Pollard's kangaroo ECDLP solver - page 80.

HardwareCollector

member

Activity: 144

Merit: 10

Quote from: Marynarz on September 01, 2020, 03:37:31 PM

Hi,

Does anyone know why my speed is so small, the card is GTX Titan Z.

I am using the compiled version of Jean_Luc.

Your card is the equivalent of two underclocked GTX 780 Tis and it is performing as expected. It is based on the Kepler architecture which is very old by today's standards.

Marynarz

jr. member

Activity: 40

Merit: 2

Yes, suppose the card is damaged, is it worth fixing it?

PawGo

legendary

Activity: 952

Merit: 1386

And on released version from githuib?

Marynarz

jr. member

Activity: 40

Merit: 2

Quote from: PawGo on September 03, 2020, 01:48:08 PM

Compile with ccap=35 and then see the result. Then try to set grid 30,768.

https://en.m.wikipedia.org/wiki/Thread_block_(CUDA_programming)

30,768,30,768

Code:

GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch
GPUEngine: Kernel: too many resources requested for launch

With other settings, after manually stopping the kangaroo, a black screen appears.

PawGo

legendary

Activity: 952

Merit: 1386

Compile with ccap=35 and then see the result. Then try to set grid 30,768.

https://en.m.wikipedia.org/wiki/Thread_block_(CUDA_programming)

Marynarz

jr. member

Activity: 40

Merit: 2

I set 175,256,175,256 and my image in the monitor turned black and sometimes it flashed to a delicate white color, after restart the image works, does it mean that this card is damaged? is it simply the fault of the drivers?

My friend says that the card has been left unused for 5 years, I will start with replacing the paste with a new one because it does not fulfill its role and it is possible that the card has just overheated

If that doesn't help, I'll just give him back Grin

PawGo

legendary

Activity: 952

Merit: 1386

The list is recommended values is here: https://developer.nvidia.com/cuda-gpus

MrFreeDragon

sr. member

Activity: 443

Merit: 350

Quote from: Marynarz on September 03, 2020, 01:06:53 PM

Code:

Kangaroo v2.2
GPU #0 GeForce GTX TITAN Z (15x192 cores) (Cap 3.5) (6144.0 MB) (Multiple host t
hreads)
GPU #1 GeForce GTX TITAN Z (15x192 cores) (Cap 3.5) (6144.0 MB) (Multiple host t
hreads)

Your ccap looks correct.
Try to play with grid size (change used values 30x384 while find the best ones for your card):

GPU: GPU #0 GeForce GTX TITAN Z (15x192 cores) Grid(30x384)

Marynarz

jr. member

Activity: 40

Merit: 2

Code:

Kangaroo v2.2
GPU #0 GeForce GTX TITAN Z (15x192 cores) (Cap 3.5) (6144.0 MB) (Multiple host t
hreads)
GPU #1 GeForce GTX TITAN Z (15x192 cores) (Cap 3.5) (6144.0 MB) (Multiple host t
hreads)

MrFreeDragon

sr. member

Activity: 443

Merit: 350

Quote from: PawGo on September 03, 2020, 12:47:53 PM

Which ccap you use for compilation?

+1

Yes, right question: ccap depends on the card, it is compute capability of the card.
For example, for Titan Z, ccap=35 (that means version 3.5)

Source: https://en.wikipedia.org/wiki/CUDA

PawGo

legendary

Activity: 952

Merit: 1386

Quote from: Marynarz on September 03, 2020, 12:52:51 PM

I am using Visual Studio 2019 for compilation, the problem also exists on the compiled version from Jean_Luc.

Great, but what is your ccap parameter?

Marynarz

jr. member

Activity: 40

Merit: 2

I am using Visual Studio 2019 for compilation, the problem also exists on the compiled version from Jean_Luc.

PawGo

legendary

Activity: 952

Merit: 1386

Which ccap you use for compilation?

Marynarz

jr. member

Activity: 40

Merit: 2

Quote from: Jean_Luc on September 03, 2020, 08:51:11 AM

Quote from: Marynarz on September 01, 2020, 03:37:31 PM

Hi,
Does anyone know why my speed is so small, the card is GTX Titan Z.

At the beginning of the process, the speed was the same ?
Avoid to have too large hashtable in RAM even if you have enough RAM on your system, it is preferable to use -wsplit and merge workfile offline.

Unfortunately I am not using Kangaroo in server mode.

A few days ago I bought a Titan card and wanted to resume working (previously I used 2 x ASUS GTX 1060 6GB = 460 MK/s) and to my surprise this speed is from the start and no matter what DP is set. I have the latest graphics drivers installed and CUDA 10.2 and the truth is, my hands are dropping, I have no idea where the problem is. Will there be any good soul to help solve this problem?

My motherboard is ASUS CROSSHAIR V FORMULA-Z,
16 GB RAM,
Corsair 850W power supply
AMD FX 8350 processor

I will be very grateful for any help.

Jean_Luc

sr. member

Activity: 462

Merit: 701

Quote from: Marynarz on September 01, 2020, 03:37:31 PM

Hi,
Does anyone know why my speed is so small, the card is GTX Titan Z.

At the beginning of the process, the speed was the same ?
Avoid to have too large hashtable in RAM even if you have enough RAM on your system, it is preferable to use -wsplit and merge workfile offline.

Marynarz

jr. member

Activity: 40

Merit: 2

Hi,

Does anyone know why my speed is so small, the card is GTX Titan Z.

i run kangaroo like this

Code:

Kangaroo.exe -t 0 -d 28 -gpu -gpuId 0,1 -ws -i save.work4 -w save.work4 -wi 600 -o found.txt in2.txt

Code:

Kangaroo v2.2
Loading: save.work4
Start:0
Stop :7FFFFFFFFFFFFFFFFFFFFF
Keys :1
LoadWork: [HashTable 3.0/3.7GB] [20s]
Number of CPU thread: 0
Range width: 2^87
Jump Avg distance: 2^42.96
Number of kangaroos: 2^21.49
Suggested DP: 19
Expected operations: 2^46.56
Expected RAM: 26.7MB
DP size: 28 [0xFFFFFFF000000000]
GPU: GPU #0 GeForce GTX TITAN Z (15x192 cores) Grid(30x384) (119.5 MB used)
SolveKeyGPU Thread GPU#0: creating kangaroos...
GPU: GPU #1 GeForce GTX TITAN Z (15x192 cores) Grid(30x384) (119.5 MB used)
SolveKeyGPU Thread GPU#1: creating kangaroos...
SolveKeyGPU Thread GPU#1: 2^20.49 kangaroos [10.0s]
SolveKeyGPU Thread GPU#0: 2^20.49 kangaroos [10.1s]
[324.91 MK/s][GPU 324.91 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 3.7d)][3.0/3.7G
[512.78 MK/s][GPU 512.78 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.3d)][3.0/3.7G
[520.19 MK/s][GPU 520.19 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.3d)][3.0/3.7G
[484.27 MK/s][GPU 484.27 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.5d)][3.0/3.7G
[452.12 MK/s][GPU 452.12 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.7d)][3.0/3.7G
[429.34 MK/s][GPU 429.34 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.8d)][3.0/3.7G
[416.00 MK/s][GPU 416.00 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[407.24 MK/s][GPU 407.24 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[410.43 MK/s][GPU 410.43 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[408.74 MK/s][GPU 408.74 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[411.46 MK/s][GPU 411.46 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[410.52 MK/s][GPU 410.52 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[411.84 MK/s][GPU 411.84 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[411.98 MK/s][GPU 411.98 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G
[410.49 MK/s][GPU 410.49 MK/s][Count 2^48.60][Dead 0][13.2d (Avg 2.9d)][3.0/3.7G

I am using the compiled version of Jean_Luc.

Marynarz

jr. member

Activity: 40

Merit: 2

Thanks for the info

MrFreeDragon

sr. member

Activity: 443

Merit: 350

Quote from: Marynarz on August 26, 2020, 02:22:19 AM

Does any of the users have such a card? NVIDIA GeForce GTX Titan Z 12GB

I would like to know what speed you can get in Kangaroo.

It should be better than 2080ti. May be it is close to Tesla performance. However I am not sure.

Why do you have such question? If you consider buying this card, you can run the tests before your final decision.

Marynarz

jr. member

Activity: 40

Merit: 2

Does any of the users have such a card? NVIDIA GeForce GTX Titan Z 12GB

I would like to know what speed you can get in Kangaroo.

Bitcoinfan2020

newbie

Activity: 5

Merit: 0

Quote from: Marynarz on August 18, 2020, 04:51:52 AM

Hi, are any of the users using kangaroo version Cuda 8.0? at the moment I can't compile Kangaroo and I need this version. could someone send a compiled version?

Here it is, the latest .exe release.

https://github.com/JeanLucPons/Kangaroo/releases/tag/2.2

Topic: Pollard's kangaroo ECDLP solver - page 80. (Read 60189 times)