* 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>
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llama.cpp for SYCL
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 (Commercial release Intel® DPC++ Compatibility Tool) 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
- Install Intel GPU driver.
a. Please install Intel GPU driver by official guide: Install GPU Drivers.
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]
- Install Intel® oneAPI Base toolkit.
a. Please follow the procedure in Get the Intel® oneAPI Base Toolkit .
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]
- 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
-
Put model file to folder models
-
Enable oneAPI running environment
source /opt/intel/oneapi/setvars.sh
- 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 |
- 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.
- Check the device ID in output
Like:
Using device **0** (Intel(R) Arc(TM) A770 Graphics) as main device
Windows
Setup Environment
- Install Intel GPU driver.
Please install Intel GPU driver by official guide: Install GPU Drivers.
- Install Intel® oneAPI Base toolkit.
a. Please follow the procedure in Get the Intel® oneAPI Base Toolkit .
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]
- 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
-
Put model file to folder models
-
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
- 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 |
- 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.
- 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. 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. 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.