Your problem is BOINC does not see the video card so does not know to accept work for the GPU.

The user boinc is not included in the video group and needs to be added to it.

http://boinc.berkeley.edu/dev/forum_thread.php?id=3564

That should have hopefully relevant info for the problem.

---

Thanks for the help.

The link had the information that I needed. BOINC now sees the GPUs.

Thanks again.

Steve

Could someone clarify things for me?

I have 2 Nvidia GPUs. GPU0 is a Fermi card, while GPU1 is a single-precision card (GTS8400) running under 64-bit Ubuntu on an AMD quad core.

Now that I've got everything running with the newly installed Fermi added, I see on the task screen that when MW downloads WU's, it will momentarily show the work unit and a notation that the it is using 1 cpu core and GPU0 or 1 core and GPU1. Then the lines disappear. I am downloading and processing WU's of some type, but I'm curious as to what kind.

A check of the Messages screen only shows a line reading "Requesting new task for GPU." The WU download lines say that I' using MW version 24, if that helps.

I am getting Arecibo Binary Pulsar WUs that stipulate they are using the Fermi.

Is Einstein monopolizing the Fermi such that MW decides to send me WUs that don't require the Fermi?

If so, is there anything that I can do to even things out?

Having said all that, it's great to have this crunching along.

Thanks for any help that you can provide.

Steve

Is there a wiki page or link that would have information on how to allocate @home tasks between multiple machines?

I've got my machine working from spares and it's a pretty decent machine. Now, I've got the bug to build a serious @home machine ("more power", aargh!). It will be a multi-core running under Ubuntu, with at least one Fermi card.

The projects that I'm interested in are:
Einstein (single and double precision wu's)
MW (ditto)
Cosmology (single)
Orbit (I think just single)
Seti (just single on Linux, has both on Windows)

My questions I'm sure have been addressed before if someone can just point me in the right direction. I haven't found it in the FAQs but I may have missed it.

Questions like, "should I concentrate the Fermi cards and double-precision projects on one machine and the single-precision tasks on the other?" Or does it matter? Those sorts of questions.

Thanks for any help that you can provide.

Regards,
Steve

You listed some projects you are interested in, great, however overall is the motivation to compete re credits (as such) or is there a driving motive on a particular genric type of project? Reason for asking is if this beast is being designed solely as a Cruncher, the over-arching motives need understanding in order to help you design it in the best possible way.

Questions like, "should I concentrate the Fermi cards and double-precision projects on one machine and the single-precision tasks on the other?" Or does it matter? Those sorts of questions

The above is why it matters, as by in large Projects have different abilities, requirements, needs, motives, charactor yaddie yadda - each one of those can trip you up, especially double/single precision. Card type is critical, and unless you are a hard core blue team member, you should at least consider the red team (ATI) if your target Projects work better on Red Team cards.

So the start point is overall motivations, followed by general preferences, and list any fixed aspects (eg must be Linux - by the looks of it). Once we all know that, then we can help design the beast with you. Your list might be (hypothetically):

- crunching to compete re fun credit side of life
- Prefer in preference order: 1. Scientific/Cosmos, 2. Crunch for max credits 3. Save the Planet projects
- NVidia or nothing at the moment, but will consider ATI if it helps my priorities
- Must be Linux Projects
- I'm semi-tech, butNeed good forum support to help with problems
- A good active Project Community is important to me

From that kind of list, Projects become clear, and from that the needed hardware. Isuggest you start a new thread for this to keep this one clear for straight GPU queeries. Lots of very knowledgeable helpful folk re all this at MW, and approaching it like this will, I suspect, attract the assistence you seek.

Regards
Zy

Zydor,

Thanks for the feedback and suggestions.

At the moment, I'm going to have to put the idea of another machine aside since I just found out that I am not returning good double-precision WUs. All of the units are getting rejected for errors. When I checked the website I found the following:

<core_client_version>6.10.58</core_client_version>
<![CDATA[
<message>
process exited with code 1 (0x1, -255)
</message>
<stderr_txt>
Device index specified on the command line was 0
Looking for a Double Precision capable NVIDIA GPU
The device GeForce GTX 460 from the command line cannot be used because a device supporting compute capability 1.3 (Double Precision) is required
Found 1 CUDA cards
Found a GeForce GTX 460
Device cannot be used, it does not have compute capability 1.3 support
No compute capability 1.3 cards have been found, exiting...

</stderr_txt>

The GTX 460 is 2.1 compute capability. It's got to be backward-compatible! I wonder if the app has "1.3" hardwired into the code and that's why it's not working?

I previously had an additional 8400GS card in which I physically pulled so it's just the Fermi now.


I'm no programmer but I'm beginning to wonder if it's a driver issue. I thought the one (the "restricted" driver that Ubuntu installed) was the latest but now I'm wondering. I see where Nvidia has a newer driver so I may try that one. Also, I noticed that when Boinc starts up and correctly sees and describes the Fermi card, it also says "driver unknown."

I've just about hit the wall on this one.

Regards,
Steve

I'm no programmer but I'm beginning to wonder if it's a driver issue. I thought the one (the "restricted" driver that Ubuntu installed) was the latest but now I'm wondering. I see where Nvidia has a newer driver so I may try that one. Also, I noticed that when Boinc starts up and correctly sees and describes the Fermi card, it also says "driver unknown."

The old CUDA application doesn't work, but you can try the new OpenCL one which should work.

Matt,

Thanks, I definitely will.

As an aside, a little while ago, I found a message thread over at Seti with someone having the exact same problem with the exact same error message about his Fermi card not being 1.3-capable.

Regards,
Steve

"As long as we've got computers, who needs enemies!"

I got this when I tried to run the NVIDIA GPU Wu's on my M8700 GT ???

stderr out

<core_client_version>6.10.58</core_client_version>
<![CDATA[
<message>
Incorrect function. (0x1) - exit code 1 (0x1)
</message>
<stderr_txt>
<search_application> milkywayathome separation 0.48 Windows x86 double OpenCL </search_application>
Found 1 platforms
Platform 0 information:
Platform name: NVIDIA CUDA
Platform version: OpenCL 1.0 CUDA 3.2.1
Platform vendor:
Platform profile:
Platform extensions: cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_d3d9_sharing cl_nv_d3d10_sharing cl_khr_d3d10_sharing cl_nv_d3d11_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll
Using device 0 on platform 0
Found 1 CL devices
Device GeForce 8700M GT (NVIDIA Corporation:0x10de)
Type: CL_DEVICE_TYPE_GPU
Driver version: 260.99
Version: OpenCL 1.0 CUDA
Compute capability: 1.1
Little endian: CL_TRUE
Error correction: CL_FALSE
Image support: CL_TRUE
Address bits: 32
Max compute units: 4
Clock frequency: 1250 Mhz
Global mem size: 519634944
Max mem alloc: 134217728
Global mem cache: 0
Cacheline size: 0
Local mem type: CL_LOCAL
Local mem size: 16384
Max const args: 9
Max const buf size: 65536
Max parameter size: 4352
Max work group size: 512
Max work item dim: 3
Max work item sizes: { 512, 512, 64 }
Mem base addr align: 2048
Min type align size: 128
Timer resolution: 1000 ns
Double extension: MW_NONE_DOUBLE
Extensions: cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_d3d9_sharing cl_nv_d3d10_sharing cl_khr_d3d10_sharing cl_nv_d3d11_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics

Compiler flags:
-cl-mad-enable -cl-no-signed-zeros -cl-strict-aliasing -cl-finite-math-only -DUSE_CL_MATH_TYPES=0 -DUSE_MAD=0 -DUSE_FMA=0 -cl-nv-verbose -DDOUBLEPREC=1 -DMILKYWAY_MATH_COMPILATION -DNSTREAM=3 -DFAST_H_PROB=1 -DAUX_BG_PROFILE=0 -DUSE_IMAGES=1 -DI_DONT_KNOW_WHY_THIS_DOESNT_WORK_HERE=0

Build status: CL_BUILD_ERROR
Build log:
ptxas application ptx input, line 58; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 74; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 75; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 177; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 178; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 179; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 180; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 181; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 182; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 183; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 184; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 185; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 198; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 199; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 200; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 201; error : Instruction 'mov' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 211; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 212; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 213; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 214; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 215; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 216; error : Instruction 'ld' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 219; error : Instruction 'mov' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 220; error : Instruction 'mov' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 221; error : Instruction 'mov' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 230; error : Instruction 'mul' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 231; error : Instruction 'mul' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 232; error : Instruction 'mul' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 233; error : Instruction 'mul' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 234; error : Instruction 'add' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 235; error : Instruction 'mul' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 236; error : Instruction 'mul' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 237; error : Instruction 'mul' requires SM 1.3 or higher, or map_f64_to_f32 directive
ptxas application ptx input, line 238; error : Instruction 'add' requires SM 1.3 or higher,
clBuildProgram: Build failure: CL_INVALID_BINARY
Error creating kernel 'mu_sum_kernel': CL_INVALID_PROGRAM_EXECUTABLE
Error building program from source: CL_INVALID_PROGRAM_EXECUTABLE
Error creating program from source: CL_INVALID_PROGRAM_EXECUTABLE
Failed to setup up CL
15:00:59 (3704): called boinc_finish

</stderr_txt>

---

STE\/E

Matt,

As far as I can tell, I properly installed things to Ubuntu and I re-set the project, however I'm still downloading tasks that say cuda23.

The one new task that I completed was still bad with the same message about needing a double-precision card, even though it's a Fermi.

Should the work units still be marked as cuda 23or should I have un-installed the boinc client 6 before extracting the tar?

Thanks for any help that you can provide.

Steve

Matt,

As far as I can tell, I properly installed things to Ubuntu and I re-set the project, however I'm still downloading tasks that say cuda23.

The one new task that I completed was still bad with the same message about needing a double-precision card, even though it's a Fermi.

Should the work units still be marked as cuda 23or should I have un-installed the boinc client 6 before extracting the tar?

Thanks for any help that you can provide.

Steve

RIght now it's not a stock application, and isn't automatically sent out. I'm not sure how system responsiveness is on lower end GPUs, so I'm waiting to hear from people using those before putting it there. If you want to try it now, you have to manually download and install from the links I posted on the news post.

I got this when I tried to run the NVIDIA GPU Wu's on my M8700 GT ???

Those errors are because that GPU doesn't support doubles. I was apparently checking that after compiling the kernel, so in the release the error should be more explicit about that.

Okay Thanks, I didn't really think it would work anyway but tried them for the Heck of it, guess I'll have to get some cards that work ... lol

---

STE\/E

One question, maybe someone got it before;
Is it possible to run a 5850 combined with a 5870 in one Box crunching?
I got a 5850 and can borrow a 5870 for some weeks now. But only have one Box for multible Cards, MSI 890FXA-GD70.

---

I have 1-4870 and 1-4890 in the same box. They are not crossfired and work fine.
I see no reason yours won't work.

---

Ah ok, thx. I guess this setup will not run as Crossfire.
I just thought about the Boinc Client, if it support the Cards together in one Box.
Years ago i got a x1900xtx and a x1950xtx still in Crossfire Setup, works very well. But the Chips where the same.
Now the Chips are to dissimilar.

---

Since they are the same generation you could conceivably crossfire the cards, but that would not offer any speedup.

---

Since they are the same generation you could conceivably crossfire the cards, but that would not offer any speedup.

Yes. I think it will make both cards default to the slowest GPU in Crossfire.

---

Can an HD580, as the prime GPU, be crossfired with an HD4850?

---

Go away, I was asleep

Nope.

---