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Code now works on cards with compute mode 3.5 (Titan, GTX780).
Tested on GTX-780 :-) It is about 275 MH/s.
any hope for compute 2.1? also how does that rate vs your cgminer speed Automatic GPU architecture chooser was added it works on any architecture from 1.0 to 3.5. The relevant cubin file should be in cmake-rpcminer. I added these files on github, so use them. |
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Code now works on cards with compute mode 3.5 (Titan, GTX780).
Tested on GTX-780 :-) It is about 275 MH/s.
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Can you explain the increase of hash rate? I thought the original miner got all could be achieved on sm30...
I'll start digging into the code, but I'd like to read high-level explanation.
Everything about the used register-count. If a CUDA code uses too many registers 2 things can happen: you can run the code on less threads, or you can tell the nvcc compiler to force use less register. There is no magic if your code needs 72 register, but you force the compiler use only 63 will mean 9 register will be in local memory (available via spill loads), and this is slower then the registers. So optimizing a CUDA code usually means write a code that can run with less register. On the other hand you can use a lot of special functions and types (I moved the input storing to __constant__ memory ). Memory reading and writing is slow, avoid unnecessary memory ops. And there are a lot of other tricks... |
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Any update on binaries for Windows? I've tried compiling with Cygwin, but cmake complains it can't find CUDA_CUDART_LIBRARY. $ cmake ../
-- The C compiler identification is GNU 4.5.3
-- The CXX compiler identification is GNU 4.5.3
CMake Warning at /usr/share/cmake-2.8.9/Modules/Platform/CYGWIN.cmake:15 (message):
CMake no longer defines WIN32 on Cygwin!
(1) If you are just trying to build this project, ignore this warning or
quiet it by setting CMAKE_LEGACY_CYGWIN_WIN32=0 in your environment or in
the CMake cache. If later configuration or build errors occur then this
project may have been written under the assumption that Cygwin is WIN32.
In that case, set CMAKE_LEGACY_CYGWIN_WIN32=1 instead.
(2) If you are developing this project, add the line
set(CMAKE_LEGACY_CYGWIN_WIN32 0) # Remove when CMake >= 2.8.4 is required
at the top of your top-level CMakeLists.txt file or set the minimum
required version of CMake to 2.8.4 or higher. Then teach your project to
build on Cygwin without WIN32.
Call Stack (most recent call first):
/usr/share/cmake-2.8.9/Modules/CMakeSystemSpecificInformation.cmake:36 (INCLUDE)
CMakeLists.txt:3 (PROJECT)
-- Check for working C compiler: /usr/bin/gcc.exe
-- Check for working C compiler: /usr/bin/gcc.exe -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working CXX compiler: /usr/bin/c++.exe
-- Check for working CXX compiler: /usr/bin/c++.exe -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Boost version: 1.53.0
-- Found the following Boost libraries:
-- date_time
-- filesystem
-- program_options
-- regex
-- system
-- thread
-- Found OpenSSL: /usr/lib/libssl.dll.a;/usr/lib/libcrypto.dll.a (found version "1.0.1e")
-- Looking for include file pthread.h
-- Looking for include file pthread.h - found
-- Looking for pthread_create
-- Looking for pthread_create - found
-- Found Threads: TRUE
CMake Error at /usr/share/cmake-2.8.9/Modules/FindPackageHandleStandardArgs.cmake:97 (MESSAGE):
Could NOT find CUDA (missing: CUDA_CUDART_LIBRARY)
Call Stack (most recent call first):
/usr/share/cmake-2.8.9/Modules/FindPackageHandleStandardArgs.cmake:288 (_FPHSA_FAILURE_MESSAGE)
cmake-modules/FindCUDA.cmake:682 (find_package_handle_standard_args)
CMakeLists.txt:32 (FIND_PACKAGE)
-- Configuring incomplete, errors occurred!
If anyone has any how-to's or some kind of guidance on how to get this working, please share. Is your CUDA_TOOLKIT_ROOT_DIR environment variable set? |
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would be great to get some more MH out of my 560ti, currently 83 MH
waiting for win7 64bit binaries
have you fixed rpc-miner-cuda so it doesnt crash the display driver when closing it, or was that a windows issue
Well, I don't know, I have dedicated cards for CUDA (no display or X attached to it) |
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260 MH/s to slow.  Unfortunately NV cards not so good for mining. Buy AMD or some asic if you want more or you can design a new asic. |
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what performance increase is expected compared to guiminer or cgminer?
Well actually CG miner is quite good, I don't expect more then 10%. For Titan and GTX780, if somebody will do some optimalization CUDA can be better. If I have enough money I'll buy a 780, and try it. |
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With this miner I manage to get from my GTX480 from 110 till 140 Mh/s at default, thanks.
You welcome! |
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I have written instructions in the readme files, but I write here some important information:
- Use 4.2 if you compile the cu files. CU files should be compiled as a second pass and compiled next to the executable
- I've added precompiled cubin files to the project, it is OS independent so you can copy it next to the executable file, if you don't want to compile the cu files
- The program has an auto-tuning feature, if you don't define the gpuGrid, and gputhreads, it will find the best configuration, it is a wider search then the original (it can take several minutes!)
- Once it is done you can use it next time
- It does't have native stratum support, use a proxy instead
- For measuring the time please run it for at least a few minutes
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Has anyone actually gotten an Nvidia card to mine efficiently enough to pay for it's own power consumption? Or are these solely for people mining with "free" electricity?
I think the short answer is no. I don`t think anyone bought an nvidia card just for mining. I think (just like me) we got nv card because other reasons (for me, I use it for work). In the computer spare time, mining can run, but it`s not worth unless you have "free" electricity. |
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Source has been released. You can found here: https://github.com/icedev576/rpcminer-optcudaPlease follow the instructions, to build and run in: README, README.md, HOW-TO files Anyone who was able to build any variation of rpcminer, can this also. Compiled Binaries for different OS, may come later.
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Any news from here? I am still waiting the sourcecode.
Sorry I am little busy at my job, I don`t have time for this today. I`ve created the github repo, but it is relatively empty now. |
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Hey man! Very interested in testing your code on a GTX TITAN!
Sorry currently I am only optimalized for 4xx to 6xx, the titan is a different issue. maybe later |
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Hi!
I`ve tried the LiteCoin for a couple of days, but my income was nearly exactly to same when mining BTC (in USD), so I switched back to bitcoin. I don`t want to fragment this small amount of income. Anyway if LTC will become more valuable I will give a next shoot to it.
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I`ve managed to merge the source. Tomorrow I will upload the source code to github. I am also thinking to create an cuda mining survival guide to add some help for nvidia card owners.
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HI Kenshin23!
Can you give me some information: what OS you use is it 64bit win or linux(distro?)? And the most important are you using rpcminer or something else?
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Thomassie12 are you still mining or you give up? What kind of miner do you use or used?
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Well, I read the whole "NVIDIA Kepler (K20) from 134MHash/s to 330MHash/s with CUDA" topic. As far I know psychocoder has optimalized the cuda code for the GK110 architecture (sm_35 in cuda). There was only 2 card supporting this: Tesla K20, Geforce Titan, but from yesterday you can buy the Geforce 780! It is the same arch, a little cheaper and more consumer. If I had enough donations, I will buy one.
My solution is speeding up the older generations: Fermi and Kepler(sm_20, sm_30), that means geforce 4xx to 6xx. So I hope I can merge them together.
I sent a binary to gaborjakab, others please wait and keep me posted.
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My code is a mess now, so it isn`t ready for a public release, but because gaborjakab uses almost the same hardware, and OS like me, I can send a binary from the current stage just for the test. So if you like please send a private message.
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This is interesting. I am reading the post, maybe I can mix the solutions together.
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