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
classes 0 16 0.000
modules 0 167 0.000
fib_iter 8 899 0.008
fib_recursive 11 873 0.013
loops 4 295 0.014
parse 22 782 0.029
asdl_generated 11 381 0.029
containers 4 122 0.033
scoped_resource 39 1,060 0.037
tuple_return_value 16 196 0.083
files 8 77 0.100
length 45 198 0.229
cartesian 87 324 0.268
escape 102 352 0.288
cgi 270 513 0.526
varargs 24 24 0.982
control_flow 208 105 1.982

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 4.5 10.7 0.41
parse 3.8 7.5 0.51
asdl_generated 3.5 6.9 0.51
escape 3.5 6.9 0.51
scoped_resource 3.7 7.1 0.52
fib_iter 3.7 6.9 0.53
fib_recursive 3.7 6.9 0.53
files 3.7 6.9 0.53
modules 3.7 6.9 0.53
loops 3.8 7.1 0.54
cartesian 3.8 6.9 0.55
cgi 3.8 6.9 0.55
control_flow 3.8 6.9 0.55
length 3.8 6.9 0.55
tuple_return_value 3.8 6.9 0.55
containers 28.6 47.8 0.60
varargs 5.6 6.9 0.81

System Time (milliseconds)

Lower ratios are better.

example name C++ Python C++ : Python
asdl_generated 0 4 0.000
control_flow 0 8 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 2 16 0.118
classes 4 16 0.236
cartesian 4 8 0.493
tuple_return_value 4 8 0.507
containers 12 16 0.750
varargs 44 48 0.900
parse 7 4 1.864
escape 8 4 2.030
scoped_resource 8 0 inf
cgi 0 0 NA
files 0 0 NA

raw benchmark files