In this case the 1060-3GB is ~10% faster than the GTX970 and the CPU usage is also around 10% greater. As most tasks at GPUGrid tend to be longer, 10% might more accurately reflect the differences between the cards than the short tasks; which spend as much time loading but less time running. So ~10% faster for ~45% less energy ~60% better in terms of performance/Watt

I think on WDDM system's the 3GB GTX 1060 ~20% faster than GTX 970 - at least this what I've observed on PCIe 3.0 x4 GTX 970 at 1.5GHz and 2.1GHz GTX 1060.

The 1152CUDA is a great cruncher for here and GTX 1070 even more so from a purely watt/performance point of view.
As you mentioned in another thread: the GTX 1060 (3GB) is hands down cost/performance king.
IMO: both the GTX 1060 and GTX 1070 are going to be the most efficient GPUGRID GPU until Pascal refresh or Volta - ACEMD scaling a major factor (maybe someday the app will make GTX 1080 work at 95% on WDDM).
My GTX 1070 hasn't risen past 110W (80% GPU usage) while staying mostly under 100W.
My (2) GTX 970 would hit 170W on some GERALD's with 86% GPU usage.

When I start to crunch on the GPU the system uses ~125W, so the GPU is using ~75W.
Of note is that my 1060 only has one 6-pin power connector (which only delivers up to ~75W)! So perhaps I'm being power capped? It's a small PCIe-2x16 motherboard, and although there's a 12-pin ATX power connector I wouldn't be surprised if the GPU isn't drawing power from the PCIE slot.

A true MiniFit.JR connectors 6 pin (not the one that missing a 12V pin like 4 pin molex adapter to 6-pin type.) can provide more than 75W. Check PSU wire gauge to determine it's amperage limit and you'll find out what the (3) 12V PCIe 6 pin wires are capable of.

Tomshardware website has detailed power consumption tests showing how each card draws it's power. Some vBIOS software from AIB (Zotac / MSI / Gigabyte / some EVGA) draw mostly all of it's power from PSU - <25W from PCIe slot that controls up to 3 phases though mostly 1 or 2 on GPU board. If you have a laser thermometer or do simple old fashion skin method - check the PCIe capacitors. If the PCIe is providing most of the power (66W) they'll be hot - if barely warm then 6-pin is main provider. My 4+1 phase Gigabyte windforce OC GTX 1060 (3GB) get's majority of power from PSU with a 6-pin at 116% power limit (140W) = Primegrid Genefer program and si software scientist benchmark max's out power.

Quoted from xdev.com Pascal OC guide (link in the x80 Pascal thread)

13A per contact (16AWG wire in small connector) to 8.5A/contact (18AWG wire). This means that using common 18AWG cable, 6-pin connector specified for 17A of current (3 contacts for +12V power, 2 contacts for GND return, one contact for detect). 8-pin have 25.5A current specification (3 contacts for +12V power, 3 contacts for GND return and 2 contacts for detection). 6-pin is 204W at +12.0V level or 306W for 8-pin accordingly.

After completing a 50nm long SCOERR_CASP22SnoS task it's looking more like the GTX1060-3GB can do a Long task in 73% of the time a 970 can (though I'm not certain my settings were identical back on the 30th Oct when using the 970; might have been running a CPU task then). If setup was identical that would make the 1060-3GB 36% faster at long runs, but others would have to demonstrate that too before I'd accept it. I've got a Long PABLO SH2 now and should be able to compare that tomorrow to 3 similar task I ran a few days ago when I definitely had the same setup. Still the same +10% CPU usage.

e9s8_e8s1p0f0-SDOERR_CASP22SnoS_crystal_contacts_50ns_ntl9_0-0-1-RND0969_0 : 14,398.54 7,695.54 63,750.00 v9.14 (cuda80)

e16s9_e9s9p0f217-SDOERR_CASP10_crystal_ss_50ns_ntl9_0-0-1-RND0343_0 : 19,631.24 6,984.46 63,750.00 v8.48 (cuda65)

The Long Long PABLO SH2 task is presently realizing around 93% GPU Utilization with X Server Settings open and ~89% minimized, varying form 88% to 96% when the X Server Settings are open. PCIE bandwidth is ~28% and CPU usage is ~16%.
The GPU heated up to 66C, so I increased the fan speed to ~2270RPM (70%) which brought the temp back down to 62C. Noticed that the GPU clock is 1879MHz, slightly lower than with the previous tasks. System power usage is also up to ~160W so the GPU is drawing ~110W (35W) more power running the PABLO's than the SCOERR's.
So greater performance from the 1060 3GB while running longer tasks and greater utilization with some Long task types.

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The PABLO_SH2TRIPER took 3% longer on the 1060-3GB than it did on a 970, so there is a lot of performance variation. CPU usage was also 11% less when using the 1060:

e16s27_e15s14p0f22-PABLO_SH2TRIPEP_L_TRI_2-0-1-RND3725_0 : 22,123.02 7,779.86 145,800.00 v9.14 (cuda80)

e14s15_e12s4p0f72-PABLO_SH2TRIPEP_Q_TRI_1-0-1-RND5699_1 : 21,321.75 8,659.11 145,800.00 v8.48 (cuda65)

e21s26_e15s3p0f391-PABLO_SH2TRIPEP_F_TRI_2-0-1-RND2465_0 : 21,323.73 8,596.28 145,800.00 v8.48 (cuda65)

Not complaining about these PABLO tasks though; if an 1152 core GPU can get 569K/day it's not bad :)
By comparison the 'shorter' Long SDOERR_CASP tasks only collect about 382K/day :|

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e9s8_e8s1p0f0-SDOERR_CASP22SnoS_crystal_contacts_50ns_ntl9_0-0-1-RND0969_0 : 14,398.54 7,695.54 63,750.00 v9.14 (cuda80)

e16s9_e9s9p0f217-SDOERR_CASP10_crystal_ss_50ns_ntl9_0-0-1-RND0343_0 : 19,631.24 6,984.46 63,750.00 v8.48 (cuda65)

-- GTX 1060 3GB @ 2.1GHz / 67% GPU usage / 51% BUS / 74W

e10s5_e8s4p0f261-SDOERR_CASP22SnoS_crystal_ss_50ns_ntl9_1-0-1-RND6842_0
15,021.71 6,281.00 63,750.00 (cuda80)

-- GTX 1070 @ 2.1GHz / 59% GPU usage / 37% BUS / 78W

e5s9_e2s1p0f88-SDOERR_CASP22SnoS_crystal_ss_50ns_ntl9_1-0-1-RND2882_0
12,249.42 6,445.78 63,750.00 (cuda80)

You're single GTX 1060 system is 4.21% faster than my GTX 1060 3GB.
The higher PCIe bandwidth usage on my system probably due to having 4 GPU's.

GTX 1070 PCIe3 x8 19% faster than my GTX 1060 PCIe3 x4.

The PABLO_SH2TRIPER took 3% longer on the 1060-3GB than it did on a 970, so there is a lot of performance variation. CPU usage was also 11% less when using the 1060:

e16s27_e15s14p0f22-PABLO_SH2TRIPEP_L_TRI_2-0-1-RND3725_0 : 22,123.02 7,779.86 145,800.00 v9.14 (cuda80)

e14s15_e12s4p0f72-PABLO_SH2TRIPEP_Q_TRI_1-0-1-RND5699_1 : 21,321.75 8,659.11 145,800.00 v8.48 (cuda65)

e21s26_e15s3p0f391-PABLO_SH2TRIPEP_F_TRI_2-0-1-RND2465_0 : 21,323.73 8,596.28 145,800.00 v8.48 (cuda65)

-- GTX 1070 @ 2.1GHz / 69% GPU / 51% BUS / 96W:

e13s5_e5s7p0f442-PABLO_SH2TRIPEP_W_TRI_2-0-1-RND9211_0 11929451
16,843.90 6,162.14 145,800.00 (cuda80)

-- GTX 1060 (3GB) @ 2.1GHz / 74% GPU / 60% BUS / 85W:

e15s20_e14s21p0f117-PABLO_SH2TRIPEP_S_TRI_1-0-1-RND6936_0
23,441.73 6,269.66 145,800.00 Long runs (cuda80)

GTX 1070 PABLO_SH2TRIPEP 28.1% faster than my GTX 1060.
Surprisingly I haven't received any unstable simulation messages on overclocked at 2.1GHz completed WU .

Thanks for posting your performances.

Quick look at the differences between our systems:

You've a slower operating system (WDDM overhead, 11%+); Windows vs Linux
You've a faster CPU, i5-4440S @2.8GHz vs AMD A6-3500 @2.1GHz
You've a faster on die PCIE controller
You've a PCIE3.0 bus vs my PCIE2.0 bus
Your heavier use of the PICE3 bus likely restricts your performances more than my PCIE2.0 x16 is being restrictive
Your 2.1GHz GPU clock is ~10% higher than my 1.9GHz.

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GTX 1060 6GB:

I had 88-92% utlization yesterday, now it's only 65%. I changed nothing in the system.

- Windows 10
- Gigabyte B150 mobo
- i5-6600, one core dedicated to GPU running at 3.6 GHz
- PCIE3 x16

Power consumption is 72W average at 65%.

I crunch WCG on this rig as well. When I enable WCG on the 3 other CPU cores, the GPU usage goes up to 75%. I have no idea why.

I had 88-92% utlization yesterday, now it's only 65%. I changed nothing in the system.

It depends (beside the system) on the workunit. Yesterday you had an ADRIA_1JWP_dist, which uses the CPU less than your recent SDOERR_CASP22S20M_crystal_ss_contacts_50ns_ntl9 workunit.

Power consumption is 72W average at 65%.

I crunch WCG on this rig as well. When I enable WCG on the 3 other CPU cores, the GPU usage goes up to 75%. I have no idea why.

It's because you didn't set the SWAN_SYNC environmental value, and without it the GPUGrid app doesn't use a CPU thread that much to make your CPU to boost.

Thanks, SWAN_SYNC seems to help, now utilization is at 72% even if only GPUGRID is running.

Moving to linux/win XP isn't possible, since this is my daily use PC.

Would getting a faster CPU help? (i5 6600k/i7 6700k)

Would getting a faster CPU help? (i5 6600k/i7 6700k)

No, it won't.

If you want to maximize GPU usage on an operating system wich has WDDM (Windows 7, 8, 8.1, 10) you should:
- crunch only 1 CPU task (or do not crunch CPU tasks at all)
- not crunch on the iGPU
- use SWAN_SYNC environmental value to make the GPUGrid app use a full CPU thread
- use the app_config.xml to run two WU on a single GPU (it will double the runtimes, so do it only if your runtimes are well below 12h)
- put your GPU to a PCIe3.0x16 slot, which really runs at x16 (you can check it with the GPU-Z tool)

And now the "how-to" part: (TLDR)

To crunch only 1 CPU task you should reduce the percentage of the CPUs available for BOINC, or the number of CPUs in the cc_config.xml.
First you have to know how many CPU threads your PC has.
To find it you should use the CPU-Z tool, or start task manager (right click on the empty area of taskbar and choose "Task Manager"). Then on the performance tab you should see as many graphs on the "CPU usage history" panel as many "logical processors" your PC has (Windows 10 reports it numerically also). If you see only 1 graph, then you should switch view.
Then you should divide 100% by the number of "logical processors" aka "threads" your PC has, and multiply it by the number of GPU tasks you have plus 1 and round it up to the nearest integer, then type the result to the BOINC manager -> Options -> Computing preferences -> Use at most [...] % of the CPUs. The other field has to stay at 100% (use at most 100% of the CPU time).
For example:

 8 CPU cores + 2 GPU tasks: 100/8*(1+2) =37.5   [38%]
12 CPU cores + 3 GPU tasks: 100/12*(1+3)=33.333 [34%]
 4 CPU cores + 2 GPU tasks: 100/4*(1+2) =75     [75%]

Theoretically this calculation can result in more than 100%, but in this case you should type 100% (2 CPU cores + 2 GPUs: 100/2*(1+2)=150), and do not crunch CPU projects at all.

Another method to set the number of CPUs in the cc_config.xml file:
The actual number should be set to the number of GPU tasks + 1.
Do not set this number higher than the number of your CPU's threads.
For example for 2 GPU tasks you should replace the 2 by 3 in the example below:
Copy the following to the clipboard:

notepad c:\ProgramData\BOINC\cc_config.xml

Press Windows key + R, then paste and press enter.
If you see an empty file, copy and paste the following:

<cc_config>
  <options>
    <ncpus>2</ncpus>
  </options>
</cc_config>

If your cc_config.xml already has an <options> section and there is no <ncpus> tag in it, you should insert the line

    <ncpus>2</ncpus>

right after the <options> tag.
Click file -> save and click [save].
If your BOINC manager is running, click on Options -> read config files.

How not to crunch on the iGPU (the Intel GPU integrated into recent Intel CPUs):
1, Do not attach to projects with Intel (OpenCL) clients, or disable this application in the project's computing preferences (it is practical to use a different venue for these hosts)
2, Disable the iGPU in the cc_config.xml file:
copy the following to the clipboard:

notepad c:\ProgramData\BOINC\cc_config.xml

Press Windows key + R, then paste and press enter.
If you see an empty file, copy and paste the following text:

<cc_config>
  <options>
    <ignore_intel_dev>0</ignore_intel_dev>
  </options>
</cc_config>

If your cc_config.xml already has an <options> section and there is no <ignore_intel_dev> tag in it, you should insert the line

    <ignore_intel_dev>0</ignore_intel_dev>

right after the <options> tag.
Click file -> save and click [save].
If your BOINC manager is running, you can click Options -> read config files.

To apply the SWAN_SYNC environmental value:
Click Start, copy & paste systempropertiesadvanced and press enter.
Click on [Environmental Variables]
Look for the lower section called "System Variables", click on the [New] button below the list of System Variables.
Type SWAN_SYNC in the name field
Type 1 in the Value field
Click [OK] 3 times.
Exit BOINC manager with stopping scientific applications.
Start BOINC manager.

To run two GPUGrid tasks on a single GPU:
The app_config.xml file should be placed to the project's home directory (by default it's at c:\ProgramData\BOINC\projects\www.gpugrid.net\)
Copy the following to the clipboard:

notepad c:\ProgramData\BOINC\projects\www.gpugrid.net\app_config.xml

Press Windows key + R, then paste and press enter. Copy & paste the following text:

<app_config>
 <app>
  <name>acemdlong</name>
  <gpu_versions>
   <gpu_usage>0.5</gpu_usage>
   <cpu_usage>1.0</cpu_usage>
  </gpu_versions>
 </app>
<app>
  <name>acemdshort</name>
  <gpu_versions>
   <gpu_usage>0.5</gpu_usage>
   <cpu_usage>1.0</cpu_usage>
  </gpu_versions>
 </app>
</app_config>

Click file -> save and click [save].
Exit BOINC manager with stopping scientific applications.
Start BOINC manager.
(If your BOINC manager is running, you can click Options -> read config files.)

Thanks, I'll try these solutions!

Thanks Retvari Zoltan, now my card works with utilisation 96-98% on windows 10 (driver 375.70) with 2 task.

I've successfully installed Ubuntu 16.04 LTS on one of my hosts.
Could someone please enlighten me how to make the SWAN_SYNC=1 setting noticed by the app? I'd appreciate it.
I've put it in /etc/environment, and when I try printenv it shows the SWAN_SYNC=1, but the app obviously does not take a full CPU thread.
The boinc and the GPUGrid app runs as user 'boinc' but I didn't find anything for this user in /home.
Is this environmental value handled by the new (9.14) Linux app?

Is this environmental value handled by the new (9.14) Linux app?

To answer my own question:
I think the new (9.14) Linux app doesn't support SWAN_SYNC=1, as I've started BOINC from the terminal by

sudo /usr/bin/boinc --dir /var/lib/boinc-client

and the CPU usage remained 7-8% (it should be 25%). I've checked previously that the SWAN_SYNC=1 is listed by

sudo printenv

This feature should be added.

1fdq-SDOERR_OPMcharmm6-0-1-RND3215_1 longest WU I've encountered to date on GTX 1070.
Estimated completion 51,300/sec (14.28hr) at 54% GPU usage / 33% MCU / 24% BUS (PCIe 3.0 x8) / 45% GPU power (83W)

I've noticed if only my GTX 1070 is running GPU usage 3 to 6% higher on all WU compared to 2/3/4 GPU Pascal or Maxwell compute.

1fdq-SDOERR_OPMcharmm6-0-1-RND3215_1 longest WU I've encountered to date on GTX 1070.
Estimated completion 51,300/sec (14.28hr) at 54% GPU usage / 33% MCU / 24% BUS (PCIe 3.0 x8) / 45% GPU power (83W)

I've noticed if only my GTX 1070 is running GPU usage 3 to 6% higher on all WU compared to 2/3/4 GPU Pascal or Maxwell compute.

GPU Clocks?

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1fdq-SDOERR_OPMcharmm6-0-1-RND3215_1 longest WU I've encountered to date on GTX 1070.
Estimated completion 51,300/sec (14.28hr) at 54% GPU usage / 33% MCU / 24% BUS (PCIe 3.0 x8) / 45% GPU power (83W)

I've noticed if only my GTX 1070 is running GPU usage 3 to 6% higher on all WU compared to 2/3/4 GPU Pascal or Maxwell compute.

GPU Clocks?

2.1GHz core and 3.8GHz (7.6GHz) memory - 2012MHz out of the box boost.
My Pascal throttles in 12.5MHz increments every 8C starting at 32C - I set a +110MHz offset to keep the constant 2.1GHz.

Anyone knows how to force GPUGRID to work with two different cards : Pascal (cuda 80) and GTX 670 (cuda 65). When I put new card into computer my old card stopped work with GPUGRID. Do you know how to solve this problem?
Many thanks!

Anyone knows how to force GPUGRID to work with two different cards : Pascal (cuda 80) and GTX 670 (cuda 65). When I put new card into computer my old card stopped work with GPUGRID. Do you know how to solve this problem?
Many thanks!

Basically No:
Either the app sorts that out or there are two different queues and you can manipulate your Boinc config files to do what you want.
At present the cuda80 app is exclusively for Pascal's and the cuda65 app doesn't work for Pascal's.
The cuda80 app has also populated all queues - which is fine for most people's setups.

If possible move one of the GPUs to another system.

In theory you could have two instances of Boinc with different drive locations and exclude one GPU for each instance, but in practice running two instances of Boinc just doesn't work.

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