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 27 0.000
loops gen 0 290 0.000
fib_iter gen 8 884 0.009
modules gen 2 176 0.010
fib_recursive gen 11 873 0.012
parse gen 18 769 0.024
asdl_generated gen 11 376 0.029
containers gen 4 101 0.037
scoped_resource gen 39 1,059 0.037
files gen 4 72 0.051
tuple_return_value gen 20 181 0.111
length gen 46 206 0.225
cartesian gen 80 326 0.245
escape gen 102 349 0.292
cgi gen 249 512 0.486
varargs gen 8 12 0.699
control_flow gen 206 117 1.762
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 10.7 0.42
gc_stack_roots gen 3.4 7.1 0.48
parse gen 3.8 7.6 0.50
asdl_generated gen 3.7 6.9 0.53
cartesian gen 3.7 6.9 0.53
cgi gen 3.7 6.9 0.53
escape gen 3.7 6.9 0.53
length gen 3.8 7.1 0.54
loops gen 3.8 7.1 0.54
scoped_resource gen 3.8 7.1 0.54
tuple_return_value gen 3.8 7.1 0.54
fib_iter gen 3.8 6.9 0.55
fib_recursive 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 6.8 0.58
containers gen 28.4 47.8 0.59
varargs gen 5.4 6.9 0.77

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
asdl_generated gen 0 8 0.000
control_flow gen 0 4 0.000
fib_iter gen 0 12 0.000
fib_recursive gen 0 12 0.000
gc_stack_roots gen 0 11 0.000
length gen 0 4 0.000
modules gen 0 8 0.000
tuple_return_value gen 0 12 0.000
containers gen 11 32 0.349
files gen 4 8 0.460
classes gen 3 4 0.829
loops gen 4 4 0.895
varargs gen 58 59 0.979
escape gen 4 4 1.015
parse gen 11 8 1.362
scoped_resource gen 8 4 1.967
cartesian gen 12 4 2.972
cgi gen 4 0 inf

raw benchmark files