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Date: Fri, 08 May 2015 19:08:18 -0300
From: Marcos Simplicio <mjunior@...c.usp.br>
To: discussions@...sword-hashing.net
Subject: [PHC] GPU benchmarks: Lyra2+yescrypt (was: Another PHC candidates
 "mechanical" tests (ROUND2))

> -------- Forwarded Message --------
> Assunto:     Re: [PHC] GPU benchmarks: Lyra2+yescrypt (was: Another PHC
> candidates "mechanical" tests (ROUND2))
> Data:     Thu, 7 May 2015 22:11:00 +0300
> De:     Solar Designer <solar@...nwall.com>
> Responder a:     discussions@...sword-hashing.net
> Para:     discussions@...sword-hashing.net
> 
> 
> 
> Marcos,
> 
> On Thu, May 07, 2015 at 01:08:13PM -0300, Marcos Simplicio wrote:
>> It took some time, but we finally completed the GPU benchmarks mentioned
>> in the e-mail below, both for Lyra2 and yescrypt. We did not use djm34's
>> yescrypt GPU implementation mentioned in another thread, though, because
>> while Lyra2 has been in their repository for a few months, we had
>> already adapted the yescrypt-opt version when we learned the news a few
>> days ago... Some optimizations made there might apply to our code too,
>> so we will take a look.
> 
> Yes, djm34's code looks more optimal to me.  yescrypt-opt actually isn't
> as optimized as yescrypt-simd, not only in terms of lacking explicit SIMD.
> It also includes blk{cpy,xor}, whereas those are avoided in -simd and
> are avoidable in -opt.  I just didn't bother yet (in part because their
> relative performance impact is lower when the code is non-SIMD; but on
> GPU you get SIMD code, it's just implicit).
> 

Our GPU specialist is taking a look at it. We will update our graphs
with the new values if djm34's is indeed faster.

> This makes me wonder: are you benchmarking your CUDA code against
> yescrypt-simd or possibly against yescrypt-opt on CPU?  Your
> readme_attacks.txt says: "We used the PHC code for each algorithm and
> the fastest version (generally, the vectorized version)."  This suggests
> that you used yescrypt-simd on CPU, but I'd like to make sure.

We actually tried every version, and kept the fastest one in each
platform: our GPU code is based on yescrypt-opt (and also Lyra2
non-SSE), while our CPU code is yescrypt-simd (the one you named "best"
in the repository).

> 
>> Anyhow, the partial results indicate that Lyra2 is actually more
>> GPU-resistant than yescrypt for a memory usage of 256 kB to 2 MB, at
>> least for our GPU (GeForce GTX TITAN),
> 
> This is very interesting if so.  But I don't buy your results yet, as I
> explained in another message.  Your reported yescrypt CPU speeds are in
> weird units, and if I try to convert them (even though they can't be),
> I get way lower speeds than what I am seeing.
> 
> Your readme_attacks.txt says "The password derivation time is the total
> test time divided by number of passwords tested." under "GPU attacks".
> Great, but is it the same on CPU?  If not, that's wrong.  If yes, it
> doesn't match my results (by far).

I also discussed that in another thread: our numbers are way closer to
those obtained by Milan than yours are (again, this does not mean any of
them are wrong, since the platforms are different). Hence, while you
have all the right to take our numbers with skepticism, they are not as
strange as you suggested.

Anyway, the CPU and GPU tests are independent, so the comparisons
suggested in the third column of our figures can be updated simply by
dividing new/our CPU numbers by new/our GPU numbers for any algorithm
having a GPU implementation.

> 
> I think you actually used a different metric on CPU, per
> readme_attacks.txt:
> 
> "The CPU benchmarks focused in legitm usage of the kdfs.
> 
>     To obtain the medium execution time:
>     - We executed "n" times each derivation;
>     - With the parameters seted accordingly with parallelism and memory
> usage desired."
> 
> While this would make sense for KDF use at large m_cost, it doesn't for
> password hashing use at low m_cost.  You should use a throughput figure
> for CPU, just like you do for GPU.

Like Milan Broz's tests, I imagine, which makes perfect sense. We will
use the exact same methodology for p=1 (as done already) to 12.


>> Since the results may change to other GPUs, we placed the code employed
>> in our git (https://github.com/leocalm/Lyra/tree/master/GPU_attacks ),
>> so anyone can confirm/refute our numbers. Also, any bug report or
>> optimization suggestion is very welcome! We tried a few tricks and
>> checked the test vectors, but we may have missed something.
> 
> I appreciate this.  I took a look via GitHub's web interface.
> Unfortunately, this fails:
> 
> $ git clone https://github.com/leocalm/Lyra/tree/master/GPU_attacks
> Cloning into 'GPU_attacks'...
> error: The requested URL returned error: 403 while accessing
> https://github.com/leocalm/Lyra/tree/master/GPU_attacks/info/refs
> fatal: HTTP request failed

Please try to get it from the root directory:
https://github.com/leocalm/Lyra/

> 
>> On 26-Mar-15 15:24, Solar Designer wrote:
>> > On Thu, Mar 26, 2015 at 02:29:29PM -0300, Marcos Simplicio wrote:
>> > Yes, and in your CPU benchmarks too, so you'd be comparing GPU attacks
>> > on Lyra2 vs. bcrypt at the same defensive running time for them (on
>> CPU).
>>
>> We did not include bcrypt to the benchmarks because we wanted to have
>> comparisons against a memory-hard scheme, so we did so for yescrypt.
> 
> I'd make sense to include bcrypt, too.  Especially if you claim that
> your GPU outperforms CPU at yescrypt despite of pwxform's rapid random
> lookups, it becomes extremely relevant that you show the same for
> bcrypt, because yescrypt-simd's rapid random lookups are on par with
> bcrypt's when both are run defensively on a modern x86 CPU.
> 

That makes sense, and can be added to our TODO list and eventual
academic publication (thank you for the advice!).

> 
>> The only situation in which we got Lyra2 running faster on our GPU than
>> on our CPU was for p=1 and 8 threads per warp (for 256KB).
> 
> You mean when you used unoptimal settings on GPU and didn't fully use
> the CPU?  This doesn't count, for either or both of these reasons.

It is actually:

1) Optimal settings for GPU: the setting with highest throughput
2) One possible setting for CPU: it corresponds to a a constrained
device that cannot afford GiBs of memory in their KDF operation, or to
lightly loaded server (e.g., it cannot afford to use a lot of memory
because it was designed for peak usage much higher than the current one,
or because other tasks consume a lot of memory and, thus, the
authentication processes should not get too much memory).

So, I would say it does count, but also that there is also a wider
picture that would be interesting to explore (="highly loaded server"),
much like done in Milan Broz's Figure 10.

> [...]
> I am sorry that my messages might sound dismissive.  Once again, I
> appreciate your work on this a lot, and I think you got very close to
> producing valuable results here.

I respectfully disagree that we have no valuable results yet, for the
reasons mentioned above and in the previous e-mail. However, we do
prefer constructive criticism (as you provided!) to plain acceptance,
since this will help to improve this study.

Hence, there is absolutely no need to apologize: quite the opposite,
even though we do not agree with every point you raised, we are very
thankful for the feedback! It will probably save us a lot of work
responding to peer reviewers in the future :)

BR,

Marcos.

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