support SYCL backend windows build (#5208)
* support SYCL backend windows build * add windows build in CI * add for win build CI * correct install oneMKL * fix install issue * fix ci * fix install cmd * fix install cmd * fix install cmd * fix install cmd * fix install cmd * fix win build * fix win build * fix win build * restore other CI part * restore as base * rm no new line * fix no new line issue, add -j * fix grammer issue * allow to trigger manually, fix format issue * fix format * add newline * fix format * fix format * fix format issuse --------- Co-authored-by: Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com>
This commit is contained in:
Neo Zhang Jianyu
GitHub
parent
e8dc55d006
commit
01684139c3
9 changed files with 281 additions and 14 deletions
426
README-sycl.md
Normal file
426
README-sycl.md
Normal file
|
|
@ -0,0 +1,426 @@
|
|||
# llama.cpp for SYCL
|
||||
|
||||
[Background](#background)
|
||||
|
||||
[OS](#os)
|
||||
|
||||
[Intel GPU](#intel-gpu)
|
||||
|
||||
[Linux](#linux)
|
||||
|
||||
[Windows](#windows)
|
||||
|
||||
[Environment Variable](#environment-variable)
|
||||
|
||||
[Known Issue](#known-issue)
|
||||
|
||||
[Q&A](#q&a)
|
||||
|
||||
[Todo](#todo)
|
||||
|
||||
## Background
|
||||
|
||||
SYCL is a higher-level programming model to improve programming productivity on various hardware accelerators—such as CPUs, GPUs, and FPGAs. It is a single-source embedded domain-specific language based on pure C++17.
|
||||
|
||||
oneAPI is a specification that is open and standards-based, supporting multiple architecture types including but not limited to GPU, CPU, and FPGA. The spec has both direct programming and API-based programming paradigms.
|
||||
|
||||
Intel uses the SYCL as direct programming language to support CPU, GPUs and FPGAs.
|
||||
|
||||
To avoid to re-invent the wheel, this code refer other code paths in llama.cpp (like OpenBLAS, cuBLAS, CLBlast). We use a open-source tool [SYCLomatic](https://github.com/oneapi-src/SYCLomatic) (Commercial release [Intel® DPC++ Compatibility Tool](https://www.intel.com/content/www/us/en/developer/tools/oneapi/dpc-compatibility-tool.html)) migrate to SYCL.
|
||||
|
||||
The llama.cpp for SYCL is used to support Intel GPUs.
|
||||
|
||||
For Intel CPU, recommend to use llama.cpp for X86 (Intel MKL building).
|
||||
|
||||
## OS
|
||||
|
||||
|OS|Status|Verified|
|
||||
|-|-|-|
|
||||
|Linux|Support|Ubuntu 22.04|
|
||||
|Windows|Support|Windows 11|
|
||||
|
||||
|
||||
## Intel GPU
|
||||
|
||||
|Intel GPU| Status | Verified Model|
|
||||
|-|-|-|
|
||||
|Intel Data Center Max Series| Support| Max 1550|
|
||||
|Intel Data Center Flex Series| Support| Flex 170|
|
||||
|Intel Arc Series| Support| Arc 770, 730M|
|
||||
|Intel built-in Arc GPU| Support| built-in Arc GPU in Meteor Lake|
|
||||
|Intel iGPU| Support| iGPU in i5-1250P, i7-1165G7|
|
||||
|
||||
|
||||
## Linux
|
||||
|
||||
### Setup Environment
|
||||
|
||||
1. Install Intel GPU driver.
|
||||
|
||||
a. Please install Intel GPU driver by official guide: [Install GPU Drivers](https://dgpu-docs.intel.com/driver/installation.html).
|
||||
|
||||
Note: for iGPU, please install the client GPU driver.
|
||||
|
||||
b. Add user to group: video, render.
|
||||
|
||||
```
|
||||
sudo usermod -aG render username
|
||||
sudo usermod -aG video username
|
||||
```
|
||||
|
||||
Note: re-login to enable it.
|
||||
|
||||
c. Check
|
||||
|
||||
```
|
||||
sudo apt install clinfo
|
||||
sudo clinfo -l
|
||||
```
|
||||
|
||||
Output (example):
|
||||
|
||||
```
|
||||
Platform #0: Intel(R) OpenCL Graphics
|
||||
`-- Device #0: Intel(R) Arc(TM) A770 Graphics
|
||||
|
||||
|
||||
Platform #0: Intel(R) OpenCL HD Graphics
|
||||
`-- Device #0: Intel(R) Iris(R) Xe Graphics [0x9a49]
|
||||
```
|
||||
|
||||
2. Install Intel® oneAPI Base toolkit.
|
||||
|
||||
|
||||
a. Please follow the procedure in [Get the Intel® oneAPI Base Toolkit ](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html).
|
||||
|
||||
Recommend to install to default folder: **/opt/intel/oneapi**.
|
||||
|
||||
Following guide use the default folder as example. If you use other folder, please modify the following guide info with your folder.
|
||||
|
||||
b. Check
|
||||
|
||||
```
|
||||
source /opt/intel/oneapi/setvars.sh
|
||||
|
||||
sycl-ls
|
||||
```
|
||||
|
||||
There should be one or more level-zero devices. Like **[ext_oneapi_level_zero:gpu:0]**.
|
||||
|
||||
Output (example):
|
||||
```
|
||||
[opencl:acc:0] Intel(R) FPGA Emulation Platform for OpenCL(TM), Intel(R) FPGA Emulation Device OpenCL 1.2 [2023.16.10.0.17_160000]
|
||||
[opencl:cpu:1] Intel(R) OpenCL, 13th Gen Intel(R) Core(TM) i7-13700K OpenCL 3.0 (Build 0) [2023.16.10.0.17_160000]
|
||||
[opencl:gpu:2] Intel(R) OpenCL Graphics, Intel(R) Arc(TM) A770 Graphics OpenCL 3.0 NEO [23.30.26918.50]
|
||||
[ext_oneapi_level_zero:gpu:0] Intel(R) Level-Zero, Intel(R) Arc(TM) A770 Graphics 1.3 [1.3.26918]
|
||||
|
||||
```
|
||||
|
||||
2. Build locally:
|
||||
|
||||
```
|
||||
mkdir -p build
|
||||
cd build
|
||||
source /opt/intel/oneapi/setvars.sh
|
||||
|
||||
#for FP16
|
||||
#cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON # faster for long-prompt inference
|
||||
|
||||
#for FP32
|
||||
cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
|
||||
|
||||
#build example/main only
|
||||
#cmake --build . --config Release --target main
|
||||
|
||||
#build all binary
|
||||
cmake --build . --config Release -v
|
||||
|
||||
cd ..
|
||||
```
|
||||
|
||||
or
|
||||
|
||||
```
|
||||
./examples/sycl/build.sh
|
||||
```
|
||||
|
||||
Note:
|
||||
|
||||
- By default, it will build for all binary files. It will take more time. To reduce the time, we recommend to build for **example/main** only.
|
||||
|
||||
### Run
|
||||
|
||||
1. Put model file to folder **models**
|
||||
|
||||
2. Enable oneAPI running environment
|
||||
|
||||
```
|
||||
source /opt/intel/oneapi/setvars.sh
|
||||
```
|
||||
|
||||
3. List device ID
|
||||
|
||||
Run without parameter:
|
||||
|
||||
```
|
||||
./build/bin/ls-sycl-device
|
||||
|
||||
or
|
||||
|
||||
./build/bin/main
|
||||
```
|
||||
|
||||
Check the ID in startup log, like:
|
||||
|
||||
```
|
||||
found 4 SYCL devices:
|
||||
Device 0: Intel(R) Arc(TM) A770 Graphics, compute capability 1.3,
|
||||
max compute_units 512, max work group size 1024, max sub group size 32, global mem size 16225243136
|
||||
Device 1: Intel(R) FPGA Emulation Device, compute capability 1.2,
|
||||
max compute_units 24, max work group size 67108864, max sub group size 64, global mem size 67065057280
|
||||
Device 2: 13th Gen Intel(R) Core(TM) i7-13700K, compute capability 3.0,
|
||||
max compute_units 24, max work group size 8192, max sub group size 64, global mem size 67065057280
|
||||
Device 3: Intel(R) Arc(TM) A770 Graphics, compute capability 3.0,
|
||||
max compute_units 512, max work group size 1024, max sub group size 32, global mem size 16225243136
|
||||
|
||||
```
|
||||
|
||||
|Attribute|Note|
|
||||
|-|-|
|
||||
|compute capability 1.3|Level-zero running time, recommended |
|
||||
|compute capability 3.0|OpenCL running time, slower than level-zero in most cases|
|
||||
|
||||
4. Set device ID and execute llama.cpp
|
||||
|
||||
Set device ID = 0 by **GGML_SYCL_DEVICE=0**
|
||||
|
||||
```
|
||||
GGML_SYCL_DEVICE=0 ./build/bin/main -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33
|
||||
```
|
||||
or run by script:
|
||||
|
||||
```
|
||||
./examples/sycl/run-llama2.sh
|
||||
```
|
||||
|
||||
Note:
|
||||
|
||||
- By default, mmap is used to read model file. In some cases, it leads to the hang issue. Recommend to use parameter **--no-mmap** to disable mmap() to skip this issue.
|
||||
|
||||
|
||||
5. Check the device ID in output
|
||||
|
||||
Like:
|
||||
```
|
||||
Using device **0** (Intel(R) Arc(TM) A770 Graphics) as main device
|
||||
```
|
||||
|
||||
## Windows
|
||||
|
||||
### Setup Environment
|
||||
|
||||
1. Install Intel GPU driver.
|
||||
|
||||
Please install Intel GPU driver by official guide: [Install GPU Drivers](https://www.intel.com/content/www/us/en/products/docs/discrete-gpus/arc/software/drivers.html).
|
||||
|
||||
2. Install Intel® oneAPI Base toolkit.
|
||||
|
||||
a. Please follow the procedure in [Get the Intel® oneAPI Base Toolkit ](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html).
|
||||
|
||||
Recommend to install to default folder: **/opt/intel/oneapi**.
|
||||
|
||||
Following guide uses the default folder as example. If you use other folder, please modify the following guide info with your folder.
|
||||
|
||||
b. Enable oneAPI running environment:
|
||||
|
||||
- In Search, input 'oneAPI'.
|
||||
|
||||
Search & open "Intel oneAPI command prompt for Intel 64 for Visual Studio 2022"
|
||||
|
||||
- In Run:
|
||||
|
||||
In CMD:
|
||||
```
|
||||
"C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64
|
||||
```
|
||||
|
||||
c. Check GPU
|
||||
|
||||
In oneAPI command line:
|
||||
|
||||
```
|
||||
sycl-ls
|
||||
```
|
||||
|
||||
There should be one or more level-zero devices. Like **[ext_oneapi_level_zero:gpu:0]**.
|
||||
|
||||
Output (example):
|
||||
```
|
||||
[opencl:acc:0] Intel(R) FPGA Emulation Platform for OpenCL(TM), Intel(R) FPGA Emulation Device OpenCL 1.2 [2023.16.10.0.17_160000]
|
||||
[opencl:cpu:1] Intel(R) OpenCL, 11th Gen Intel(R) Core(TM) i7-1185G7 @ 3.00GHz OpenCL 3.0 (Build 0) [2023.16.10.0.17_160000]
|
||||
[opencl:gpu:2] Intel(R) OpenCL Graphics, Intel(R) Iris(R) Xe Graphics OpenCL 3.0 NEO [31.0.101.5186]
|
||||
[ext_oneapi_level_zero:gpu:0] Intel(R) Level-Zero, Intel(R) Iris(R) Xe Graphics 1.3 [1.3.28044]
|
||||
|
||||
```
|
||||
|
||||
3. Install cmake & make
|
||||
|
||||
a. Download & install cmake for windows: https://cmake.org/download/
|
||||
|
||||
b. Download & install make for windows provided by mingw-w64: https://www.mingw-w64.org/downloads/
|
||||
|
||||
|
||||
### Build locally:
|
||||
|
||||
In oneAPI command line window:
|
||||
|
||||
```
|
||||
mkdir -p build
|
||||
cd build
|
||||
@call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 --force
|
||||
|
||||
:: for FP16
|
||||
:: faster for long-prompt inference
|
||||
:: cmake -G "MinGW Makefiles" .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release -DLLAMA_SYCL_F16=ON
|
||||
|
||||
:: for FP32
|
||||
cmake -G "MinGW Makefiles" .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release
|
||||
|
||||
|
||||
:: build example/main only
|
||||
:: make main
|
||||
|
||||
:: build all binary
|
||||
make -j
|
||||
cd ..
|
||||
```
|
||||
|
||||
or
|
||||
|
||||
```
|
||||
.\examples\sycl\win-build-sycl.bat
|
||||
```
|
||||
|
||||
Note:
|
||||
|
||||
- By default, it will build for all binary files. It will take more time. To reduce the time, we recommend to build for **example/main** only.
|
||||
|
||||
### Run
|
||||
|
||||
1. Put model file to folder **models**
|
||||
|
||||
2. Enable oneAPI running environment
|
||||
|
||||
- In Search, input 'oneAPI'.
|
||||
|
||||
Search & open "Intel oneAPI command prompt for Intel 64 for Visual Studio 2022"
|
||||
|
||||
- In Run:
|
||||
|
||||
In CMD:
|
||||
```
|
||||
"C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64
|
||||
```
|
||||
|
||||
3. List device ID
|
||||
|
||||
Run without parameter:
|
||||
|
||||
```
|
||||
build\bin\ls-sycl-device.exe
|
||||
|
||||
or
|
||||
|
||||
build\bin\main.exe
|
||||
```
|
||||
|
||||
Check the ID in startup log, like:
|
||||
|
||||
```
|
||||
found 4 SYCL devices:
|
||||
Device 0: Intel(R) Arc(TM) A770 Graphics, compute capability 1.3,
|
||||
max compute_units 512, max work group size 1024, max sub group size 32, global mem size 16225243136
|
||||
Device 1: Intel(R) FPGA Emulation Device, compute capability 1.2,
|
||||
max compute_units 24, max work group size 67108864, max sub group size 64, global mem size 67065057280
|
||||
Device 2: 13th Gen Intel(R) Core(TM) i7-13700K, compute capability 3.0,
|
||||
max compute_units 24, max work group size 8192, max sub group size 64, global mem size 67065057280
|
||||
Device 3: Intel(R) Arc(TM) A770 Graphics, compute capability 3.0,
|
||||
max compute_units 512, max work group size 1024, max sub group size 32, global mem size 16225243136
|
||||
|
||||
```
|
||||
|
||||
|Attribute|Note|
|
||||
|-|-|
|
||||
|compute capability 1.3|Level-zero running time, recommended |
|
||||
|compute capability 3.0|OpenCL running time, slower than level-zero in most cases|
|
||||
|
||||
4. Set device ID and execute llama.cpp
|
||||
|
||||
Set device ID = 0 by **set GGML_SYCL_DEVICE=0**
|
||||
|
||||
```
|
||||
set GGML_SYCL_DEVICE=0
|
||||
build\bin\main.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
|
||||
```
|
||||
or run by script:
|
||||
|
||||
```
|
||||
.\examples\sycl\win-run-llama2.bat
|
||||
```
|
||||
|
||||
Note:
|
||||
|
||||
- By default, mmap is used to read model file. In some cases, it leads to the hang issue. Recommend to use parameter **--no-mmap** to disable mmap() to skip this issue.
|
||||
|
||||
|
||||
5. Check the device ID in output
|
||||
|
||||
Like:
|
||||
```
|
||||
Using device **0** (Intel(R) Arc(TM) A770 Graphics) as main device
|
||||
```
|
||||
|
||||
## Environment Variable
|
||||
|
||||
#### Build
|
||||
|
||||
|Name|Value|Function|
|
||||
|-|-|-|
|
||||
|LLAMA_SYCL|ON (mandatory)|Enable build with SYCL code path. <br>For FP32/FP16, LLAMA_SYCL=ON is mandatory.|
|
||||
|LLAMA_SYCL_F16|ON (optional)|Enable FP16 build with SYCL code path. Faster for long-prompt inference. <br>For FP32, not set it.|
|
||||
|CMAKE_C_COMPILER|icx|Use icx compiler for SYCL code path|
|
||||
|CMAKE_CXX_COMPILER|icpx (Linux), icx (Windows)|use icpx/icx for SYCL code path|
|
||||
|
||||
#### Running
|
||||
|
||||
|
||||
|Name|Value|Function|
|
||||
|-|-|-|
|
||||
|GGML_SYCL_DEVICE|0 (default) or 1|Set the device id used. Check the device ids by default running output|
|
||||
|GGML_SYCL_DEBUG|0 (default) or 1|Enable log function by macro: GGML_SYCL_DEBUG|
|
||||
|
||||
## Known Issue
|
||||
|
||||
- Hang during startup
|
||||
|
||||
llama.cpp use mmap as default way to read model file and copy to GPU. In some system, memcpy will be abnormal and block.
|
||||
|
||||
Solution: add **--no-mmap**.
|
||||
|
||||
## Q&A
|
||||
|
||||
- Error: `error while loading shared libraries: libsycl.so.7: cannot open shared object file: No such file or directory`.
|
||||
|
||||
Miss to enable oneAPI running environment.
|
||||
|
||||
Install oneAPI base toolkit and enable it by: `source /opt/intel/oneapi/setvars.sh`.
|
||||
|
||||
- In Windows, no result, not error.
|
||||
|
||||
Miss to enable oneAPI running environment.
|
||||
|
||||
## Todo
|
||||
|
||||
- Support to build in Windows.
|
||||
|
||||
- Support multiple cards.
|
||||
Loading…
Add table
Add a link
Reference in a new issue