Topic: [ANN] cudaMiner & ccMiner CUDA based mining applications [Windows/Linux/MacOSX] - page 1049. (Read 3426947 times)

Thanks for this. Great explanation. Got about 60kh/s extra on my GTX 780!

Hi everyone, I wrote a small Treatise on Cuda Miner, mind helping me check it over? (Much updated! wow!)
http://www.reddit.com/r/Dogecoinmining/comments/1tguse/a_treatise_on_cuda_miner/

probably an unstable card due to excessive overclocking ...

have you heard of the lookup_gap feature of the OpenCL based miner? reduces the scratchpad size by factor 2 or 3 and replaces the lookups by some extra computation. Not sure if nvidia cards have the computational reserves, but we could try...the funnel shifter seems to help a bit in creating some breathing room. compute 3.5 devices are definitely memory limited when hashing.

Doubling up keys in a clever way might get that to 90 but at the cost of probably unacceptable register pressure.  I tried it once and threw away the code, but there are a few other ways to imagine doing it.

It's really hard to beat the raw number of ALUs those AMD devices have when the code is as trivially parallel as brute-force hashing.

So I am just mining a bit for the experience and its mostly going well but this weird thing. After a couple accepted my hash rate goes out of control and it never works again until I reboot my computer. If this is a known issue or someone else has this if you could let me know. Thanks and sorry if this is newbish.

You could also optimize on the low-end GT 640 (GDDR 5 version). It has Compute 3.5, does around 105 kHsh/s with OC and I generally found its results to scale up pretty linearly with the number of SMX. i.e. scaling it up to 12 SMX (like the GTX 780) yields some 630 kHash/s which people actually seem to be hitting when overclocking their devices.

EDIT: I did some profiling with Cuda 5.5 Visual Profiler on a Compute 3.0 device recently (also 2 SMX, a laptop part). I found that the artithmetic units were pretty maxed out. And it also showed an 80% efficiency in the instruction scheduler. Meaning that the dual issue feature in each SMX four warp schedulers was pretty nicely utilized. The occupancy on each SMX was 100%, which is perfect. Memory accesses were fully coalesced 128 byte transactions. Can't get any better than this.

Semi-idle question:  Is there community interest in sponsoring some more optimization of the cudaminer code for Kepler GK104 and GK110-based cards?

In honesty, I think I threw my best optimization ideas at the version most of you are already running.  *grins*  But there's probably another 5% here and there, which could translate into, say, at least a 10-20kh/sec boost on faster cards.

  -Dave

Oh, well that makes me sad. My 2 cards have 2 diff TDP.. 110% and 115%.. which i find odd..

Anyway, thanks for cudaminer, specially the December 18th update.. amazing speed boots!

I am peaking out at 590 kHash/s per device. Meh. limited to 106% TDP, by the way.

Im actually in line for the Step-Up program by EVGA to upgrade to TI's for free. You saying its not worth it ?

yeah, keep making me sorry for buying 3x 780 Ti ...

The extra power draw of the 3 additional SMX in the Ti prevents any meaningful overclocking, it seems.

Christian

yeah, keep making me sorry for buying 3x 780 Ti ...

The extra power draw of the 3 additional SMX in the Ti prevents any meaningful overclocking, it seems.

Christian

2 x EVGA 780 Classified overclocked to 1300MHz
cudaminer settings: -i 0 -H 1 -m 1 -l T12x16

A Treatise on CUDAMiner
Thanks CBuchner for creating Cudaminer!
If this helped please upvote for other puppy miners!
I've added popular cards and configs to the bottom.
Disclaimer: I'm like every other shibe.. I can make mistakes, if something doesn't look right, please, please correct me! Thanks!
Some edits: A Minor Observation. -c 1 performs better than -c 2 generally.
Hi! So you're looking to Mine using your Nvidia Card, don't know how to setup CUDA Miner?
The basic format for CUDA Miner's .bat file will be.
Stratum (For HTTP: Replace stratum+tcp with http):
Ex: cudaminer -H 0 -i 1 -l auto -C 2 -o stratum+tcp://xyz.yourpool.com:porthere -u username.worker -p password
What each flag does:
[-H] scrypt also has a small SHA256 component to it: 0 hashes this single threaded on the CPU. 1 to enable multithreaded hashing on the CPU. 2 offloads everything to the GPU (default)
[-i] list of flags (0 or 1) to enable interactive desktop performance on individual cards. Use this to remove lag at the cost of some hashing performance. Do not use large launch configs for devices that shall run in interactive mode - it's best to use autotune!
This setting set at 0 will cause your GPU to run at 100% and most likely will cause lag while even tabbing through your browser! Set at 1 if you're trying to use your PC while mining.
[-l] specify the kernel launch configuration per device. This replaces autotune or heuristic selection. You can pass the strings "auto" or just a kernel prefix like L or F or K or T to autotune for a specific card generation or a kernel prefix plus a lauch configuration like F28x8 if you know what kernel runs best (from a previous autotune).
[-C] list of flags (0 or 1 or 2) to enable use of the texture cache for reading from the scrypt scratchpad. 1 uses a 1D cache, whereas 2 uses a 2D texture layout. Cached operation has proven to be slightly faster than noncached operation on most GPUs.
In Depth & Getting the most out of your card:
Well, let me start off with a checklist.
Do you have the latest version of CUDA Miner?
If Yes then Move on.. If no (Or you're not sure), then go here: https://bitcointalksearch.org/topic/ann-cudaminer-ccminer-cuda-based-mining-applications-windowslinuxmacosx-167229
Do you have the latest drivers installed for your video card?
If yes.. carry on! If not.. http://www.nvidia.com/Download/index.aspx
Well then, now that that's done...
A few things you'll need to know before going on..
What video card do you have?
If you know.. Carry on. If you're not sure.. Then Install GPU-Z to find out!
http://www.techpowerup.com/downloads/SysInfo/GPU-Z/
Now that you know what video card you have, you'll have to find out what compute version it is using. Find your video card on this chart. (For ease, use ctrl + F on windows and then type in the # of your card)
Compute Version:
1.0
G80, G92, G92b, G94, G94b GeForce GT 420, GeForce 8800 Ultra, GeForce 8800 GTX, GeForce GT 340, GeForce GT 330, GeForce GT 320, GeForce 315, GeForce 310, GeForce 9800 GT, GeForce 9600 GT, GeForce 9400GT, Quadro FX 5600, Quadro FX 4600, Quadro Plex 2100 S4, Tesla C870, Tesla D870, Tesla S870 1.1
G86, G84, G98, G96, G96b, G94, G94b, G92, G92b GeForce G110M, GeForce 9300M GS, GeForce 9200M GS, GeForce 9100M G, GeForce 8400M GT, GeForce G105M, Quadro FX 4700 X2, Quadro FX 3700, Quadro FX 1800, Quadro FX 1700, Quadro FX 580, Quadro FX 570, Quadro FX 470, Quadro FX 380, Quadro FX 370, Quadro FX 370 Low Profile, Quadro NVS 450, Quadro NVS 420, Quadro NVS 290, Quadro NVS 295, Quadro Plex 2100 D4, Quadro FX 3800M, Quadro FX 3700M, Quadro FX 3600M, Quadro FX 2800M, Quadro FX 2700M, Quadro FX 1700M, Quadro FX 1600M, Quadro FX 770M, Quadro FX 570M, Quadro FX 370M, Quadro FX 360M, Quadro NVS 320M, Quadro NVS 160M, Quadro NVS 150M, Quadro NVS 140M, Quadro NVS 135M, Quadro NVS 130M, Quadro NVS 450, Quadro NVS 420, Quadro NVS 295
1.2
GT218, GT216, GT215 GeForce GT 240, GeForce GT 220, GeForce 210, GeForce GTS 360M, GeForce GTS 350M, GeForce GT 335M, GeForce GT 330M, GeForce GT 325M, GeForce GT 240M, GeForce G210M, GeForce 310M, GeForce 305M, Quadro FX 380 Low Profile, NVIDIA NVS 300, Quadro FX 1800M, Quadro FX 880M, Quadro FX 380M, NVIDIA NVS 300, NVS 5100M, NVS 3100M, NVS 2100M
1.3
GT200, GT200b GeForce GTX 280, GeForce GTX 275, GeForce GTX 260, Quadro FX 5800, Quadro FX 4800, Quadro FX 4800 for Mac, Quadro FX 3800, Quadro CX, Quadro Plex 2200 D2, Tesla C1060, Tesla S1070, Tesla M1060
2.0
GF100, GF110 GeForce GTX 590, GeForce GTX 580, GeForce GTX 570, GeForce GTX 480, GeForce GTX 470, GeForce GTX 465, GeForce GTX 480M, Quadro 6000, Quadro 5000, Quadro 4000, Quadro 4000 for Mac, Quadro Plex 7000, Quadro 5010M, Quadro 5000M, Tesla C2075, Tesla C2050/C2070, Tesla M2050/M2070/M2075/M2090
2.1
GF104, GF106 GF108，GF114, GF116, GF119 GeForce GTX 560 Ti, GeForce GTX 550 Ti, GeForce GTX 460, GeForce GTS 450, GeForce GTS 450, GeForce GT 640 (GDDR3), GeForce GT 630, GeForce GT 620, GeForce GT 610, GeForce GT 520, GeForce GT 440, GeForce GT 440, GeForce GT 430, GeForce GT 430*, GeForce GTX 675M, GeForce GTX 670M, GeForce GT 635M, GeForce GT 630M, GeForce GT 625M, GeForce GT 720M, GeForce GT 620M, GeForce 710M, GeForce 610M, GeForce GTX 580M, GeForce GTX 570M, GeForce GTX 560M, GeForce GT 555M, GeForce GT 550M, GeForce GT 540M, GeForce GT 525M, GeForce GT 520MX, GeForce GT 520M, GeForce GTX 485M, GeForce GTX 470M, GeForce GTX 460M, GeForce GT 445M, GeForce GT 435M, GeForce GT 420M, GeForce GT 415M, GeForce 710M, GeForce 410M, Quadro 2000, Quadro 2000D, Quadro 600, Quadro 410, Quadro 4000M, Quadro 3000M, Quadro 2000M, Quadro 1000M, NVS 5400M, NVS 5200M, NVS 4200M
3.0
GK104, GK106, GK107 GeForce GTX 770, GeForce GTX 760, GeForce GTX 690, GeForce GTX 680, GeForce GTX 670, GeForce GTX 660 Ti, GeForce GTX 660, GeForce GTX 650 Ti BOOST, GeForce GTX 650 Ti, GeForce GTX 650, GeForce GTX 780M, GeForce GTX 770M, GeForce GTX 765M, GeForce GTX 760M, GeForce GTX 680MX, GeForce GTX 680M, GeForce GTX 675MX, GeForce GTX 670MX, GeForce GTX 660M, GeForce GT 750M, GeForce GT 650M, GeForce GT 745M, GeForce GT 645M, GeForce GT 740M, GeForce GT 730M, GeForce GT 640M, GeForce GT 640M LE, GeForce GT 735M, GeForce GT 730M, Quadro K5000, Quadro K4000, Quadro K2000, Quadro K2000D, Quadro K600, Quadro K500M, Tesla K10
3.5
GK110, GK208 GeForce GTX TITAN, GeForce GTX 780, GeForce GT 640 (GDDR5), Quadro K6000, Tesla K20 '*' - OEM-only products (Thanks Wikipedia!)
Now.. Moving on and now that you know what version you have..
We now can find out what Kernel CUDA Miner is best suited to using! Available kernel prefixes are: L - Legacy cards (compute 1.x) F - Fermi cards (Compute 2.x) S - Kepler cards (currently compiled for Compute 1.2) - formerly best for Kepler K - Kepler cards (Compute 3.0) - based on Dave Andersen's work. Now best for Kepler. T - Titan, GTX 780 and GK208 based cards (Compute 3.5) X - Experimental kernel. Currently requires Compute 3.5 (Copied from the CUDAMiner Readme) For Legacy Cards you're best off using auto.
Now find the # of SM(X) units for your card here: http://en.wikipedia.org/wiki/Comparison_of_Nvidia_graphics_processing_units
Fermi is limited to 16 Warps per SM Unit Kepler is limited to 32 Warps per SMX Unit.
If you're on Fermi, with The 560 Ti which has 8 SM units your .bat file will look something like: cudaminer -H 0 -i 1 -l F8x16 -C 2 -o stratum+tcp://xyz.yourpool.com:porthere -u username.worker -p password
If you're using Kepler, with the 660 (Seems to be a popular card), which has 5 SMX Units your .bat will look like: cudaminer -H 0 -i 1 -l K5x32 -C 2 -o stratum+tcp://xyz.yourpool.com:porthere -u username.worker -p password
Titan should be the same as Kepler. (Although someone else may know more on this topic..)
Ta-Da!
To get the most out of your card, you can tweak the -H and -C with 0 1 or 2. I would not recommend using -i 0 if you are trying to browse the web while using your computer, things can stutter, a lot, and annoy you.
WOW! Much hash. http://s15.postimg.org/onsy6sdjf/doge2.jpg
General Mining Tips:
Be sure to find a good pool of course! Try to find a PPLNS Pool with 0-1% fee. I'm not going to suggest any, I don't want to seem biased. There are many good pools! (Thanks Crazypotatoes on doges.org for suggesting this)
Use GPU-Z to monitor temperatures on your card. If it gets too hot you may want to shut it down. Mining doges isn't worth it at the expense of your computer and or video card. (Crazypotatoes again)
Use MSI Afterburner to increase your fan speeds. (Don't Overclock if you're not sure about what you're doing. There are many guides on this but I don't think its worth it if you're not sure what you're touching.) (Yep Crazypotatoes)
Some cards and configs:
560 Ti: -H 0 -i 1 -l F8x16 -C 1 -m 1
660: -H 0 -i 1 -l K5x32 -C 1 -m 1
670:-H 0 -i 1 -l K7x32 -C 1 -m 1
780: -H 1 -i 1 -l T9x20 -C 2 or -H 1 -i 1 -l T12x32 -c 1