[Cython] CEP1000: Native dispatch through callables

Robert Bradshaw robertwb at gmail.com
Thu May 3 22:18:03 CEST 2012


On Thu, May 3, 2012 at 5:24 AM, Dag Sverre Seljebotn
<d.s.seljebotn at astro.uio.no> wrote:
> I'm afraid I'm going to try to kick this thread alive again. I want us to
> have something that Travis can implement in numba and "his" portion of
> SciPy, and also that could be used by NumPy devs.

That's great, I'd like to get things moving forward on this.

> Since the decisions are rather arbitrary, perhaps we can try to quickly get
> to the "+1" stage (or, depending on how things turn out, a tournament
> starting with at most one proposal per person).
>
>
> On 04/20/2012 09:30 AM, Robert Bradshaw wrote:
>>
>> On Thu, Apr 19, 2012 at 6:18 AM, Dag Sverre Seljebotn
>> <d.s.seljebotn at astro.uio.no>  wrote:
>>>
>>> On 04/19/2012 01:20 PM, Nathaniel Smith wrote:
>>>>
>>>>
>>>> On Thu, Apr 19, 2012 at 11:56 AM, Dag Sverre Seljebotn
>>>> <d.s.seljebotn at astro.uio.no>    wrote:
>>>>>
>>>>>
>>>>> I thought of some drawbacks of getfuncptr:
>>>>>
>>>>>  - Important: Doesn't allow you to actually inspect the supported
>>>>> signatures, which is needed (or at least convenient) if you want to use
>>>>> an
>>>>> FFI library or do some JIT-ing. So an iteration mechanism is still
>>>>> needed
>>>>> in
>>>>> addition, meaning the number of things for the object to implement
>>>>> grows
>>>>> a
>>>>> bit large. Default implementations help -- OTOH there really wasn't a
>>>>> major
>>>>> drawback with the table approach as long as JIT's can just replace it?
>>>>
>>>>
>>>>
>>>> But this is orthogonal to the table vs. getfuncptr discussion. We're
>>>> assuming that the table might be extended at runtime, which means you
>>>> can't use it to determine which signatures are supported. So we need
>>>> some sort of extra interface for the caller and callee to negotiate a
>>>> type anyway. (I'm intentionally agnostic about whether it makes more
>>>> sense for the caller or the callee to be doing the iterating... in
>>>> general type negotiation could be quite complicated, and I don't think
>>>> we know enough to get that interface right yet.)
>>>
>>>
>>>
>>> Hmm. Right. Let's define an explicit goal for the CEP then.
>>>
>>> What I care about at is getting the spec right enough such that, e.g.,
>>> NumPy
>>> and SciPy, and other (mostly manually written) C extensions with slow
>>> development pace, can be forward-compatible with whatever crazy things
>>> Cython or Numba does.
>>>
>>> There's 4 cases:
>>>
>>>  1) JIT calls JIT (ruled out straight away)
>>>
>>>  2) JIT calls static: Say that Numba wants to optimize calls to np.sin
>>> etc.
>>> without special-casing; this seem to require reading a table of static
>>> signatures
>>>
>>>  3) Static calls JIT: This is the case when scipy.integrate routines
>>> calls a
>>> Numba callback and Numba generates a specialization for the dtype they
>>> explicitly needs. This calls for getfuncptr (but perhaps in a form which
>>> we
>>> can't quite determine yet?).
>>>
>>>  4) Static calls static: Either table or getfuncptr works.
>>>
>>> My gut feeling is go for 2) and 4) in this round =>  table.
>>
>>
>> getfuncptr is really simple and flexible, but I'm with you on both of
>> these to points, and the overhead was not trivial.
>
>
> It's interesting to hear you say the overhead was not trivial (that was my
> hunch too but I sort of yielded to peer pressure). I think SAGE has some
> history with this -- isn't one of the reasons for the "cpdef" vs. "cdef"
> split that "cpdef" has the cost of a single lookup for the presence of a
> __dict__ on the object, which was an unacceptable penalty for parts of Sage?
> That can't have been much more than a 1ns penalty per instance.

It's mostly historical, as a lot of Sage was written before cpdef
existed (and people following this pattern after the fact).  There are
also some cases where cdef is used because the "leaf" classes are
often in Python but have no need to override the given method, and an
actual dictionary lookup would be required otherwise (e.g. in the
coercion model).

>> Of course we could offer both, i.e. look at the table first, if it's
>> not there call getfuncptr if it's non-null, then fall back to "slow"
>> call or error. These are all opt-in depending on how hard you want to
>> try to optimize things.
>
>
> That's actually exactly what I was envisioning -- in time (with JITs on both
> ends) the table could act sort of as a cache for commonly used overloads,
> and getfuncptr would access the others more slowly.

OK, then +1

>> As far as keys vs. interning, I'm also tempted to try to have my cake
>> and eat it too. Define a space-friendly encoding for signatures and
>> require interning for anything that doesn't fit into a single
>> sizeof(void*). The fact that this cutoff would vary for 32 vs 64-bit
>> would require some care, but could be done with macros in C. If the
>> signatures produce non-aligned "pointer" values there won't be any
>> collisions, and this way libraries only have to share in the global
>> (Python-level?) interning scheme iff they want to expose/use "large"
>> signatures.
>
>
> That was the approach I described to Nathaniel as having the "worst features
> of both" -- lack of readable gdb dumps of the keys, and having to define an
> interning mechanism for use by the 5% cases that don't fit.

Yes, it has the best and worst features of both.

> To sum up hat's been said earlier: The only thing that would blow the key
> size above 64 bits except very many arguments would be things like
> classes/interfaces/vtables. But in that case, reasonable-sized keys for the
> vtables can be computed (whether by interning, cryptographic hashing, or a
> GUID like Microsoft COM).
>
> So I'm still +1 on my proposal; but I would be happy with an intern-based
> proposal if somebody bothers to flesh it out a bit (I don't quite know how
> I'd do it and would get lost in PyObject* vs. char* and cross-language state
> sharing...).
>
> My proposal in summary:
>
>  - Table with variable-sized entries (not getfuncptr, not interning) that
> can be scanned by the caller in 128-bit increments.
>
>  - Only use 64 bit pointers, in order to keep table format the same on 32
> bit and 64 bit.
>
>  - Do encoding of the signature strings. Utility functions to work with this
> (both to scan tables and encode/decode a format string) will be provided as
> C code by the CEP that can be bundled.
>
> Pros:
>
>  - Table format is not specific to Python world (it makes as much sense to
> use, e.g., internally in Julia)
>
>  - No state needs to be shared between packages run-time (they can use the
> bundled C code in isolation if they wish)
>
>  - No need for an interning machinery
>
>  - More easily compatible with multiple interpreter states (?)
>
>  - Minor performance benefit of table over getfuncptr (intern vs. key didn't
> matter). [Cue comment that this doesn't matter.]
>
> Cons:
>
>  - Lack of instant low-level debuggability, like in the interned case (a
> human needs to run a function on the key constant to see what it corresponds
> to)
>
>  - Not as extendable as getfuncptr (though currently we don't quite know how
> we would extend it, and it's easy to add getfuncptr in the future)
>
> Notes:
>
>  - When extended to handle vtable argument types, these still needs to be
> some interning or crypto-hashing. But that is likely to come up anyway as
> part of a COM-like queryInterface protocol, and at that point we will be
> better at making those decisions and design a good interning mechanism.

+1 to going with this, with the following suggestions for future
interoperability:

1) Even if we don't flesh out getfuncptr at this point, lets leave a
slot in the spec for it which must be set to NULL.

2) Lets define the encoding to emit odd first words, to allow using
(alligned) pointers in some future interning extension without
worrying about collision. This could be used to prevent matching on
the 2n+1th words as well when scanning the table.

- Robert


More information about the cython-devel mailing list