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sycl : backend documentation review (#13544)

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* sycl: reviewing and updating docs

* Updates Runtime error codes

* Improves OOM troubleshooting entry

* Added a llama 3 sample

* Updated supported models

* Updated releases table
This commit is contained in:
Alberto Cabrera Pérez
2025-05-19 14:38:20 +01:00
committed by GitHub
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commit 725f23f1f3
6 changed files with 96 additions and 39 deletions
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85
docs/backend/SYCL.md
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@ -17,25 +17,25 @@
**SYCL** is a high-level parallel programming model designed to improve developers productivity writing code across various hardware accelerators such as CPUs, GPUs, and FPGAs. It is a single-source language designed for heterogeneous computing and based on standard C++17. **SYCL** is a high-level parallel programming model designed to improve developers productivity writing code across various hardware accelerators such as CPUs, GPUs, and FPGAs. It is a single-source language designed for heterogeneous computing and based on standard C++17.
**oneAPI** is an open ecosystem and a standard-based specification, supporting multiple architectures including but not limited to intel CPUs, GPUs and FPGAs. The key components of the oneAPI ecosystem include: **oneAPI** is an open ecosystem and a standard-based specification, supporting multiple architectures including but not limited to Intel CPUs, GPUs and FPGAs. The key components of the oneAPI ecosystem include:
- **DPCPP** *(Data Parallel C++)*: The primary oneAPI SYCL implementation, which includes the icpx/icx Compilers. - **DPCPP** *(Data Parallel C++)*: The primary oneAPI SYCL implementation, which includes the icpx/icx Compilers.
- **oneAPI Libraries**: A set of highly optimized libraries targeting multiple domains *(e.g. Intel oneMKL, oneMath and oneDNN)*. - **oneAPI Libraries**: A set of highly optimized libraries targeting multiple domains *(e.g. Intel oneMKL, oneMath and oneDNN)*.
- **oneAPI LevelZero**: A high performance low level interface for fine-grained control over intel iGPUs and dGPUs. - **oneAPI LevelZero**: A high performance low level interface for fine-grained control over Intel iGPUs and dGPUs.
- **Nvidia & AMD Plugins**: These are plugins extending oneAPI's DPCPP support to SYCL on Nvidia and AMD GPU targets. - **Nvidia & AMD Plugins**: These are plugins extending oneAPI's DPCPP support to SYCL on Nvidia and AMD GPU targets.
### Llama.cpp + SYCL ### Llama.cpp + SYCL
The llama.cpp SYCL backend is designed to support **Intel GPU** firstly. Based on the cross-platform feature of SYCL, it also supports other vendor GPUs: Nvidia and AMD. The llama.cpp SYCL backend is primarily designed for **Intel GPUs**.
SYCL cross-platform capabilities enable support for Nvidia GPUs as well, with limited support for AMD.
## Recommended Release ## Recommended Release
The SYCL backend would be broken by some PRs due to no online CI. The following releases are verified and recommended:
The following release is verified with good quality:
|Commit ID|Tag|Release|Verified Platform| Update date| |Commit ID|Tag|Release|Verified Platform| Update date|
|-|-|-|-|-| |-|-|-|-|-|
|24e86cae7219b0f3ede1d5abdf5bf3ad515cccb8|b5377 |[llama-b5377-bin-win-sycl-x64.zip](https://github.com/ggml-org/llama.cpp/releases/download/b5377/llama-b5377-bin-win-sycl-x64.zip) |ArcB580/Linux/oneAPI 2025.1<br>LNL Arc GPU/Windows 11/oneAPI 2025.1.1|2025-05-15|
|3bcd40b3c593d14261fb2abfabad3c0fb5b9e318|b4040 |[llama-b4040-bin-win-sycl-x64.zip](https://github.com/ggml-org/llama.cpp/releases/download/b4040/llama-b4040-bin-win-sycl-x64.zip) |Arc770/Linux/oneAPI 2024.1<br>MTL Arc GPU/Windows 11/oneAPI 2024.1| 2024-11-19| |3bcd40b3c593d14261fb2abfabad3c0fb5b9e318|b4040 |[llama-b4040-bin-win-sycl-x64.zip](https://github.com/ggml-org/llama.cpp/releases/download/b4040/llama-b4040-bin-win-sycl-x64.zip) |Arc770/Linux/oneAPI 2024.1<br>MTL Arc GPU/Windows 11/oneAPI 2024.1| 2024-11-19|
|fb76ec31a9914b7761c1727303ab30380fd4f05c|b3038 |[llama-b3038-bin-win-sycl-x64.zip](https://github.com/ggml-org/llama.cpp/releases/download/b3038/llama-b3038-bin-win-sycl-x64.zip) |Arc770/Linux/oneAPI 2024.1<br>MTL Arc GPU/Windows 11/oneAPI 2024.1|| |fb76ec31a9914b7761c1727303ab30380fd4f05c|b3038 |[llama-b3038-bin-win-sycl-x64.zip](https://github.com/ggml-org/llama.cpp/releases/download/b3038/llama-b3038-bin-win-sycl-x64.zip) |Arc770/Linux/oneAPI 2024.1<br>MTL Arc GPU/Windows 11/oneAPI 2024.1||
@ -106,15 +106,14 @@ SYCL backend supports Intel GPU Family:
|-------------------------------|---------|---------------------------------------| |-------------------------------|---------|---------------------------------------|
| Intel Data Center Max Series | Support | Max 1550, 1100 | | Intel Data Center Max Series | Support | Max 1550, 1100 |
| Intel Data Center Flex Series | Support | Flex 170 | | Intel Data Center Flex Series | Support | Flex 170 |
| Intel Arc Series | Support | Arc 770, 730M, Arc A750 | | Intel Arc Series | Support | Arc 770, 730M, Arc A750, B580 |
| Intel built-in Arc GPU | Support | built-in Arc GPU in Meteor Lake, Arrow Lake | | Intel built-in Arc GPU | Support | built-in Arc GPU in Meteor Lake, Arrow Lake, Lunar Lake |
| Intel iGPU | Support | iGPU in 13700k,iGPU in 13400, i5-1250P, i7-1260P, i7-1165G7 | | Intel iGPU | Support | iGPU in 13700k, 13400, i5-1250P, i7-1260P, i7-1165G7 |
*Notes:* *Notes:*
- **Memory** - **Memory**
- The device memory is a limitation when running a large model. The loaded model size, *`llm_load_tensors: buffer_size`*, is displayed in the log when running `./bin/llama-cli`. - The device memory is a limitation when running a large model. The loaded model size, *`llm_load_tensors: buffer_size`*, is displayed in the log when running `./bin/llama-cli`.
- Please make sure the GPU shared memory from the host is large enough to account for the model's size. For e.g. the *llama-2-7b.Q4_0* requires at least 8.0GB for integrated GPU and 4.0GB for discrete GPU. - Please make sure the GPU shared memory from the host is large enough to account for the model's size. For e.g. the *llama-2-7b.Q4_0* requires at least 8.0GB for integrated GPU and 4.0GB for discrete GPU.
- **Execution Unit (EU)** - **Execution Unit (EU)**
@ -138,9 +137,11 @@ Note: AMD GPU support is highly experimental and is incompatible with F16.
Additionally, it only supports GPUs with a sub_group_size (warp size) of 32. Additionally, it only supports GPUs with a sub_group_size (warp size) of 32.
## Docker ## Docker
The docker build option is currently limited to *intel GPU* targets.
The docker build option is currently limited to *Intel GPU* targets.
### Build image ### Build image
```sh ```sh
# Using FP16 # Using FP16
docker build -t llama-cpp-sycl --build-arg="GGML_SYCL_F16=ON" --target light -f .devops/intel.Dockerfile . docker build -t llama-cpp-sycl --build-arg="GGML_SYCL_F16=ON" --target light -f .devops/intel.Dockerfile .
@ -148,9 +149,10 @@ docker build -t llama-cpp-sycl --build-arg="GGML_SYCL_F16=ON" --target light -f
*Notes*: *Notes*:
To build in default FP32 *(Slower than FP16 alternative)*, you can remove the `--build-arg="GGML_SYCL_F16=ON"` argument from the previous command. To build in default FP32 *(Slower than FP16 alternative)*, set `--build-arg="GGML_SYCL_F16=OFF"` in the previous command.
You can also use the `.devops/llama-server-intel.Dockerfile`, which builds the *"server"* alternative. You can also use the `.devops/llama-server-intel.Dockerfile`, which builds the *"server"* alternative.
Check the [documentation for Docker](../docker.md) to see the available images.
### Run container ### Run container
@ -250,7 +252,7 @@ sycl-ls
- **Intel GPU** - **Intel GPU**
When targeting an intel GPU, the user should expect one or more level-zero devices among the available SYCL devices. Please make sure that at least one GPU is present, for instance [`level_zero:gpu`] in the sample output below: When targeting an intel GPU, the user should expect one or more devices among the available SYCL devices. Please make sure that at least one GPU is present via `sycl-ls`, for instance `[level_zero:gpu]` in the sample output below:
``` ```
[opencl:acc][opencl:0] Intel(R) FPGA Emulation Platform for OpenCL(TM), Intel(R) FPGA Emulation Device OpenCL 1.2 [2023.16.10.0.17_160000] [opencl:acc][opencl:0] Intel(R) FPGA Emulation Platform for OpenCL(TM), Intel(R) FPGA Emulation Device OpenCL 1.2 [2023.16.10.0.17_160000]
@ -282,7 +284,7 @@ For AMD GPUs we should expect at least one SYCL-HIP device [`hip:gpu`]:
#### Intel GPU #### Intel GPU
``` ```sh
./examples/sycl/build.sh ./examples/sycl/build.sh
``` ```
@ -351,7 +353,7 @@ cmake --build build --config Release -j -v
#### Retrieve and prepare model #### Retrieve and prepare model
You can refer to the general [*Prepare and Quantize*](README.md#prepare-and-quantize) guide for model prepration, or simply download [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) model as example. You can refer to the general [*Prepare and Quantize*](README.md#prepare-and-quantize) guide for model preparation, or download an already quantized model like [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) or [Meta-Llama-3-8B-Instruct-Q4_0.gguf](https://huggingface.co/aptha/Meta-Llama-3-8B-Instruct-Q4_0-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q4_0.gguf).
##### Check device ##### Check device
@ -398,11 +400,15 @@ Choose one of following methods to run.
```sh ```sh
./examples/sycl/run-llama2.sh 0 ./examples/sycl/run-llama2.sh 0
# OR
./examples/sycl/run-llama3.sh 0
``` ```
- Use multiple devices: - Use multiple devices:
```sh ```sh
./examples/sycl/run-llama2.sh ./examples/sycl/run-llama2.sh
# OR
./examples/sycl/run-llama3.sh
``` ```
2. Command line 2. Command line
@ -425,13 +431,13 @@ Examples:
- Use device 0: - Use device 0:
```sh ```sh
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -no-cnv -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33 -sm none -mg 0 ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -no-cnv -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 99 -sm none -mg 0
``` ```
- Use multiple devices: - Use multiple devices:
```sh ```sh
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -no-cnv -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33 -sm layer ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -no-cnv -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 99 -sm layer
``` ```
*Notes:* *Notes:*
@ -452,7 +458,7 @@ use 1 SYCL GPUs: [0] with Max compute units:512
1. Install GPU driver 1. Install GPU driver
Intel GPU drivers instructions guide and download page can be found here: [Get intel GPU Drivers](https://www.intel.com/content/www/us/en/products/docs/discrete-gpus/arc/software/drivers.html). Intel GPU drivers instructions guide and download page can be found here: [Get Intel GPU Drivers](https://www.intel.com/content/www/us/en/products/docs/discrete-gpus/arc/software/drivers.html).
2. Install Visual Studio 2. Install Visual Studio
@ -629,7 +635,7 @@ Once it is completed, final results will be in **build/Release/bin**
#### Retrieve and prepare model #### Retrieve and prepare model
You can refer to the general [*Prepare and Quantize*](README.md#prepare-and-quantize) guide for model prepration, or simply download [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) model as example. You can refer to the general [*Prepare and Quantize*](README.md#prepare-and-quantize) guide for model preparation, or download an already quantized model like [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) or [Meta-Llama-3-8B-Instruct-Q4_0.gguf](https://huggingface.co/aptha/Meta-Llama-3-8B-Instruct-Q4_0-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q4_0.gguf).
##### Check device ##### Check device
@ -648,7 +654,7 @@ Similar to the native `sycl-ls`, available SYCL devices can be queried as follow
build\bin\llama-ls-sycl-device.exe build\bin\llama-ls-sycl-device.exe
``` ```
This command will only display the selected backend that is supported by SYCL. The default backend is level_zero. For example, in a system with 2 *intel GPU* it would look like the following: This command will only display the selected backend that is supported by SYCL. The default backend is level_zero. For example, in a system with 2 *Intel GPU* it would look like the following:
``` ```
found 2 SYCL devices: found 2 SYCL devices:
| | | |Compute |Max compute|Max work|Max sub| | | | | |Compute |Max compute|Max work|Max sub| |
@ -658,13 +664,14 @@ found 2 SYCL devices:
| 1|[level_zero:gpu:1]| Intel(R) UHD Graphics 770| 1.3| 32| 512| 32| 53651849216| | 1|[level_zero:gpu:1]| Intel(R) UHD Graphics 770| 1.3| 32| 512| 32| 53651849216|
``` ```
#### Choose level-zero devices #### Choose level-zero devices
|Chosen Device ID|Setting| |Chosen Device ID|Setting|
|-|-| |-|-|
|0|`set ONEAPI_DEVICE_SELECTOR="level_zero:1"` or no action| |0|Default option. You may also want to `set ONEAPI_DEVICE_SELECTOR="level_zero:0"`|
|1|`set ONEAPI_DEVICE_SELECTOR="level_zero:1"`| |1|`set ONEAPI_DEVICE_SELECTOR="level_zero:1"`|
|0 & 1|`set ONEAPI_DEVICE_SELECTOR="level_zero:0;level_zero:1"`| |0 & 1|`set ONEAPI_DEVICE_SELECTOR="level_zero:0;level_zero:1"` or `set ONEAPI_DEVICE_SELECTOR="level_zero:*"`|
#### Execute #### Execute
@ -673,7 +680,13 @@ Choose one of following methods to run.
1. Script 1. Script
``` ```
examples\sycl\win-run-llama2.bat examples\sycl\win-run-llama-2.bat
```
or
```
examples\sycl\win-run-llama-3.bat
``` ```
2. Command line 2. Command line
@ -697,13 +710,13 @@ Examples:
- Use device 0: - Use device 0:
``` ```
build\bin\llama-cli.exe -no-cnv -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 33 -s 0 -sm none -mg 0 build\bin\llama-cli.exe -no-cnv -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 99 -sm none -mg 0
``` ```
- Use multiple devices: - Use multiple devices:
``` ```
build\bin\llama-cli.exe -no-cnv -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 33 -s 0 -sm layer build\bin\llama-cli.exe -no-cnv -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 99 -sm layer
``` ```
@ -714,7 +727,9 @@ Note:
```sh ```sh
detect 1 SYCL GPUs: [0] with top Max compute units:512 detect 1 SYCL GPUs: [0] with top Max compute units:512
``` ```
Or Or
```sh ```sh
use 1 SYCL GPUs: [0] with Max compute units:512 use 1 SYCL GPUs: [0] with Max compute units:512
``` ```
@ -726,15 +741,17 @@ use 1 SYCL GPUs: [0] with Max compute units:512
| Name | Value | Function | | Name | Value | Function |
|--------------------|---------------------------------------|---------------------------------------------| |--------------------|---------------------------------------|---------------------------------------------|
| GGML_SYCL | ON (mandatory) | Enable build with SYCL code path.<br>FP32 path - recommended for better perforemance than FP16 on quantized model| | GGML_SYCL | ON (mandatory) | Enable build with SYCL code path. |
| GGML_SYCL_TARGET | INTEL *(default)* \| NVIDIA \| AMD | Set the SYCL target device type. | | GGML_SYCL_TARGET | INTEL *(default)* \| NVIDIA \| AMD | Set the SYCL target device type. |
| GGML_SYCL_DEVICE_ARCH | Optional (except for AMD) | Set the SYCL device architecture, optional except for AMD. Setting the device architecture can improve the performance. See the table [--offload-arch](https://github.com/intel/llvm/blob/sycl/sycl/doc/design/OffloadDesign.md#--offload-arch) for a list of valid architectures. | | GGML_SYCL_DEVICE_ARCH | Optional (except for AMD) | Set the SYCL device architecture, optional except for AMD. Setting the device architecture can improve the performance. See the table [--offload-arch](https://github.com/intel/llvm/blob/sycl/sycl/doc/design/OffloadDesign.md#--offload-arch) for a list of valid architectures. |
| GGML_SYCL_F16 | OFF *(default)* \|ON *(optional)* | Enable FP16 build with SYCL code path. | | GGML_SYCL_F16 | OFF *(default)* \|ON *(optional)* | Enable FP16 build with SYCL code path. (1.) |
| GGML_SYCL_GRAPH | ON *(default)* \|OFF *(Optional)* | Enable build with [SYCL Graph extension](https://github.com/intel/llvm/blob/sycl/sycl/doc/extensions/experimental/sycl_ext_oneapi_graph.asciidoc). | | GGML_SYCL_GRAPH | ON *(default)* \|OFF *(Optional)* | Enable build with [SYCL Graph extension](https://github.com/intel/llvm/blob/sycl/sycl/doc/extensions/experimental/sycl_ext_oneapi_graph.asciidoc). |
| GGML_SYCL_DNN | ON *(default)* \|OFF *(Optional)* | Enable build with oneDNN. | | GGML_SYCL_DNN | ON *(default)* \|OFF *(Optional)* | Enable build with oneDNN. |
| CMAKE_C_COMPILER | `icx` *(Linux)*, `icx/cl` *(Windows)* | Set `icx` compiler for SYCL code path. | | CMAKE_C_COMPILER | `icx` *(Linux)*, `icx/cl` *(Windows)* | Set `icx` compiler for SYCL code path. |
| CMAKE_CXX_COMPILER | `icpx` *(Linux)*, `icx` *(Windows)* | Set `icpx/icx` compiler for SYCL code path. | | CMAKE_CXX_COMPILER | `icpx` *(Linux)*, `icx` *(Windows)* | Set `icpx/icx` compiler for SYCL code path. |
1. FP16 is recommended for better prompt processing performance on quantized models. Performance is equivalent in text generation but set `GGML_SYCL_F16=OFF` if you are experiencing issues with FP16 builds.
#### Runtime #### Runtime
| Name | Value | Function | | Name | Value | Function |
@ -752,7 +769,7 @@ use 1 SYCL GPUs: [0] with Max compute units:512
## Q&A ## Q&A
- Error: `error while loading shared libraries: libsycl.so.7: cannot open shared object file: No such file or directory`. - Error: `error while loading shared libraries: libsycl.so: cannot open shared object file: No such file or directory`.
- Potential cause: Unavailable oneAPI installation or not set ENV variables. - Potential cause: Unavailable oneAPI installation or not set ENV variables.
- Solution: Install *oneAPI base toolkit* and enable its ENV through: `source /opt/intel/oneapi/setvars.sh`. - Solution: Install *oneAPI base toolkit* and enable its ENV through: `source /opt/intel/oneapi/setvars.sh`.
@ -781,18 +798,18 @@ use 1 SYCL GPUs: [0] with Max compute units:512
It's same for other projects including llama.cpp SYCL backend. It's same for other projects including llama.cpp SYCL backend.
- Meet issue: `Native API failed. Native API returns: -6 (PI_ERROR_OUT_OF_HOST_MEMORY) -6 (PI_ERROR_OUT_OF_HOST_MEMORY) -999 (UNKNOWN PI error)` or `failed to allocate SYCL0 buffer` - `Native API failed. Native API returns: 39 (UR_RESULT_ERROR_OUT_OF_DEVICE_MEMORY)`, `ggml_backend_sycl_buffer_type_alloc_buffer: can't allocate 3503030272 Bytes of memory on device`, or `failed to allocate SYCL0 buffer`
Device Memory is not enough. You are running out of Device Memory.
|Reason|Solution| |Reason|Solution|
|-|-| |-|-|
|Default Context is too big. It leads to more memory usage.|Set `-c 8192` or smaller value.| | The default context is too big. It leads to excessive memory usage.|Set `-c 8192` or a smaller value.|
|Model is big and require more memory than device's.|Choose smaller quantized model, like Q5 -> Q4;<br>Use more than one devices to load model.| | The model is too big and requires more memory than what is available.|Choose a smaller model or change to a smaller quantization, like Q5 -> Q4;<br>Alternatively, use more than one device to load model.|
### **GitHub contribution**: ### **GitHub contribution**:
Please add the **[SYCL]** prefix/tag in issues/PRs titles to help the SYCL-team check/address them without delay. Please add the `SYCL :` prefix/tag in issues/PRs titles to help the SYCL contributors to check/address them without delay.
## TODO ## TODO
- NA - Review ZES_ENABLE_SYSMAN: https://github.com/intel/compute-runtime/blob/master/programmers-guide/SYSMAN.md#support-and-limitations

3
docs/docker.md
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@ -22,6 +22,9 @@ Additionally, there the following images, similar to the above:
- `ghcr.io/ggml-org/llama.cpp:full-musa`: Same as `full` but compiled with MUSA support. (platforms: `linux/amd64`) - `ghcr.io/ggml-org/llama.cpp:full-musa`: Same as `full` but compiled with MUSA support. (platforms: `linux/amd64`)
- `ghcr.io/ggml-org/llama.cpp:light-musa`: Same as `light` but compiled with MUSA support. (platforms: `linux/amd64`) - `ghcr.io/ggml-org/llama.cpp:light-musa`: Same as `light` but compiled with MUSA support. (platforms: `linux/amd64`)
- `ghcr.io/ggml-org/llama.cpp:server-musa`: Same as `server` but compiled with MUSA support. (platforms: `linux/amd64`) - `ghcr.io/ggml-org/llama.cpp:server-musa`: Same as `server` but compiled with MUSA support. (platforms: `linux/amd64`)
- `ghcr.io/ggml-org/llama.cpp:full-intel`: Same as `full` but compiled with SYCL support. (platforms: `linux/amd64`)
- `ghcr.io/ggml-org/llama.cpp:light-intel`: Same as `light` but compiled with SYCL support. (platforms: `linux/amd64`)
- `ghcr.io/ggml-org/llama.cpp:server-intel`: Same as `server` but compiled with SYCL support. (platforms: `linux/amd64`)
The GPU enabled images are not currently tested by CI beyond being built. They are not built with any variation from the ones in the Dockerfiles defined in [.devops/](../.devops/) and the GitHub Action defined in [.github/workflows/docker.yml](../.github/workflows/docker.yml). If you need different settings (for example, a different CUDA, ROCm or MUSA library, you'll need to build the images locally for now). The GPU enabled images are not currently tested by CI beyond being built. They are not built with any variation from the ones in the Dockerfiles defined in [.devops/](../.devops/) and the GitHub Action defined in [.github/workflows/docker.yml](../.github/workflows/docker.yml). If you need different settings (for example, a different CUDA, ROCm or MUSA library, you'll need to build the images locally for now).

8
examples/sycl/run-llama2.sh
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@ -12,16 +12,16 @@ source /opt/intel/oneapi/setvars.sh
INPUT_PROMPT="Building a website can be done in 10 simple steps:\nStep 1:" INPUT_PROMPT="Building a website can be done in 10 simple steps:\nStep 1:"
MODEL_FILE=models/llama-2-7b.Q4_0.gguf MODEL_FILE=models/llama-2-7b.Q4_0.gguf
NGL=33 NGL=99
CONEXT=4096 CONTEXT=4096
if [ $# -gt 0 ]; then if [ $# -gt 0 ]; then
GGML_SYCL_DEVICE=$1 GGML_SYCL_DEVICE=$1
echo "use $GGML_SYCL_DEVICE as main GPU" echo "use $GGML_SYCL_DEVICE as main GPU"
#use signle GPU only #use signle GPU only
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -m ${MODEL_FILE} -p "${INPUT_PROMPT}" -n 400 -e -ngl ${NGL} -s 0 -c ${CONEXT} -mg $GGML_SYCL_DEVICE -sm none ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -m ${MODEL_FILE} -p "${INPUT_PROMPT}" -n 400 -e -ngl ${NGL} -s 0 -c ${CONTEXT} -mg $GGML_SYCL_DEVICE -sm none
else else
#use multiple GPUs with same max compute units #use multiple GPUs with same max compute units
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -m ${MODEL_FILE} -p "${INPUT_PROMPT}" -n 400 -e -ngl ${NGL} -s 0 -c ${CONEXT} ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -m ${MODEL_FILE} -p "${INPUT_PROMPT}" -n 400 -e -ngl ${NGL} -s 0 -c ${CONTEXT}
fi fi

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examples/sycl/run-llama3.sh Executable file
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@ -0,0 +1,28 @@
#!/bin/bash
# MIT license
# Copyright (C) 2025 Intel Corporation
# SPDX-License-Identifier: MIT
# If you want more control, DPC++ Allows selecting a specific device through the
# following environment variable
#export ONEAPI_DEVICE_SELECTOR="level_zero:0"
source /opt/intel/oneapi/setvars.sh
#export GGML_SYCL_DEBUG=1
#ZES_ENABLE_SYSMAN=1, Support to get free memory of GPU by sycl::aspect::ext_intel_free_memory. Recommended to use when --split-mode = layer.
INPUT_PROMPT="Building a website can be done in 10 simple steps:\nStep 1:"
MODEL_FILE=models/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf
NGL=99 # Layers offloaded to the GPU. If the device runs out of memory, reduce this value according to the model you are using.
CONTEXT=4096
if [ $# -gt 0 ]; then
GGML_SYCL_DEVICE=$1
echo "Using $GGML_SYCL_DEVICE as the main GPU"
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -m ${MODEL_FILE} -p "${INPUT_PROMPT}" -n 400 -e -ngl ${NGL} -c ${CONTEXT} -mg $GGML_SYCL_DEVICE -sm none
else
#use multiple GPUs with same max compute units
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -m ${MODEL_FILE} -p "${INPUT_PROMPT}" -n 400 -e -ngl ${NGL} -c ${CONTEXT}
fi

2
examples/sycl/win-run-llama2.bat
View File

@ -6,4 +6,4 @@ set INPUT2="Building a website can be done in 10 simple steps:\nStep 1:"
@call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 --force @call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 --force
.\build\bin\llama-cli.exe -m models\llama-2-7b.Q4_0.gguf -p %INPUT2% -n 400 -e -ngl 33 -s 0 .\build\bin\llama-cli.exe -m models\llama-2-7b.Q4_0.gguf -p %INPUT2% -n 400 -e -ngl 99 -s 0

9
examples/sycl/win-run-llama3.bat Normal file
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@ -0,0 +1,9 @@
:: MIT license
:: Copyright (C) 2024 Intel Corporation
:: SPDX-License-Identifier: MIT
set INPUT2="Building a website can be done in 10 simple steps:\nStep 1:"
@call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 --force
.\build\bin\llama-cli.exe -m models\Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf -p %INPUT2% -n 400 -e -ngl 99