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 C++ Python C++ : Python
fib_iter 8 897 0.009
asdl_generated 4 381 0.010
modules 2 179 0.010
fib_recursive 11 892 0.012
loops 4 295 0.014
parse 30 768 0.039
scoped_resource 43 1,010 0.043
files 4 70 0.057
tuple_return_value 14 179 0.078
containers 16 120 0.134
classes 3 22 0.150
cartesian 79 353 0.224
length 45 199 0.229
escape 103 348 0.295
cgi 265 508 0.522
varargs 20 24 0.810
control_flow 209 105 2.001

Max Resident Set Size (MB)

Lower ratios are better. We use MB (powers of 10), not MiB (powers of 2).

example name C++ Python C++ : Python
classes 4.3 10.8 0.40
asdl_generated 3.5 7.1 0.50
parse 3.9 7.6 0.52
loops 3.8 7.2 0.53
cartesian 3.7 6.9 0.53
cgi 3.7 6.9 0.53
escape 3.7 6.9 0.53
fib_iter 3.7 6.9 0.53
tuple_return_value 3.7 6.9 0.53
length 3.8 7.1 0.54
fib_recursive 3.8 6.9 0.55
files 3.8 6.9 0.55
modules 3.8 6.9 0.55
scoped_resource 3.8 6.9 0.55
control_flow 3.9 6.9 0.57
containers 28.6 47.8 0.60
varargs 5.5 6.8 0.81

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
classes 0 11 0.000
containers 0 20 0.000
control_flow 0 12 0.000
fib_iter 0 4 0.000
fib_recursive 0 8 0.000
length 0 12 0.000
loops 0 8 0.000
modules 0 4 0.000
tuple_return_value 7 16 0.436
scoped_resource 4 8 0.493
cgi 4 8 0.502
files 4 8 0.513
escape 4 8 0.514
varargs 47 49 0.972
cartesian 12 8 1.479
asdl_generated 7 0 inf
parse 0 0 NA

raw benchmark files