add GPU example

Author: jeremiaswerner

experimental/serverless-fleets/tutorials/docling/README.md

@@ -57,7 +57,9 @@ cat commands.jsonl
 
 ### Step 3 - Run the Fleet
 
-Now run the fleet to process the PDFs. In this tutorial we use the static array index with `--tasks-from-file commands.jsonl` to specify the tasks for the 11 pdfs. We give each task 24 vCPU, run docling with `--num-threads 24` and choose a mx3d-24x240 worker profile with 24 vCPU. Therefore we run only 1 docling command per worker at a time and utilize the full worker per pdf processing. We run `--max-scale 4` instances and workers in parallel. Launch the fleet with the following command in the `tutorials/docling` directory.
+Now run the fleet to process the PDFs. In this tutorial we use the static array index with `--tasks-from-file commands.jsonl` to specify the tasks for the 11 pdfs. We give each task 24 vCPU, run docling with `--num-threads 24` and choose a mx3d-24x240 worker profile with 24 vCPU. Therefore we run only 1 docling command per worker at a time and utilize the full worker per pdf processing. We run `--max-scale 4` instances and workers in parallel. 
+
+Launch the fleet with the following command in the `tutorials/docling` directory.
 ```
 ./run
 ```
@@ -173,6 +175,10 @@ If you want to modify the tutorial to add some more parallism, e.g. to run 4 doc
 2. the cpu per task to `--cpu 6`
 Now, with `--max-scale 4` you would only get a single worker. Modify `--max-scale 8` to get 2 workers, each processing 4 docling commands.
 
+#### Run with a Serverless GPU
+
+Run `./run_gpu` to launch the docling commands on a GPU. This example, is bringing up a single `gx3-24x120x1l40s` and runs the 11 pdfs sequentially.
+
 
 ### Step 4 - Download results
 

experimental/serverless-fleets/tutorials/docling/run_gpu

@@ -0,0 +1,29 @@
+#!/bin/bash
+
+set -e
+
+uuid=$(uuidgen | tr '[:upper:]' '[:lower:]' | awk -F- '{print $1}')
+
+# https://github.com/docling-project/docling-serve?tab=readme-ov-file#container-images
+IMAGE="quay.io/docling-project/docling-serve"
+
+echo ibmcloud code-engine experimental fleet run --name "fleet-${uuid}-1"
+echo "  "--image $IMAGE
+echo "  "--registry-secret fleet-registry-secret
+echo "  "--worker-profile gx3-24x120x1l40s
+echo "  "--max-scale 1
+echo "  "--tasks-from-file commands.jsonl
+echo "  "--cpu 24
+echo "  "--memory 120G
+
+ibmcloud code-engine experimental fleet run --name "fleet-${uuid}-1" \
+--image $IMAGE \
+--registry-secret fleet-registry-secret \
+--worker-profile gx3-24x120x1l40s \
+--max-scale 1 \
+--tasks-from-file commands.jsonl \
+--cpu 24 \
+--memory 120G \
+
+ibmcloud code-engine experimental fleet get --name "fleet-${uuid}-1"
+