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
gc_stack_roots gen 0 12 0.000
fib_iter gen 8 874 0.009
modules gen 2 174 0.010
fib_recursive gen 11 879 0.012
loops gen 4 290 0.013
asdl_generated gen 11 371 0.029
parse gen 29 772 0.037
scoped_resource gen 39 1,026 0.038
containers gen 11 125 0.091
files gen 7 72 0.103
tuple_return_value gen 20 189 0.107
cartesian gen 75 343 0.218
length gen 45 199 0.225
classes gen 3 13 0.244
escape gen 107 341 0.313
cgi gen 250 528 0.474
varargs gen 23 24 0.982
control_flow gen 208 115 1.812

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 10.7 0.41
asdl_generated gen 3.4 6.9 0.49
loops gen 3.5 7.2 0.49
cartesian gen 3.5 7.1 0.50
parse gen 3.8 7.5 0.51
gc_stack_roots gen 3.5 6.9 0.51
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
modules gen 3.7 6.9 0.53
fib_iter gen 3.8 7.1 0.54
scoped_resource gen 3.7 6.8 0.54
length gen 3.8 6.9 0.55
tuple_return_value gen 3.8 6.9 0.55
control_flow gen 3.9 6.9 0.57
files gen 3.9 6.9 0.57
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
asdl_generated gen 0 8 0.000
classes gen 0 17 0.000
escape gen 0 12 0.000
fib_iter gen 0 12 0.000
fib_recursive gen 0 12 0.000
files gen 0 4 0.000
length gen 0 8 0.000
loops gen 0 4 0.000
modules gen 0 8 0.000
parse gen 0 4 0.000
tuple_return_value gen 0 4 0.000
containers gen 4 8 0.468
scoped_resource gen 8 12 0.649
varargs gen 43 48 0.900
cgi gen 4 4 1.010
cartesian gen 16 4 3.945
gc_stack_roots gen 2 0 inf
control_flow gen 0 0 NA

raw benchmark files