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 16 0.000
modules gen 0 183 0.000
fib_iter gen 8 895 0.009
fib_recursive gen 11 876 0.012
loops gen 4 295 0.013
asdl_generated gen 11 379 0.029
parse gen 25 758 0.033
scoped_resource gen 47 1,029 0.046
tuple_return_value gen 17 196 0.087
files gen 8 73 0.104
containers gen 16 123 0.132
length gen 45 199 0.227
cartesian gen 82 329 0.251
escape gen 97 341 0.286
cgi gen 265 513 0.516
control_flow gen 208 117 1.773
varargs gen 23 11 2.038
gc_stack_roots gen 2 0 inf

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
gc_stack_roots gen 3.4 6.9 0.49
parse gen 3.9 7.7 0.51
cartesian gen 3.5 6.9 0.51
escape gen 3.7 7.1 0.52
loops gen 3.7 7.1 0.52
asdl_generated gen 3.7 6.9 0.53
cgi 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
files gen 3.8 7.1 0.54
tuple_return_value gen 3.8 7.1 0.54
modules gen 3.8 6.9 0.55
scoped_resource gen 3.8 6.9 0.55
length gen 3.9 7.1 0.56
control_flow gen 3.8 6.8 0.56
containers gen 28.6 47.8 0.60
varargs gen 5.2 7.1 0.74

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
asdl_generated gen 0 12 0.000
containers gen 0 16 0.000
fib_recursive gen 0 16 0.000
files gen 0 4 0.000
gc_stack_roots gen 0 12 0.000
length gen 0 8 0.000
loops gen 0 4 0.000
classes gen 3 16 0.204
parse gen 4 12 0.351
modules gen 2 4 0.453
escape gen 8 12 0.683
varargs gen 43 61 0.701
cartesian gen 8 8 0.980
cgi gen 4 4 1.000
tuple_return_value gen 3 0 inf
control_flow gen 0 0 NA
fib_iter gen 0 0 NA
scoped_resource gen 0 0 NA

raw benchmark files