GeForce GTX 680 are now available! Please post hashing results here.

[The-Real-Link]

  Yeah, as you guys said it just doesn't seem right in theory.  Whether the CUDA miner or something else needs to be adjusted or re-written for the Kepler architecture is just my guess, it's too bad to not see it mine well.

  FWIW, Folding @ Home (Stanford) has also said they have to recompile their program to work with the new architecture.  Thus while normally Folding is a strong suit for Nvidia, it also is "broken" on the Kepler cards for the moment.

  Might also just need a newer driver.  Hopefully if that's the case, Nvidia won't take 3 months to release one.  Normally it seems like they get new cards' drivers out very fast (updated ones I mean, rather than the stock).  Here's hoping!

[tacotime]

  Yeah, as you guys said it just doesn't seem right in theory.  Whether the CUDA miner or something else needs to be adjusted or re-written for the Kepler architecture is just my guess, it's too bad to not see it mine well.

  FWIW, Folding @ Home (Stanford) has also said they have to recompile their program to work with the new architecture.  Thus while normally Folding is a strong suit for Nvidia, it also is "broken" on the Kepler cards for the moment.

  Might also just need a newer driver.  Hopefully if that's the case, Nvidia won't take 3 months to release one.  Normally it seems like they get new cards' drivers out very fast (updated ones I mean, rather than the stock).  Here's hoping!

Folding @ Home is broken because nVidia broke it.  The cards have way less DP/SP floating point performance than a 560 Ti.  It's part of nVidia's new tactic of making their lower end architecture useful only for gaming.

[ssateneth]

  Yeah, as you guys said it just doesn't seem right in theory.  Whether the CUDA miner or something else needs to be adjusted or re-written for the Kepler architecture is just my guess, it's too bad to not see it mine well.

  FWIW, Folding @ Home (Stanford) has also said they have to recompile their program to work with the new architecture.  Thus while normally Folding is a strong suit for Nvidia, it also is "broken" on the Kepler cards for the moment.

  Might also just need a newer driver.  Hopefully if that's the case, Nvidia won't take 3 months to release one.  Normally it seems like they get new cards' drivers out very fast (updated ones I mean, rather than the stock).  Here's hoping!

Folding @ Home is broken because nVidia broke it.  The cards have way less DP/SP floating point performance than a 560 Ti.  It's part of nVidia's new tactic of making their lower end architecture useful only for gaming.

just means amd is gonna get that much more money from people that want to use gpus for gpgpu since amd gpgpu is hugely better than anything nvidia has ever offered

[bulanula]

Bumping this because I want some REAL results this time around.

I think that people have given up on the Kepler for mining just because the kernels we have now are totally NOT optimized for it and that is why it gets only 100 MHash/s.

With more kernel development I am pretty sure that this card will be a killer mining card.

Maybe someone is holding back the code and mining at over 400 mhash/s

Too bad I am not a coder otherwise I would have done this myself.

I just find it really hard to believe a GTX 580 gets 140 mhash/s and this POS Kepler gets lower at 100 mhash/s ...

Also, while we are on the subject, how is this doing for F@H : did they develop that new Kepler-optimized client that Nvidia was promising or not ?

[Buckwheet]

F@H has not released a Kepler aware core with optimizations yet. Using the currently available cores GTX680 is performing on par with GTX 560 Ti.

[Gabi]

  Yeah, as you guys said it just doesn't seem right in theory.  Whether the CUDA miner or something else needs to be adjusted or re-written for the Kepler architecture is just my guess, it's too bad to not see it mine well.

  FWIW, Folding @ Home (Stanford) has also said they have to recompile their program to work with the new architecture.  Thus while normally Folding is a strong suit for Nvidia, it also is "broken" on the Kepler cards for the moment.

  Might also just need a newer driver.  Hopefully if that's the case, Nvidia won't take 3 months to release one.  Normally it seems like they get new cards' drivers out very fast (updated ones I mean, rather than the stock).  Here's hoping!

Folding @ Home is broken because nVidia broke it.  The cards have way less DP/SP floating point performance than a 560 Ti.  It's part of nVidia's new tactic of making their lower end architecture useful only for gaming.

And despite that there are ppl who love nvidia and hate amd. Nonsense.

Seriously, who want to buy a nvidia? Not me.

[Schleicher]

I have tried to recompile the Ufa-miner and the rpcminer-cuda, but for various reasons it didn't work.
Now I have written a very simple miner using the latest CUDA toolkit, just to see what the speed is like.
Since I have written the kernel from scratch, and the program is not doing longpolling, there's some room for improvement.

If somebody with a GTX680 would like to try it you can download it there:
http://www.sonstiges.org/bitcoin/ICU-Miner.zip
Usage:

Code:

ICU-Miner.exe URL username password devicenumber gridsize blocksize

(devicenumber, gridsize and blocksize are optional)
For example:

Code:

ICU-Miner.exe http://mining.eligius.st:8337/ 1BtVLjUkAzF9wZGHfKzzsPivgNAn4DTp1Q joshua

Here's the ugly source code:
http://www.sonstiges.org/bitcoin/ICU-Miner-source.zip

[bulanula]

I have tried to recompile the Ufa-miner and the rpcminer-cuda, but for various reasons it didn't work.
Now I have written a very simple miner using the latest CUDA toolkit, just to see what the speed is like.
Since I have written the kernel from scratch, and the program is not doing longpolling, there's some room for improvement.

If somebody with a GTX680 would like to try it you can download it there:
http://www.sonstiges.org/bitcoin/ICU-Miner.zip
Usage:

Code:

ICU-Miner.exe URL username password devicenumber gridsize blocksize

(devicenumber, gridsize and blocksize are optional)
For example:

Code:

ICU-Miner.exe http://mining.eligius.st:8337/ 1BtVLjUkAzF9wZGHfKzzsPivgNAn4DTp1Q joshua

Here's the ugly source code:
http://www.sonstiges.org/bitcoin/ICU-Miner-source.zip

Too bad I don't have a GTX 680.

Somebody needs to try this ASAP !

[scifimike12]

I just tried it now but it doesn't seem to work very well.  Desktop is completely unresponsive and the GPU usage doesn't stay pegged at 99%.

[niooron]

Nvidia just cut all integer and double precision support to fit 1536 crappy shaders. We have to wait for the high end Kepler.

[bulanula]

Nvidia just cut all integer and double precision support to fit 1536 crappy shaders. We have to wait for the high end Kepler.

Care for a link ?

As much as I love AMD vs Nvidia mining competition it really does look like Kepler totally SUCKS for mining

Or maybe the GTX 680 is the card that is for gaming only and designed to crush 7970 prices ?

Thanks !

[Miner99er]

Or maybe the GTX 680 is the card that is for gaming only and designed to crush 7970 prices ?

Thanks !

YES... please! Then again, there's the 7990 down the pike.

Then you'd have to decide between a $499 7970 (if the price drops) or $849 7990 for each slot.

Please let the 7990 hit 1.3Ghash/s.

[jedi95]

GTX 680 mining does work but the performance is very disappointing at the moment. I think there may be some gains from drivers in the future though, since I'm only showing ~70% power usage. However, I highly doubt the GTX 680 will ever be competitive as a mining card.

Showing 123.40 Mhash/sec in Phoenix 2.0.0 with the following settings:

Code:

[cl:1:0]
    kernel = opencl
    name = GTX 680
    disabled = False
    worksize = 256
    vectors = False
    vectors4 = False
    bfi_int = False
    goffset = False
    fastloop = True
    aggression = 2

Vectors seem to reduce performance. Enabling goffset will cause the miner to error out and exit after about a minute. GPU clock was a constant 1241MHz for the test. (using +144 offset) Maximum load temperature was 67 C.

Code:

[04/06/2012 14:26:27] Welcome to Phoenix v2.0.0
[14:26:27] Connected to server
[14:26:27] Server gave new work; passing to WorkQueue
[14:26:27] New block (WorkQueue)
[14:26:27] Server gave new work; passing to WorkQueue
[14:26:31] [GTX 680] Result 00000000963d2b3a... ACCEPTED
[14:27:01] [GTX 680] Result 00000000a91cf2e1... ACCEPTED
[14:27:02] Server gave new work; passing to WorkQueue
[14:27:04] [GTX 680] Result 00000000dca6829f... ACCEPTED
[14:27:12] [GTX 680] Result 00000000747b6cd5... ACCEPTED
[14:27:15] [GTX 680] Result 000000005d990449... ACCEPTED
[14:27:27] Server gave new work; passing to WorkQueue
[14:27:32] [GTX 680] Result 0000000021cd0601... ACCEPTED
[14:28:02] Server gave new work; passing to WorkQueue
[14:28:27] Server gave new work; passing to WorkQueue
[14:28:28] [GTX 680] Result 00000000db036548... ACCEPTED
[14:28:51] Server gave new work; passing to WorkQueue
[14:28:51] New block (WorkQueue)
[14:28:52] Server gave new work; passing to WorkQueue
[14:29:03] [GTX 680] Result 0000000057bdfa90... ACCEPTED
[14:29:26] Server gave new work; passing to WorkQueue
[14:29:52] Server gave new work; passing to WorkQueue
[14:30:04] [GTX 680] Result 0000000093be9bbe... ACCEPTED
[123.40 Mhash/s] [9 Accepted] [0 Rejected] [MMP]

[bulanula]

Watching as I have an itch for a gtx 680 for gaming stuff. Would also much prefer mining to go with the package. Right now I would choose the 7970 completely based on mining/gaming performance.

I think we are going to be watching for a long time because it seems nobody is interested in getting Nvidia to be competitive in mining against AMD 

[n4l3hp]

Watching as I have an itch for a gtx 680 for gaming stuff. Would also much prefer mining to go with the package. Right now I would choose the 7970 completely based on mining/gaming performance.

I think we are going to be watching for a long time because it seems nobody is interested in getting Nvidia to be competitive in mining against AMD 

It's not that they're not interested. They just know that they will only be wasting their time and think "Why bother?".   
 

[waterboyserver]

Apparently nVidia is releasing a Kepler version of Tesla on May 14.  What seems very interesting is that it is a 7 billion transistor chip, the GTX 680 is 3.5 billion transistors.

http://www.brightsideofnews.com/news/2012/4/20/nvidia-to-launch-a-7-billion-transistor-kepler-gpgpu-tesla-boards-on-may-14.aspx

[MrTeal]

Apparently nVidia is releasing a Kepler version of Tesla on May 14.  What seems very interesting is that it is a 7 billion transistor chip, the GTX 680 is 3.5 billion transistors.

http://www.brightsideofnews.com/news/2012/4/20/nvidia-to-launch-a-7-billion-transistor-kepler-gpgpu-tesla-boards-on-may-14.aspx

Interesting. With the number it would be tempting to think 2xGK104, but given how crippled GK104 is in FP64 performance I can't see that happening in a Tesla product. If this actually is BigK, it's way ahead of when most people expected it to ship.

[AzN1337c0d3r]

Apparently nVidia is releasing a Kepler version of Tesla on May 14.  What seems very interesting is that it is a 7 billion transistor chip, the GTX 680 is 3.5 billion transistors.

http://www.brightsideofnews.com/news/2012/4/20/nvidia-to-launch-a-7-billion-transistor-kepler-gpgpu-tesla-boards-on-may-14.aspx

Interesting. With the number it would be tempting to think 2xGK104, but given how crippled GK104 is in FP64 performance I can't see that happening in a Tesla product. If this actually is BigK, it's way ahead of when most people expected it to ship.

Actually NVIDIA is most likely just crippling in the drivers like they did for the GTX480 vs Quadro6000/Tesla C2050 by hobbling the drivers. Anyways I dont think GK104 has ECC support, so it is likely this new card will be GK110.

[MrTeal]

Apparently nVidia is releasing a Kepler version of Tesla on May 14.  What seems very interesting is that it is a 7 billion transistor chip, the GTX 680 is 3.5 billion transistors.

http://www.brightsideofnews.com/news/2012/4/20/nvidia-to-launch-a-7-billion-transistor-kepler-gpgpu-tesla-boards-on-may-14.aspx

Interesting. With the number it would be tempting to think 2xGK104, but given how crippled GK104 is in FP64 performance I can't see that happening in a Tesla product. If this actually is BigK, it's way ahead of when most people expected it to ship.

Actually NVIDIA is most likely just crippling in the drivers like they did for the GTX480 vs Quadro6000/Tesla C2050 by hobbling the drivers. Anyways I dont think GK104 has ECC support, so it is likely this new card will be GK110.

You're basing this on what? Every review that talks about it is pretty emphatic that FP64 performance just isn't there, which is one of the reasons NVIDIA was able to pack so much performance in such a little die.

From Anandtech

The other change coming from GF114 is the mysterious block #15, the CUDA FP64 block. In order to conserve die space while still offering FP64 capabilities on GF114, NVIDIA only made one of the three CUDA core blocks FP64 capable. In turn that block of CUDA cores could execute FP64 instructions at a rate of ¼ FP32 performance, which gave the SM a total FP64 throughput rate of 1/12th FP32. In GK104 none of the regular CUDA core blocks are FP64 capable; in its place we have what we’re calling the CUDA FP64 block.

The CUDA FP64 block contains 8 special CUDA cores that are not part of the general CUDA core count and are not in any of NVIDIA’s diagrams. These CUDA cores can only do and are only used for FP64 math. What's more, the CUDA FP64 block has a very special execution rate: 1/1 FP32. With only 8 CUDA cores in this block it takes NVIDIA 4 cycles to execute a whole warp, but each quarter of the warp is done at full speed as opposed to ½, ¼, or any other fractional speed that previous architectures have operated at. Altogether GK104’s FP64 performance is very low at only 1/24 FP32 (1/6 * ¼), but the mere existence of the CUDA FP64 block is quite interesting because it’s the very first time we’ve seen 1/1 FP32 execution speed. Big Kepler may not end up resembling GK104, but if it does then it may be an extremely potent FP64 processor if it’s built out of CUDA FP64 blocks.

[AzN1337c0d3r]

Mining doesnt use FP -_- Also not sure why you quoted the part on GF114. The GTX480 and Quadro/Tesla are GF100, not GF114.

Edit: Anyways if it is right that 1 of the 3 blocks cannot do anything but FP mathematics, that means that there are still 1024 cores which can. Coupled with the halved speed, it should still match the GTX580. I wonder why the performance is so poor then.

I dont buy the new architecture = no tuned miner theory. It should be relatively easy to write a compiler for a MIMD architecture like the GTX680 and get 99% utilization with data parallel tasks, like hashing.