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update guide (#8909)

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@ -80,7 +80,14 @@ The following release is verified with good quality:
### Intel GPU ### Intel GPU
**Verified devices** SYCL backend supports Intel GPU Family:
- Intel Data Center Max Series
- Intel Flex Series, Arc Series
- Intel Built-in Arc GPU
- Intel iGPU in Core CPU (11th Generation Core CPU and newer, refer to [oneAPI supported GPU](https://www.intel.com/content/www/us/en/developer/articles/system-requirements/intel-oneapi-base-toolkit-system-requirements.html#inpage-nav-1-1)).
#### Verified devices
| Intel GPU | Status | Verified Model | | Intel GPU | Status | Verified Model |
|-------------------------------|---------|---------------------------------------| |-------------------------------|---------|---------------------------------------|
@ -88,7 +95,7 @@ The following release is verified with good quality:
| 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 |
| Intel built-in Arc GPU | Support | built-in Arc GPU in Meteor Lake | | Intel built-in Arc GPU | Support | built-in Arc GPU in Meteor Lake |
| Intel iGPU | Support | iGPU in i5-1250P, i7-1260P, i7-1165G7 | | Intel iGPU | Support | iGPU in 13700k, i5-1250P, i7-1260P, i7-1165G7 |
*Notes:* *Notes:*
@ -237,6 +244,13 @@ Similarly, user targeting Nvidia GPUs should expect at least one SYCL-CUDA devic
### II. Build llama.cpp ### II. Build llama.cpp
#### Intel GPU #### Intel GPU
```
./examples/sycl/build.sh
```
or
```sh ```sh
# Export relevant ENV variables # Export relevant ENV variables
source /opt/intel/oneapi/setvars.sh source /opt/intel/oneapi/setvars.sh
@ -276,23 +290,26 @@ cmake --build build --config Release -j -v
### III. Run the inference ### III. Run the inference
1. 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 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.
2. Enable oneAPI running environment ##### Check device
1. Enable oneAPI running environment
```sh ```sh
source /opt/intel/oneapi/setvars.sh source /opt/intel/oneapi/setvars.sh
``` ```
3. List devices information 2. List devices information
Similar to the native `sycl-ls`, available SYCL devices can be queried as follow: Similar to the native `sycl-ls`, available SYCL devices can be queried as follow:
```sh ```sh
./build/bin/llama-ls-sycl-device ./build/bin/llama-ls-sycl-device
``` ```
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:
@ -304,12 +321,37 @@ 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
4. Launch inference |Chosen Device ID|Setting|
|-|-|
|0|`export ONEAPI_DEVICE_SELECTOR="level_zero:1"` or no action|
|1|`export ONEAPI_DEVICE_SELECTOR="level_zero:1"`|
|0 & 1|`export ONEAPI_DEVICE_SELECTOR="level_zero:0;level_zero:1"`|
#### Execute
Choose one of following methods to run.
1. Script
- Use device 0:
```sh
./examples/sycl/run_llama2.sh 0
```
- Use multiple devices:
```sh
./examples/sycl/run_llama2.sh
```
2. Command line
Launch inference
There are two device selection modes: There are two device selection modes:
- Single device: Use one device target specified by the user. - Single device: Use one device assigned by user. Default device id is 0.
- Multiple devices: Automatically choose the devices with the same backend. - Multiple devices: Automatically choose the devices with the same backend.
In two device selection modes, the default SYCL backend is level_zero, you can choose other backend supported by SYCL by setting environment variable ONEAPI_DEVICE_SELECTOR. In two device selection modes, the default SYCL backend is level_zero, you can choose other backend supported by SYCL by setting environment variable ONEAPI_DEVICE_SELECTOR.
@ -326,11 +368,6 @@ Examples:
```sh ```sh
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -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 -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
``` ```
or run by script:
```sh
./examples/sycl/run_llama2.sh 0
```
- Use multiple devices: - Use multiple devices:
@ -338,12 +375,6 @@ or run by script:
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -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 -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
``` ```
Otherwise, you can run the script:
```sh
./examples/sycl/run_llama2.sh
```
*Notes:* *Notes:*
- Upon execution, verify the selected device(s) ID(s) in the output log, which can for instance be displayed as follow: - Upon execution, verify the selected device(s) ID(s) in the output log, which can for instance be displayed as follow:
@ -390,7 +421,7 @@ c. Verify installation
In the oneAPI command line, run the following to print the available SYCL devices: In the oneAPI command line, run the following to print the available SYCL devices:
``` ```
sycl-ls sycl-ls.exe
``` ```
There should be one or more *level-zero* GPU devices displayed as **[ext_oneapi_level_zero:gpu]**. Below is example of such output detecting an *intel Iris Xe* GPU as a Level-zero SYCL device: There should be one or more *level-zero* GPU devices displayed as **[ext_oneapi_level_zero:gpu]**. Below is example of such output detecting an *intel Iris Xe* GPU as a Level-zero SYCL device:
@ -411,6 +442,18 @@ b. The new Visual Studio will install Ninja as default. (If not, please install
### II. Build llama.cpp ### II. Build llama.cpp
You could download the release package for Windows directly, which including binary files and depended oneAPI dll files.
Choose one of following methods to build from source code.
1. Script
```sh
.\examples\sycl\win-build-sycl.bat
```
2. CMake
On the oneAPI command line window, step into the llama.cpp main directory and run the following: On the oneAPI command line window, step into the llama.cpp main directory and run the following:
``` ```
@ -425,12 +468,8 @@ cmake -B build -G "Ninja" -DGGML_SYCL=ON -DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPI
cmake --build build --config Release -j cmake --build build --config Release -j
``` ```
Otherwise, run the `win-build-sycl.bat` wrapper which encapsulates the former instructions:
```sh
.\examples\sycl\win-build-sycl.bat
```
Or, use CMake presets to build: Or, use CMake presets to build:
```sh ```sh
cmake --preset x64-windows-sycl-release cmake --preset x64-windows-sycl-release
cmake --build build-x64-windows-sycl-release -j --target llama-cli cmake --build build-x64-windows-sycl-release -j --target llama-cli
@ -442,7 +481,9 @@ cmake --preset x64-windows-sycl-debug
cmake --build build-x64-windows-sycl-debug -j --target llama-cli cmake --build build-x64-windows-sycl-debug -j --target llama-cli
``` ```
Or, you can use Visual Studio to open llama.cpp folder as a CMake project. Choose the sycl CMake presets (`x64-windows-sycl-release` or `x64-windows-sycl-debug`) before you compile the project. 3. Visual Studio
You can use Visual Studio to open llama.cpp folder as a CMake project. Choose the sycl CMake presets (`x64-windows-sycl-release` or `x64-windows-sycl-debug`) before you compile the project.
*Notes:* *Notes:*
@ -450,23 +491,25 @@ Or, you can use Visual Studio to open llama.cpp folder as a CMake project. Choos
### III. Run the inference ### III. Run the inference
1. Retrieve and prepare model #### Retrieve and prepare model
You can refer to the general [*Prepare and Quantize*](README#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 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.
2. Enable oneAPI running environment ##### Check device
1. Enable oneAPI running environment
On the oneAPI command line window, run the following and step into the llama.cpp directory: On the oneAPI command line window, run the following and step into the llama.cpp directory:
``` ```
"C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64
``` ```
3. List devices information 2. List devices information
Similar to the native `sycl-ls`, available SYCL devices can be queried as follow: Similar to the native `sycl-ls`, available SYCL devices can be queried as follow:
``` ```
build\bin\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:
@ -479,9 +522,27 @@ 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
|Chosen Device ID|Setting|
|-|-|
|0|`set ONEAPI_DEVICE_SELECTOR="level_zero:1"` or no action|
|1|`set ONEAPI_DEVICE_SELECTOR="level_zero:1"`|
|0 & 1|`set ONEAPI_DEVICE_SELECTOR="level_zero:0;level_zero:1"`|
4. Launch inference #### Execute
Choose one of following methods to run.
1. Script
```
examples\sycl\win-run-llama2.bat
```
2. Command line
Launch inference
There are two device selection modes: There are two device selection modes:
@ -508,11 +569,7 @@ build\bin\llama-cli.exe -m models\llama-2-7b.Q4_0.gguf -p "Building a website ca
``` ```
build\bin\llama-cli.exe -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 -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
``` ```
Otherwise, run the following wrapper script:
```
.\examples\sycl\win-run-llama2.bat
```
Note: Note:
@ -526,17 +583,18 @@ Or
use 1 SYCL GPUs: [0] with Max compute units:512 use 1 SYCL GPUs: [0] with Max compute units:512
``` ```
## Environment Variable ## Environment Variable
#### Build #### Build
| Name | Value | Function | | Name | Value | Function |
|--------------------|-----------------------------------|---------------------------------------------| |--------------------|-----------------------------------|---------------------------------------------|
| GGML_SYCL | ON (mandatory) | Enable build with SYCL code path. | | GGML_SYCL | ON (mandatory) | Enable build with SYCL code path.<br>FP32 path - recommended for better perforemance than FP16 on quantized model|
| GGML_SYCL_TARGET | INTEL *(default)* \| NVIDIA | Set the SYCL target device type. | | GGML_SYCL_TARGET | INTEL *(default)* \| NVIDIA | Set the SYCL target device type. |
| 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. |
| CMAKE_C_COMPILER | icx | 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. |
#### Runtime #### Runtime
@ -572,9 +630,18 @@ use 1 SYCL GPUs: [0] with Max compute units:512
``` ```
Otherwise, please double-check the GPU driver installation steps. Otherwise, please double-check the GPU driver installation steps.
- Can I report Ollama issue on Intel GPU to llama.cpp SYCL backend?
No. We can't support Ollama issue directly, because we aren't familiar with Ollama.
Sugguest reproducing on llama.cpp and report similar issue to llama.cpp. We will surpport it.
It's same for other projects including llama.cpp SYCL backend.
### **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-team check/address them without delay.
## TODO ## TODO
- Support row layer split for multiple card runs. - NA