moirk/Unraid_Intel-ARC_Deployment
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Update README.md

Browse Source
This commit is contained in:
Admin9705
2024-12-12 09:33:45 -05:00
committed by GitHub
parent 3e9596ac63
commit ee788920a3
1 changed files with 13 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
README.md
View File

@@ -51,7 +51,7 @@ Whether you’re an experienced Unraid user or just beginning, this step-by-step
## Data Savings with AV1 Encoding
AV1 encoding drastically reduces file sizes. Using three Intel ARC GPUs to encode just 10-15% of a large library saved about 37TB. For a 300TB collection, careful AV1 conversion could reduce it to 75-100TB.
AV1 encoding drastically reduces file sizes. Using three Intel ARC GPUs to encode just 10-15% of a large library saved about 116TB. For a 300TB collection, careful AV1 conversion could reduce it to 75-100TB.
<img width="373" alt="image" src="https://github.com/user-attachments/assets/09d36726-56d9-4c53-8589-eca2173e7283">
@@ -121,8 +121,8 @@ If you find this guide helpful, consider clicking the ★ (Star) button above. I
When installing Tdarr, you may see an option to deploy both the server and node in one container. For easier troubleshooting, deploy them separately.
1. Install **Tdarr Server** (not Tdarr Node) from the Unraid App Store.
2. Name it clearly, e.g., “Tdarr_Server.”
1. Install **Tdarr** (not Tdarr Node) from the Unraid App Store.
2. Name it clearly, e.g., “Server” “TServer” “TdarrServer”
3. Ensure the server IP is correct (usually your Unraid server’s IP).
4. Set the internal node option to **False**, so you will deploy a separate node container later.
@@ -134,11 +134,15 @@ When installing Tdarr, you may see an option to deploy both the server and node
## Tdarr Transcoding Location
Choose a suitable location for transcoding. For occasional use, an SSD/NVMe cache is fine. For heavy use (multiple streams, multiple GPUs), consider a dedicated NVMe. Avoid HDDs or RAM to prevent bottlenecks and errors.
Choose a suitable location for transcoding. For occasional use, an SSD/NVMe cache is fine. For heavy use (multiple streams, multiple GPUs), consider a dedicated NVMe. Avoid HDDs or RAM to prevent bottlenecks and errors.
### Warning: Bottlenecks & SSD Wear
Continuous transcoding strains SSD/NVMe drives. Using a dedicated, cost-effective NVMe helps preserve your primary drives’ health.
Continuous transcoding strains SSD/NVMe drives. Using a dedicated, cost-effective NVMe helps preserve your primary drives’ health.
Note this is optional. I have a cheap 512GB NVME that Tdarr transcodes to. Since Tdarr will transcode 100s of TBs of data possibly, avoid wearing your primary SSD/NVME. I personally had an NVME give me a BAD SMART warning (nothing was wrong with it) but warning of ZERO life left for reliability.
I also personally encountered where Tdarr bottleneck my primary NVME due to the amount of GPU's and Transcodes reading and writing to my primary appdata NVME.
<img width="754" alt="image" src="https://github.com/user-attachments/assets/daac629c-3fe9-45e4-89e9-c8e50686e2ea" />
@@ -149,7 +153,7 @@ After deploying the Tdarr Server, install the **Tdarr Node** (listed separately)
<img width="397" alt="image" src="https://github.com/user-attachments/assets/6b384a42-194d-4089-b1ff-89d6cca77728" />
1. Install **Tdarr Node** from the Unraid App Store.
2. Give it a clear name, e.g., Node1. For multiple GPUs, deploy more nodes (Node2, etc.).
2. Give it a clear name, e.g., Node1. For multiple GPUs, deploy more nodes (N1, N2, etc.).
3. Ensure the server IP and Node IP match.
4. Keep configs/logs organized per node.
5. Match the transcode cache path from the server’s template. Add node identifiers if using multiple nodes.
@@ -158,7 +162,9 @@ After deploying the Tdarr Server, install the **Tdarr Node** (listed separately)
To identify GPUs:
* `ls -la /dev/dri/`
**WARNING:** One entry might be your iGPU. Do not assign the iGPU to a Tdarr Node. Check Plex’s GPU order if unsure.
**WARNING:** One entry might be your iGPU. Do not assign the iGPU to a Tdarr Node.
_Tip:_ If you go to plex, goto Transcoding and click your GPU list... the actually order listed there is the same order of the GPUs when typing ls -la /dev/dri. In the phot example below, you will notice I skipped render129, which is actually the iGPU. Plex lists my order of graphics cards as Intel ARC 380 > Raphel (AMD iGPU) > Intel ARC 380 > Intel ARC 380. So the second one on the plex list of graphics cards was the same order of of ls -la /dev/dri.
<img width="477" alt="image" src="https://github.com/user-attachments/assets/8ce39a4d-1479-433c-b3c8-9eceb4ebf044" />
<img width="749" alt="image" src="https://github.com/user-attachments/assets/736eff11-ec78-441d-9c82-0f11def877bd" />