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
modules gen 0 171 0.000
fib_iter gen 8 889 0.009
fib_recursive gen 11 882 0.012
loops gen 4 293 0.012
asdl_generated gen 11 370 0.031
parse gen 25 768 0.033
scoped_resource gen 44 1,058 0.042
containers gen 8 111 0.072
files gen 7 71 0.104
tuple_return_value gen 20 188 0.107
classes gen 3 22 0.147
length gen 44 202 0.219
cartesian gen 82 331 0.248
escape gen 93 349 0.267
cgi gen 266 506 0.526
varargs gen 24 32 0.734
control_flow gen 209 115 1.823
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 10.8 0.41
gc_stack_roots gen 3.4 6.9 0.49
parse gen 3.8 7.7 0.49
scoped_resource gen 3.7 7.1 0.52
loops gen 3.8 7.2 0.53
cartesian gen 3.7 6.9 0.53
cgi gen 3.7 6.9 0.53
asdl_generated gen 3.8 7.1 0.54
tuple_return_value gen 3.8 7.1 0.54
escape gen 3.7 6.8 0.54
control_flow gen 3.8 6.9 0.55
fib_iter gen 3.8 6.9 0.55
length gen 3.8 6.9 0.55
modules gen 3.8 6.9 0.55
fib_recursive gen 3.8 6.8 0.56
files gen 3.9 6.9 0.57
containers gen 28.7 47.8 0.60
varargs gen 5.6 7.1 0.80

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
asdl_generated gen 0 12 0.000
classes gen 0 9 0.000
fib_iter gen 0 4 0.000
fib_recursive gen 0 4 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 8 0.000
tuple_return_value gen 0 4 0.000
modules gen 2 12 0.162
containers gen 8 24 0.335
parse gen 4 12 0.349
cgi gen 4 8 0.506
scoped_resource gen 4 4 1.000
varargs gen 43 40 1.076
escape gen 12 8 1.453
cartesian gen 8 4 2.035
control_flow gen 0 0 NA

raw benchmark files