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GTX 1080 Ti
### Specs
Maximum Graphics Card Power (W) 250
#### Cores
CUDA Cores 3584
Graphics Clock (MHz) 1480
Processor Clock (MHz) 1582
#### Memory
Standard Memory Config 11 GB GDDR5X
Memory Interface Width 352-bit
Memory Bandwidth (GB/sec) 11 Gbps
#### Supported Technologies
SLI, CUDA, 3D Vision, PhysX, NVIDIA G-SYNC™, GameStream, ShadowWorks, DirectX 12, Virtual Reality, Ansel

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### 3/ [coins](projects.feedfarm.md#coins) _?_
## GeForce
## Questions
### Interkonektivity via SLI
sli becomes NVlink
##### https://en.wikipedia.org/wiki/Scalable_Link_Interface
>SLI allows two, three, or four graphics processing units (GPUs) to share the workload when rendering real-time 3D computer graphics.
>Not all motherboards with multiple PCI-Express x16 slots support SLI.
##### https://www.gpumag.com/nvidia-sli-and-compatible-cards/
>**High-Bandwidth Bridge or SLI HB Bridge** (650 MHz Pixel Clock and 2GB/s Bandwidth) This is the fastest bridge and is sold exclusively by Nvidia. Its recommended for monitors up to 5K and surround. SLI HB Bridges are only available in 2-way configurations.
##### resume?
- [SLI is not needed for 3d renders](https://linustechtips.com/topic/896397-is-sli-really-needed-for-rendering/)
- [SLI and VR](https://www.quora.com/Is-SLI-worth-it-for-VR?share=1)
- [ SLI in gamemachine](https://www.quora.com/Is-SLI-worth-it-in-a-gaming-machine)
- SLI and nvidia quadro?
- [ SLI and machine learning]
- https://www.mathworks.com/matlabcentral/answers/482171-can-i-ues-nvidia-gpu-sli-bridges-for-better-deep-learning-performance
### VRam share?
- is it possible?
- --> seems not possible ---> 11GB
### Machine Learning
- https://www.pugetsystems.com/labs/hpc/NVIDIA-GTX-1080Ti-Performance-for-Machine-Learning----as-Good-as-TitanX-913/
#### Hardware setup
- https://blog.slavv.com/the-1700-great-deep-learning-box-assembly-setup-and-benchmarks-148c5ebe6415 !!!
- https://medium.com/the-mission/how-to-build-the-perfect-deep-learning-computer-and-save-thousands-of-dollars-9ec3b2eb4ce2
- http://guanghan.info/blog/en/my-works/building-our-personal-deep-learning-rig-gtx-1080-ubuntu-16-04-cuda-8-0rc-cudnn-7-tensorflowmxnetcaffedarknet/
- https://www.servethehome.com/deeplearning10-the-8x-nvidia-gtx-1080-ti-gpu-monster-part-1/
- multi gpus
- https://hackerfall.com/story/which-gpus-to-get-for-deep-learning
- https://medium.com/analytics-vidhya/setting-up-a-multi-gpu-machine-and-testing-with-a-tensorflow-deep-learning-model-c35ad76603cf
- cluster networking
- https://timdettmers.com/2014/09/21/how-to-build-and-use-a-multi-gpu-system-for-deep-learning/
##### !!
https://timdettmers.com/2020/09/07/which-gpu-for-deep-learning/
https://timdettmers.com/2018/12/16/deep-learning-hardware-guide/
----
https://www.reddit.com/r/buildapc/comments/inqpo5/multigpu_seven_rtx_3090_workstation_possible/
## 3D
### Blender
#### sheepit
- cant manage plenty of stuff
## render farms
- https://www.videomaker.com/article/c01/18933-make-a-render-farm-out-of-old-computers-for-a-cost-effective-way-to-speed-up-rendering
- https://www.toolfarm.com/tutorial/in_depth_render_farms-2/
@ -76,13 +17,15 @@ https://www.reddit.com/r/buildapc/comments/inqpo5/multigpu_seven_rtx_3090_workst
- [linux video tutorial](https://www.youtube.com/watch?v=10cpBZ86vrc)
- [DaVinci Resolve Remote Render Server Complete Guide (Windows/Linux)](https://forum.level1techs.com/t/davinci-resolve-remote-render-server-complete-guide-windows-linux/138807)
### blender
## AI
#incubation https://www.makeuseof.com/4-unique-ways-to-get-datasets-for-your-machine-learning-project/
### spleeter
!!!! #incubation !!!!
EASYTOGO
### [incubation.openAI](incubation.openAI.md)
#### [jukebox](https://github.com/openai/jukebox)
- [ ] 16gb VRAM?
@ -105,8 +48,10 @@ EASYTOGO
- https://runwayml.com/
## coins
- Efektivni vs. efektni?
- bitcoin? [[ethereum]] ?
- [[ethereum]]
- pools
- ethermine
- peerideo
??????? ???????
???????

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## Questions
### Interkonektivity via SLI
sli becomes NVlink
##### https://en.wikipedia.org/wiki/Scalable_Link_Interface
>SLI allows two, three, or four graphics processing units (GPUs) to share the workload when rendering real-time 3D computer graphics.
>Not all motherboards with multiple PCI-Express x16 slots support SLI.
##### https://www.gpumag.com/nvidia-sli-and-compatible-cards/
>**High-Bandwidth Bridge or SLI HB Bridge** (650 MHz Pixel Clock and 2GB/s Bandwidth) This is the fastest bridge and is sold exclusively by Nvidia. Its recommended for monitors up to 5K and surround. SLI HB Bridges are only available in 2-way configurations.
##### resume?
- [SLI is not needed for 3d renders](https://linustechtips.com/topic/896397-is-sli-really-needed-for-rendering/)
- [SLI and VR](https://www.quora.com/Is-SLI-worth-it-for-VR?share=1)
- [ SLI in gamemachine](https://www.quora.com/Is-SLI-worth-it-in-a-gaming-machine)
- SLI and nvidia quadro?
- [ SLI and machine learning]
- https://www.mathworks.com/matlabcentral/answers/482171-can-i-ues-nvidia-gpu-sli-bridges-for-better-deep-learning-performance
### VRam share?
- is it possible?
- --> seems not possible ---> 11GB
### Machine Learning
- https://www.pugetsystems.com/labs/hpc/NVIDIA-GTX-1080Ti-Performance-for-Machine-Learning----as-Good-as-TitanX-913/
#### Hardware setup
- https://blog.slavv.com/the-1700-great-deep-learning-box-assembly-setup-and-benchmarks-148c5ebe6415 !!!
- https://medium.com/the-mission/how-to-build-the-perfect-deep-learning-computer-and-save-thousands-of-dollars-9ec3b2eb4ce2
- http://guanghan.info/blog/en/my-works/building-our-personal-deep-learning-rig-gtx-1080-ubuntu-16-04-cuda-8-0rc-cudnn-7-tensorflowmxnetcaffedarknet/
- https://www.servethehome.com/deeplearning10-the-8x-nvidia-gtx-1080-ti-gpu-monster-part-1/
- multi gpus
- https://hackerfall.com/story/which-gpus-to-get-for-deep-learning
- https://medium.com/analytics-vidhya/setting-up-a-multi-gpu-machine-and-testing-with-a-tensorflow-deep-learning-model-c35ad76603cf
- cluster networking
- https://timdettmers.com/2014/09/21/how-to-build-and-use-a-multi-gpu-system-for-deep-learning/
##### !!
https://timdettmers.com/2020/09/07/which-gpu-for-deep-learning/
https://timdettmers.com/2018/12/16/deep-learning-hardware-guide/
----
https://www.reddit.com/r/buildapc/comments/inqpo5/multigpu_seven_rtx_3090_workstation_possible/