RFR(M):8214751: X86: Support for VNNI instruction

[Vladimir Kozlov]

On 12/7/18 10:33 AM, Deshpande, Vivek R wrote:
> Hi Vladimir
> 
> This patch is useful for AI ML/DL applications such convolution based Neural Nets.

Add to RFE's Description this comment. May be have some JMH benchmark results to show improvement.

> I have updated the patch with your suggestion.
> I am creating the MulAddS2I patch late and before vectoriztion.

Add check that all combined nodes belongs to the same loop - you have this information since you 
inside loopopts.

Thanks,
Vladimir

> The updated webrev is here:
> http://cr.openjdk.java.net/~vdeshpande/8214751/VNNI/webrev.01/
> 
> I am also working on the test.
> 
> Regards,
> Vivek
> 
> 
> -----Original Message-----
> From: Vladimir Kozlov [mailto:vladimir.kozlov at oracle.com]
> Sent: Thursday, December 6, 2018 11:59 AM
> To: Deshpande, Vivek R <vivek.r.deshpande at intel.com>; hotspot-compiler-dev at openjdk.java.net compiler <hotspot-compiler-dev at openjdk.java.net>
> Subject: Re: RFR(M):8214751: X86: Support for VNNI instruction
> 
> Hi Vivek,
> 
> What applications benefit this optimizations?
> 
> This optimization may prevent some constant folding and others IGVN optimizations and RA since MulAddS2INode is generated too early I think. The only benefit we will have only if vectors are generated. Can you generate vectors without MulAddS2INode? Or create MulAddS2INode just before vectorization and expand it if vectorization failed? I would prefer first solution to have a struct in SuperWord code which find such pattern and try to vectorize it.
> 
> You need to add test to verify correctness of results.
> Add UseAVX == 0 check to predicates which use SSE2 code. Otherwise they may be selected even if UseAVX > 0.
> 
> Thanks,
> Vladimir
> 
> On 12/3/18 8:58 PM, Deshpande, Vivek R wrote:
>> Hi All
>>
>> Could you please review the VNNI VPDPWSSD instruction support with autovectorization.
>> It can vectorize this operation in the loop:
>> out[i] += ((in1[2*i] * in2[2*i]) + (in1[2*i+1] * in2[2*i+1])); More
>> information on VNNI can be found here:
>> https://software.intel.com/sites/default/files/managed/c5/15/architect
>> ure-instruction-set-extensions-programming-reference.pdf
>>
>>
>> The initial performance gains with micro on skylake with AVX3 is 10.8x.
>>    and it generates
>> vmovdqu xmm3, xmmword ptr [rbp+r8*2+0x10] vmovdqu xmm6, xmmword ptr
>> [rdx+r8*2+0x10] vpmaddwd xmm3, xmm6, xmm3 vpaddd xmm3, xmm3, xmmword
>> ptr [r9+rdi*4+0x10] vmovdqu xmmword ptr [r9+rdi*4+0x10], xmm3
>>
>> It can generate vpdpwssd instruction on cascadelake.
>>
>> The webrev is here:
>> http://cr.openjdk.java.net/~vdeshpande/8214751/VNNI/webrev.00/
>> <http://cr.openjdk.java.net/%7Evdeshpande/8214751/VNNI/webrev.00/>
>>
>> The jbs entry for the same is here:
>>
>> https://bugs.openjdk.java.net/browse/JDK-8214751
>>
>> Regards,
>>
>> Vivek
>>