Run Multiple WU's on Your GPU

Perhaps related,
For Nvidia RTX 2000 series GPUs, anything above 2 is useless.
The RTX 2080 Ti does 3 WUs at the same time as it does 2WUs, a tiny bit faster, but it'll also consume about 10W more power ( 5%) for finishing 2x3 WUs in less than 5% difference in time of 3x2WUs.
AMD GPUs are a bit better for Einstein and Milkyway, because they have more DPP.

I think because Milkyway is using DPP, more than what the GPUs actually have to offer, and thus is bottlenecking the GPU by a lot! (80-140W usage out of 150-195W limits).
If that's the case, you could set GPU to 0.33 and 0.25, on RTX3080 and 3090.

My main issue is, that I want to use only 1 Milkyway on my GPU, and combine it with another project that doesn't use a lot of 64bit (DPP) commands.
I have 2 GPUs in my system, and want to run 1 Milkyway WU per GPU.
With my current setup, 2 MW WUs are running on one GPU, and none on the second.

<app_config>
<app>
<name>milkyway</name>
<gpu_versions>
<max_concurrent>2</max_concurrent>
<gpu_usage>0.3333</gpu_usage>
<cpu_usage>0.5</cpu_usage>
</gpu_versions>
</app>
<project_max_concurrent>2</project_max_concurrent>
</app_config>

Perhaps related,
For Nvidia RTX 2000 series GPUs, anything above 2 is useless.
The RTX 2080 Ti does 3 WUs at the same time as it does 2WUs, a tiny bit faster, but it'll also consume about 10W more power ( 5%) for finishing 2x3 WUs in less than 5% difference in time of 3x2WUs.
AMD GPUs are a bit better for Einstein and Milkyway, because they have more DPP.

Einstein is SP.

I think because Milkyway is using DPP, more than what the GPUs actually have to offer, and thus is bottlenecking the GPU by a lot! (80-140W usage out of 150-195W limits).
If that's the case, you could set GPU to 0.33 and 0.25, on RTX3080 and 3090.

Fine if you add another task that isn't MW. But two MW will not magically create more DP units in your card. Doubling up the same type of project on one card only solves one problem - the CPU is holding up the GPU.

I've ceased bothering anyway, it doesn't gain you that much in any scenario.

Hi Guys,

So I have tried running more than one unit and I can't get much of a boost from it, so for example, if I run 1 unit the completion times are around 1:40, if I run 2 they are around 3:30 so if anything they are running slower.
GPU is an RTX 3090, I checked the power usage and on a single unit it's pulling around 190w, and for two it's around 215w, I tried up to 5 and it seems to cap at 215w no matter the number of units.
The card can pull up to 350w under full load (Einstein does) so it feels like for whatever reason MW@H cant fully utilize my card even with multiple WU's.
Any ideas on how to fully use the card with multiple WU's?
My config is for two units:

<app_config>
<app>
<name>milkyway</name>
<gpu_versions>
<gpu_usage>0.5</gpu_usage>
<cpu_usage>0.05</cpu_usage>
</gpu_versions>
</app>
</app_config>

Hi Guys,

So I have tried running more than one unit and I can't get much of a boost from it, so for example, if I run 1 unit the completion times are around 1:40, if I run 2 they are around 3:30 so if anything they are running slower.
GPU is an RTX 3090, I checked the power usage and on a single unit it's pulling around 190w, and for two it's around 215w, I tried up to 5 and it seems to cap at 215w no matter the number of units.
The card can pull up to 350w under full load (Einstein does) so it feels like for whatever reason MW@H cant fully utilize my card even with multiple WU's.
Any ideas on how to fully use the card with multiple WU's?
My config is for two units:

<app_config>
<app>
<name>milkyway</name>
<gpu_versions>
<gpu_usage>0.5</gpu_usage>
<cpu_usage>0.05</cpu_usage>
</gpu_versions>
</app>
</app_config>

You may or may not get a boost, it depends on your CPU and GPU relative speeds. Ignore what I said in my last post, I'm now doubling up in some circumstances. If the CPU is slow (per core, as the tasks will only use 1 core) and the GPU is fast, then doubling or more will help. If you have a good CPU and it's not doing much else, and your GPU isn't that fast, then you might not need to. It also depends on what you're running on the GPU, some projects have apps that require more CPU than others. Einstein needs a lot, Collatz doesn't need much at all. MW needs it in chunks as it starts each of the tasks inside the bundle (currently a bundle of 4, so you'll see it pausing at 25, 50, 75%). What I do is watch the GPU usage in something like GPU-Z or MSI Afterburner, something with a graph of usage. If it's pretty much 100% all the time, leave it alone. If it's dipping a lot, try doubling and see if it goes higher. You can also try freeing up CPU cores.

You need to build a tired old PC and add a few HD 7970 or R9 280X cards to it....

Just because Nvidia sell you a high priced item doesn't make it suitable for efficient use on this project.

I bought a used Gen 1 GTX Titan Black for the high DP and extra RAM, but it is still 3x slower than a cheap R9 280X.

I currently run a Radeon VII and spews out a result every 11 seconds, running multiple tasks on a quad core CPU.

I would say Nvidia cards would be better used for GPUGrid, but they have no work available....

dunx

I would say Nvidia cards would be better used for GPUGrid, but they have no work available....

Nvidia is cerainly not efficient with MW. Folding has a CUDA app now, and enough work. They are past their shortages.
You can run the GPU on folding, and by eliminating the CPU slot (enabled by default) run BOINC on the CPU if you want to.
https://foldingathome.org/start-folding/

You need to build a tired old PC and add a few HD 7970 or R9 280X cards to it....

Just because Nvidia sell you a high priced item doesn't make it suitable for efficient use on this project.

I bought a used Gen 1 GTX Titan Black for the high DP and extra RAM, but it is still 3x slower than a cheap R9 280X.

I currently run a Radeon VII and spews out a result every 11 seconds, running multiple tasks on a quad core CPU.

I would say Nvidia cards would be better used for GPUGrid, but they have no work available....

dunx

Yip, I always get old AMD cards for Boinc. I'm appalled at Nvidia's attitude making the DP so slow.

You need to build a tired old PC and add a few HD 7970 or R9 280X cards to it....

Just because Nvidia sell you a high priced item doesn't make it suitable for efficient use on this project.

I bought a used Gen 1 GTX Titan Black for the high DP and extra RAM, but it is still 3x slower than a cheap R9 280X.

I currently run a Radeon VII and spews out a result every 11 seconds, running multiple tasks on a quad core CPU.

I would say Nvidia cards would be better used for GPUGrid, but they have no work available....

dunx

Yip, I always get old AMD cards for Boinc. I'm appalled at Nvidia's attitude making the DP so slow.

Some projects do do better with Nvidia cards but as you said those requiring DP do better with AMD cards.

Some projects do do better with Nvidia cards but as you said those requiring DP do better with AMD cards.

I'll be getting a very fast Nvidia one day for a game, I guess I'll allocate that to SP projects only. Unless I find an AMD that's as good. I need 4K at 120 frames per second.

Your 3090 will crush tasks at primegrid....... although I've seen with GFN-16 tasks, its not much quicker than a 3060Ti! Same can't be said for other PG sub projects though where the 3090 will be king.

---

Your 3090 will crush tasks at primegrid....... although I've seen with GFN-16 tasks, its not much quicker than a 3060Ti! Same can't be said for other PG sub projects though where the 3090 will be king.

It seems impossible to get a straight answer anywhere as to which projects use DP (and are therefore best on old AMDs) and which are SP (which are therefore best on new Nvidias). Presumably the developers must know!

Mainly from my own testing with a few cards to see how fast they go, it appears that:

Einstein=SP
Milkyway=DP
Collatz=SP
Primegrid=half of each

SRBase seems to be SP