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Date: Sat, 20 Sep 2014 15:14:12 +0400
From: Solar Designer <>
Subject: Re: [PHC] Multiply with CUDA

On Fri, Sep 19, 2014 at 07:00:24PM -0500, Steve Thomas wrote:
> I heard some people talking about multiply being slow on GPUs

Yes, as well as other instructions - in terms of latency.

> but still a little faster than CPUs.

I guess you mean in terms of throughput?  Per multiprocessor vs. per core?

> This is why it's slow on Nvidia cards:
> 5.4.1. Arithmetic Instructions

Thanks!  This only talks about throughput, not latency, although latency
is mentioned elsewhere on this page:

"If all input operands are registers, latency is caused by register
dependencies [...]
Execution time varies depending on the instruction, but it is typically
about 22 clock cycles for devices of compute capability 1.x and 2.x and
about 11 clock cycles for devices of compute capability 3.x"

It is unclear whether multiply instructions possibly have a higher than
this minimum latency.

If we have to combine multiple smaller multiplies to build a bigger one,
the total latency may grow.  (Except when it's merely two separate
instructions for low 32 and high 32 bits of outputs, which I guess may
execute in parallel.)

> Some CPUs have a higher latency on the high part.


> Intel's Nehalem is 10 vs 3, but most are closer or no difference.

Per GenuineIntel00106A2_Nehalem-EP_InstLatX64.txt, the 10 cycles is only
for high 64 bits of 128-bit result.  It does not apply for high 32 bits
of 64-bit result.  In fact, PMULUDQ on Nehalem produces the full 64-bit
results in 3 cycles (scalar instructions producing 64-bit results are 3
or 4.8? cycles depending on which instruction you use).

> Newer CPUs can do 64bit*64bit=128bit with a throughput of 1 per cycle and a
> latency of 3 cycles (

I recall it's at best 4 cycles for the upper 64 bits (RDX), except maybe
on low-clocked AMD APUs (would need to double-check), per the files at

3 cycles is best for the lower 64 bits of result (RAX).

> When comparing
> CPUs and GPUs with hash function speeds GPUs are ~10x faster than optimized SIMD
> CPU code. So we're losing SIMD with multiply so that's a 8x hit. GPUs have a
> similar hit on speed while doing smaller multiplies which is another ~4x
> slowdown.

You lost me here.  In what case are we "losing SIMD with multiply"?  Do
you mean e.g. when we use specifically the 64x64->128 multiply on CPU?

One of the reasons why I don't use 64x64->128 in yescrypt is that
64x64->128 is not directly available on 32-bit CPUs and in 32-bit mode
on 64-bit CPUs.  With 32-bit CPUs/mode in mind, it's 32x32->64 max, and
we do have SIMD with that.

> Last note, interleaving MULX (umul128), ADCX (_addcarryx_u64), and ADOX
> (_addcarryx_u64) with VPMULUDQ (_mm256_mul_epu32) might get better performance
> on CPUs. MULX and VPMULUDQ should be similar in speed since VPMULUDQ can do
> 4x(32bit*32bit=64bit) but there's 4x more work to do than doing 64bit*64bit=128.
> Interleaving them should mask some of the latency.

I view potential SIMD/scalar interleaving as implementation detail, as
long as the hashing scheme provides sufficient/tunable parallelism.

Why do you say that "4x(32bit*32bit=64bit)" is "4x more work" than
"64bit*64bit=128"?  In terms of die area, I'd expect these to be
similar, but in terms of latency I'd expect Nx(32x32->64) to take a cycle
less (like 3 vs. 4 if both are optimized for lowest real time latency,
which is what we actually see for these in some CPUs).


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