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Message-ID: <CAKGDhHUn4tOT_A_yPLnyVyDYBC0kNuhAL1tw9z1w4856CciLJA@mail.gmail.com>
Date: Sat, 4 Jul 2015 17:08:29 +0200
From: Agnieszka Bielec <bielecagnieszka8@...il.com>
To: john-dev@...ts.openwall.com
Subject: Re: PHC: Lyra2 on GPU
2015-07-04 11:54 GMT+02:00 Solar Designer <solar@...nwall.com>:
> On Sat, Jul 04, 2015 at 02:04:26AM +0200, Agnieszka Bielec wrote:
>> I received results:
>>
>> [a@...er run]$ ./john --test --format=lyra2-opencl --dev=5
>> Benchmarking: Lyra2-opencl, Lyra2 [Lyra2 Sponge OpenCL (inefficient,
>> development use only)]... Device 5: GeForce GTX TITAN
>> Local worksize (LWS) 64, global worksize (GWS) 2048
>> DONE
>> Speed for cost 1 (t) of 8, cost 2 (m) of 8, cost 3 (c) of 256, cost 4 (p) of 2
>> Raw: 6023 c/s real, 5965 c/s virtual
>>
>> [a@...er run]$ ./john --test --format=lyra2-opencl
>> Benchmarking: Lyra2-opencl, Lyra2 [Lyra2 Sponge OpenCL (inefficient,
>> development use only)]... Device 0: Tahiti [AMD Radeon HD 7900 Series]
>> Local worksize (LWS) 64, global worksize (GWS) 2048
>> DONE
>> Speed for cost 1 (t) of 8, cost 2 (m) of 8, cost 3 (c) of 256, cost 4 (p) of 2
>> Raw: 7447 c/s real, 51200 c/s virtual
>>
>> before optimizations speed was equal to 1k
>
> Cool. And these are much better than what you were getting with Lyra2
> authors' CUDA code, right?
yes, but they claimed that theirs implementation isn't optimal
this is the best result I gained
[a@...er run]$ ./john --test --format=lyra2-cuda
Benchmarking: Lyra2-cuda, Lyra2 [Lyra2 CUDA]... DONE
Speed for cost 1 (t) of 8, cost 2 (m) of 8
Raw: 1914 c/s real, 1932 c/s virtual
my first version in opencl had speed more than 1k but I don't remember exactly
>
> Are these higher speeds reproducible on actual cracking runs? Please test.
what means 'reproducible on actual cracking runs' ?
>
>> my optimizations are based on transfer one table to local memory and
>> copying small portions of global memory into local buffers, I didn't
>> saw any sense i coalescing and I didn't tried it
>
> OK.
>
> Is the "copying small portions of global memory into local buffers" like
> prefetching? Or are those small portions more frequently accessed than
> the rest? In other words, why is this optimization effective for Lyra2?
I'm copying data in several separate for loops.only sometimes one
element is accessed two times, mostly it's 1 time, but these portions
are small anyway, 12 ulong's for one random pointer to global memory
(4 is max) so I decided copy even if something is accessed only once,
and I tried to copy bigger portions at once but speed was worse, even
if something is accessed only once it's faster with copying on AMD GPU
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