Andriy Oblivantsev
52672c34b0
Workflow triggers on push to main/release branches, tags, PRs, and manual dispatch. Uses Docker Buildx with GHA cache for faster rebuilds. Tags images with ollama version, git SHA, and branch/tag names. Co-authored-by: Cursor <cursoragent@cursor.com>
162 lines
6.6 KiB
Markdown
162 lines
6.6 KiB
Markdown
# Ollama for Intel GPU (SYCL)
|
|
|
|
> Run LLMs on Intel GPUs at full speed — no NVIDIA required.
|
|
|
|
A Docker-based setup that pairs [Ollama](https://github.com/ollama/ollama) **v0.15.6** with a custom-built **SYCL backend** for Intel GPU acceleration, plus [Open WebUI](https://github.com/open-webui/open-webui) for a browser chat interface. Three commands to go from zero to local AI.
|
|
|
|
**Why this exists:** Ollama's official release ships only a Vulkan backend for Intel GPUs, leaving significant performance on the table. This repo builds the `ggml-sycl` backend from source with Intel oneAPI, unlocking oneMKL, oneDNN, and Level-Zero direct GPU access.
|
|
|
|
|
|
---
|
|
|
|
## Quick start
|
|
|
|
### Option A: Build from source
|
|
|
|
```shell
|
|
git clone https://github.com/mattcurf/ollama-intel-gpu
|
|
cd ollama-intel-gpu
|
|
docker compose up
|
|
```
|
|
|
|
The first `docker compose up` builds the SYCL backend from source (~2 min on a modern CPU). Subsequent starts are instant.
|
|
|
|
### Option B: Use the pre-built image
|
|
|
|
```shell
|
|
docker run -d \
|
|
--device /dev/dri:/dev/dri \
|
|
--shm-size 16G \
|
|
-p 11434:11434 \
|
|
-v ollama-data:/root/.ollama \
|
|
ghcr.io/mattcurf/ollama-intel-gpu:latest
|
|
```
|
|
|
|
Open **http://localhost:3000** (with WebUI) or use the API directly at `http://localhost:11434`.
|
|
|
|
> **Multiple GPUs?** Set `ONEAPI_DEVICE_SELECTOR=level_zero:0` in `docker-compose.yml` to pick the right device.
|
|
|
|
---
|
|
|
|
## Tested hardware
|
|
|
|
| Intel GPU | Status |
|
|
|-----------|--------|
|
|
| Core Ultra 7 155H integrated Arc (Meteor Lake) | Verified |
|
|
| Arc A-series (A770, A750, A380) | Expected compatible |
|
|
| Data Center Flex / Max | Expected compatible |
|
|
|
|
**Requirements:** Ubuntu 24.04+, Docker with Compose, Intel GPU with Level-Zero driver support.
|
|
|
|
---
|
|
|
|
## SYCL vs Vulkan performance
|
|
|
|
Both backends run on Intel GPUs. This repo defaults to SYCL for the speed advantage.
|
|
|
|
| Intel GPU | Vulkan | SYCL | Gain |
|
|
|---|---|---|---|
|
|
| MTL iGPU (155H) | ~8-11 tok/s | **~16 tok/s** | +45-100% |
|
|
| ARL-H iGPU | ~10-12 tok/s | **~17 tok/s** | +40-70% |
|
|
| Arc A770 | ~30-35 tok/s | **~55 tok/s** | +57-83% |
|
|
| Flex 170 | ~30-35 tok/s | **~50 tok/s** | +43-67% |
|
|
| Data Center Max 1550 | — | **~73 tok/s** | — |
|
|
|
|
*Benchmarks: llama-2-7b Q4_0, llama.cpp, community-reported.*
|
|
|
|
**What makes SYCL faster:**
|
|
|
|
- **oneMKL / oneDNN** — Intel's optimized math and neural network libraries
|
|
- **Level-Zero** — direct GPU communication, lower overhead than Vulkan
|
|
- **Intel-tuned kernels** — MUL_MAT hand-optimized per architecture (MTL, ARL, Arc, Flex, PVC)
|
|
|
|
**When Vulkan makes sense:** no build step, cross-vendor support (AMD/NVIDIA), smaller image. Use the official Ollama Docker image with `OLLAMA_VULKAN=1`.
|
|
|
|
---
|
|
|
|
## How it works
|
|
|
|
Ollama ships the `ggml-sycl.h` header but intentionally excludes the SYCL implementation from its vendored ggml. This repo fills that gap:
|
|
|
|
```
|
|
┌─────────────────────────────────────────────────────────┐
|
|
│ Stage 1: Build (intel/oneapi-basekit:2025.1.1) │
|
|
│ │
|
|
│ ollama v0.15.6 source ──┐ │
|
|
│ ├── cmake + icpx ── libggml-sycl.so
|
|
│ ggml-sycl @ a5bb8ba4 ──┘ │
|
|
│ ▲ │
|
|
│ └── patch-sycl.py (2 API fixes) │
|
|
├─────────────────────────────────────────────────────────┤
|
|
│ Stage 2: Runtime (ubuntu:24.04) │
|
|
│ │
|
|
│ ollama binary (official v0.15.6) │
|
|
│ + libggml-sycl.so + oneAPI runtime libs │
|
|
│ + Intel GPU drivers (Level-Zero, IGC, compute-runtime) │
|
|
│ + Open WebUI (separate container) │
|
|
└─────────────────────────────────────────────────────────┘
|
|
```
|
|
|
|
The `ggml-sycl` source is fetched from the **exact llama.cpp commit** (`a5bb8ba4`) that ollama vendors, ensuring ABI compatibility. Two small patches are applied by `patch-sycl.py`:
|
|
|
|
1. **`graph_compute` signature** — ollama adds an `int batch_size` parameter not present upstream
|
|
2. **`GGML_TENSOR_FLAG_COMPUTE` removal** — ollama drops this enum; without the patch, every compute node gets skipped, producing garbage output
|
|
|
|
---
|
|
|
|
## Configuration
|
|
|
|
Environment variables in `docker-compose.yml`:
|
|
|
|
| Variable | Default | Description |
|
|
|---|---|---|
|
|
| `OLLAMA_HOST` | `0.0.0.0` | Listen address |
|
|
| `OLLAMA_KEEP_ALIVE` | `24h` | How long models stay loaded in memory |
|
|
| `OLLAMA_NUM_PARALLEL` | `1` | Concurrent request slots |
|
|
| `OLLAMA_MAX_LOADED_MODELS` | `1` | Max models in VRAM simultaneously |
|
|
| `ONEAPI_DEVICE_SELECTOR` | `level_zero:0` | Which Intel GPU to use |
|
|
| `ZES_ENABLE_SYSMAN` | `1` | Enable Level-Zero system management |
|
|
| `OLLAMA_DEBUG` | `1` | Verbose logging (disable in production) |
|
|
|
|
---
|
|
|
|
## Project structure
|
|
|
|
```
|
|
.
|
|
├── Dockerfile # Multi-stage build: oneAPI SYCL → minimal runtime
|
|
├── docker-compose.yml # ollama + Open WebUI services
|
|
├── patch-sycl.py # Patches ggml-sycl for ollama API compatibility
|
|
├── start-ollama.sh # Custom entrypoint (legacy, from IPEX-LLM era)
|
|
└── doc/
|
|
└── screenshot.png
|
|
```
|
|
|
|
---
|
|
|
|
## Troubleshooting
|
|
|
|
**SYCL device not detected** — Ensure `/dev/dri` is accessible. Check `docker compose logs ollama-intel-gpu` for `SYCL0` in the device list.
|
|
|
|
**"failed to sample token"** — Usually means an ABI mismatch between ggml-sycl and ollama's vendored ggml. The `GGML_COMMIT` ARG in the Dockerfile must match the ggml version ollama vendors.
|
|
|
|
**Model too large for VRAM** — Intel integrated GPUs share system memory. Increase `shm_size` in `docker-compose.yml` or use a smaller quantization (Q4_0, Q4_K_M).
|
|
|
|
**Slow first inference** — SYCL JIT-compiles GPU kernels on first run. Subsequent inferences are faster.
|
|
|
|
---
|
|
|
|
## References
|
|
|
|
- [Ollama](https://github.com/ollama/ollama)
|
|
- [Open WebUI](https://github.com/open-webui/open-webui)
|
|
- [llama.cpp SYCL backend](https://github.com/ggml-org/llama.cpp/blob/master/docs/backend/SYCL.md)
|
|
- [Intel oneAPI base toolkit](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html)
|
|
- [Intel GPU driver installation](https://dgpu-docs.intel.com/driver/client/overview.html)
|
|
|
|
---
|
|
|
|
## License
|
|
|
|
See [LICENSE](LICENSE) for details.
|