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)
Topic: Pollard's kangaroo ECDLP solver - page 79. (Read 58565 times)
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
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
The list is recommended values is here: https://developer.nvidia.com/cuda-gpus
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)
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)
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
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?
I am using Visual Studio 2019 for compilation, the problem also exists on the compiled version from Jean_Luc.
Which ccap you use for compilation?
Hi,
Does anyone know why my speed is so small, the card is GTX Titan Z.
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.
Hi,
Does anyone know why my speed is so small, the card is GTX Titan Z.
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.
Hi,
Does anyone know why my speed is so small, the card is GTX Titan Z.
i run kangaroo like this
I am using the compiled version of Jean_Luc.
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.
Thanks for the info
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.
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.
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.
I would like to know what speed you can get in Kangaroo.
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
Maybe just make a change in Makefile to use installed/preferred version instead of specified in the file - change the lines 43 to:
CUDA = /usr/local/cuda
CXXCUDA = /usr/bin/g++
CUDA = /usr/local/cuda
CXXCUDA = /usr/bin/g++
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?
OK could give me your input file and how you launched the program ?
Lots of dead kangaroos usually means that you search for a key which is out of the specified range.
I run the program like this
Code:
Kangaroo.exe -t 4 -ws -i save.work2 -w save.work2 -wi 350 in2.txt
In Kangaroo v2.2 I have the same problem with this file, the file will be sent soon in a private message.
Code:
Kangaroo v2.2
Loading: save.work2
Version : 0
DP bits : 13
Start : 0
Stop : FFFFFFFFFFFFFF
Key : --------------------------------------------------------------------
Count : 2405518294016 2^41.129
Time : 2.4d
DP Size : 3.4/4.3GB
DP Count : 114730854 2^26.774
HT Max : 1212 [@ 00C579]
HT Min : 0 [@ 01A688]
HT Avg : 437.66
HT SDev : 522.59
Kangaroos : 0 2^-inf
The expected number of operation is the average number of group operations needed to solve the key (including the DP overhead). It correspond to ~50% probability.
If you use -m 3 and if the search is aborted, you are sure at ~99.7% that the key is not in the given range.
Thank you, now it is clear.
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