen 11 377 0.029
containers gen 4 101 0.037
parse gen 29 765 0.038
scoped_resource gen 48 1,013 0.047
tuple_return_value gen 20 187 0.107
files gen 7 63 0.118
gc_stack_roots gen 2 8 0.216
length gen 45 201 0.224
classes gen 3 13 0.244
cartesian gen 83 334 0.247
escape gen 103 356 0.290
cgi gen 269 515 0.522
varargs gen 8 12 0.693
control_flow gen 210 111 1.891

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 10.6 0.42
parse gen 3.8 7.6 0.50
asdl_generated gen 3.5 6.9 0.51
scoped_resource gen 3.7 7.1 0.52
gc_stack_roots gen 3.5 6.8 0.52
loops gen 3.8 7.2 0.53
cartesian gen 3.7 6.9 0.53
escape gen 3.7 6.9 0.53
fib_iter gen 3.7 6.9 0.53
fib_recursive gen 3.7 6.9 0.53
tuple_return_value gen 3.7 6.9 0.53
cgi gen 3.8 6.9 0.55
files gen 3.8 6.9 0.55
modules gen 3.8 6.9 0.55
control_flow gen 3.9 6.9 0.57
length gen 3.9 6.9 0.57
containers gen 28.4 47.8 0.59
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 8 0.000
classes gen 0 17 0.000
control_flow gen 0 4 0.000
fib_recursive gen 0 4 0.000
files gen 0 12 0.000
gc_stack_roots gen 0 4 0.000
length gen 0 8 0.000
modules gen 0 4 0.000
parse gen 0 4 0.000
scoped_resource gen 0 12 0.000
tuple_return_value gen 0 8 0.000
containers gen 11 35 0.325
fib_iter gen 4 8 0.468
loops gen 4 4 0.909
varargs gen 58 60 0.970
cartesian gen 8 4 1.978
escape gen 4 0 inf
asdl_generated gen 0 0 NA

raw benchmark files