Switch GPU backend from Vulkan to SYCL for ~2x inference performance on Intel GPUs

Build ggml-sycl from upstream llama.cpp (commit a5bb8ba4, matching ollama's
vendored ggml) using Intel oneAPI 2025.1.1 in a multi-stage Docker build.
Patch two ollama-specific API divergences via patch-sycl.py: added batch_size
parameter to graph_compute, removed GGML_TENSOR_FLAG_COMPUTE skip-check that
caused all compute nodes to be bypassed.

Tested: gemma3:1b — 27/27 layers on GPU, 10.2 tok/s gen, 65.3 tok/s prompt eval.
Co-authored-by: Cursor <cursoragent@cursor.com>

docker-compose.yml

@@ -8,8 +8,7 @@ services:
     container_name: ollama-intel-gpu
     restart: unless-stopped
     devices:
-      #  - /dev/dri:/dev/dri
-      - /dev/dri/renderD128:/dev/dri/renderD128
+      - /dev/dri:/dev/dri
     volumes:
       - /tmp/.X11-unix:/tmp/.X11-unix
       - ollama-intel-gpu:/root/.ollama
@@ -17,7 +16,9 @@ services:
     environment:
       - DISPLAY=${DISPLAY}
       - OLLAMA_HOST=0.0.0.0
-      - OLLAMA_VULKAN=1
+      - OLLAMA_DEBUG=1
+      - ONEAPI_DEVICE_SELECTOR=level_zero:0
+      - ZES_ENABLE_SYSMAN=1
       - OLLAMA_DEFAULT_KEEPALIVE=6h
       - OLLAMA_KEEP_ALIVE=24h
       - OLLAMA_MAX_LOADED_MODELS=1