[LLVMdev] Vectorization factor limitation in Loop Vectorizer

[James Molloy]

Hi shahid,

Having looked into this in the past, we're not taking into account the fact
that integer promotions and truncations will disappear during code
generation. The canonicalisation phase likes to create i32 and greater type
arithmetic, which creates extensions and promotions . However of course the
vectoriser can use i8 arithmetic I vectors, so those should go away.

Often this is the cause of insufficient vectorisation factors being picked,
and we should fix it.

James
On Sat, 13 Dec 2014 at 16:09, Shahid, Asghar-ahmad <
Asghar-ahmad.Shahid at amd.com> wrote:

>  So IMO, if we modify the VF calculation for targets/subtargets using TTI
> where higher VF is supported
>
> The vectorizer’s scope will become wider.
>
>
>
> Did/do you foresee any issue with this?
>
>
>
> Thanks,
>
> Shahid
>
>
>
> *From:* Nadav Rotem [mailto:nrotem at apple.com]
> *Sent:* Saturday, December 13, 2014 2:47 AM
> *To:* Shahid, Asghar-ahmad
> *Cc:* llvmdev at cs.uiuc.edu
> *Subject:* Re: [LLVMdev] Vectorization factor limitation in Loop
> Vectorizer
>
>
>
> Hi Shahid,
>
>
>
>  On Dec 10, 2014, at 10:48 PM, Shahid, Asghar-ahmad <
> Asghar-ahmad.Shahid at amd.com> wrote:
>
>
>
> Hi Nadav/Devs
>
>
>
> I am exploring Loop Vectorizer to vectorize i8 scalar operations into 8xi8
> vector operation.
>
>
>
> I was expecting the Loop Vectorizer to analyze the profitability for
> vectorization factor(VF) of 8,
>
> However it is not doing so due to the widest type calculation done for the
> blocks inside the loop.
>
>
>
> May be I am missing something, however, I am curious to know why Loop
> Vectorizer limits the
>
> profitability check to widest type and not allowing for other narrower
> type?
>
>
>
> The vectorizer stops the search of profitable vectorization factors at the
> widest type because higher vectorization factors would require the compiler
> to split the vectorized value into multiple registers. The vectorizer’s
> cost model first tries to optimize for SIMD instruction utilization. Later,
> we optimize for ILP by doubling the vectorization factor (we call it
> “interleave”) and exposing ILP.
>
>
>
> Thanks,
>
> Nadav
>
>
>
>
>
> Regards,
>
> Shahid
>
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