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
fib_iter gen 4 879 0.004
modules gen 2 169 0.011
fib_recursive gen 11 865 0.012
loops gen 4 289 0.013
asdl_generated gen 10 366 0.028
parse gen 24 773 0.031
scoped_resource gen 47 1,001 0.047
files gen 4 71 0.053
containers gen 11 113 0.098
tuple_return_value gen 20 180 0.112
length gen 24 200 0.120
classes gen 3 26 0.122
cartesian gen 87 315 0.275
escape gen 96 347 0.277
cgi gen 257 508 0.505
varargs gen 17 20 0.822
control_flow gen 208 114 1.816
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 7.1 0.48
parse gen 3.8 7.6 0.50
cartesian gen 3.5 6.9 0.51
cgi gen 3.7 7.1 0.52
scoped_resource gen 3.7 7.1 0.52
asdl_generated gen 3.7 6.9 0.53
escape gen 3.7 6.9 0.53
loops gen 3.7 6.9 0.53
fib_recursive gen 3.8 6.9 0.55
files gen 3.8 6.9 0.55
length gen 3.8 6.9 0.55
modules gen 3.8 6.9 0.55
tuple_return_value gen 3.8 6.9 0.55
fib_iter gen 3.9 7.1 0.56
control_flow gen 3.9 6.9 0.57
containers gen 28.5 47.8 0.60
varargs gen 5.6 6.9 0.81

System Time (milliseconds)

Lower ratios are better.

example name gen C++ Python C++ : Python
asdl_generated gen 0 4 0.000
cartesian gen 0 8 0.000
classes gen 0 4 0.000
fib_recursive gen 0 4 0.000
gc_stack_roots gen 0 12 0.000
loops gen 0 4 0.000
modules gen 0 8 0.000
tuple_return_value gen 0 8 0.000
containers gen 4 19 0.189
cgi gen 4 8 0.501
parse gen 4 8 0.504
fib_iter gen 4 4 0.945
files gen 4 4 0.945
varargs gen 50 48 1.028
escape gen 8 4 2.007
length gen 20 8 2.502
control_flow gen 0 0 NA
scoped_resource gen 0 0 NA

raw benchmark files