mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-09-23 13:36:20 +00:00
01684139c3
* 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>
427 lines
11 KiB
Markdown
427 lines
11 KiB
Markdown
# llama.cpp for SYCL
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[Background](#background)
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[OS](#os)
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[Intel GPU](#intel-gpu)
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[Linux](#linux)
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[Windows](#windows)
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[Environment Variable](#environment-variable)
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[Known Issue](#known-issue)
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[Q&A](#q&a)
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[Todo](#todo)
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## Background
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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.
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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.
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Intel uses the SYCL as direct programming language to support CPU, GPUs and FPGAs.
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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.
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The llama.cpp for SYCL is used to support Intel GPUs.
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For Intel CPU, recommend to use llama.cpp for X86 (Intel MKL building).
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## OS
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|OS|Status|Verified|
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|Linux|Support|Ubuntu 22.04|
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|Windows|Support|Windows 11|
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## Intel GPU
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|Intel GPU| Status | Verified Model|
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|-|-|-|
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|Intel Data Center Max Series| Support| Max 1550|
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|Intel Data Center Flex Series| Support| Flex 170|
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|Intel Arc Series| Support| Arc 770, 730M|
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|Intel built-in Arc GPU| Support| built-in Arc GPU in Meteor Lake|
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|Intel iGPU| Support| iGPU in i5-1250P, i7-1165G7|
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## Linux
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### Setup Environment
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1. Install Intel GPU driver.
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a. Please install Intel GPU driver by official guide: [Install GPU Drivers](https://dgpu-docs.intel.com/driver/installation.html).
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Note: for iGPU, please install the client GPU driver.
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b. Add user to group: video, render.
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```
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sudo usermod -aG render username
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sudo usermod -aG video username
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```
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Note: re-login to enable it.
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c. Check
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```
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sudo apt install clinfo
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sudo clinfo -l
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```
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Output (example):
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```
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Platform #0: Intel(R) OpenCL Graphics
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`-- Device #0: Intel(R) Arc(TM) A770 Graphics
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Platform #0: Intel(R) OpenCL HD Graphics
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`-- Device #0: Intel(R) Iris(R) Xe Graphics [0x9a49]
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```
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2. Install Intel® oneAPI Base toolkit.
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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).
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Recommend to install to default folder: **/opt/intel/oneapi**.
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Following guide use the default folder as example. If you use other folder, please modify the following guide info with your folder.
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b. Check
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```
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source /opt/intel/oneapi/setvars.sh
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sycl-ls
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```
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There should be one or more level-zero devices. Like **[ext_oneapi_level_zero:gpu:0]**.
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Output (example):
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```
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[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]
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[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]
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[opencl:gpu:2] Intel(R) OpenCL Graphics, Intel(R) Arc(TM) A770 Graphics OpenCL 3.0 NEO [23.30.26918.50]
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[ext_oneapi_level_zero:gpu:0] Intel(R) Level-Zero, Intel(R) Arc(TM) A770 Graphics 1.3 [1.3.26918]
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```
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2. Build locally:
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```
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mkdir -p build
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cd build
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source /opt/intel/oneapi/setvars.sh
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#for FP16
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#cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON # faster for long-prompt inference
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#for FP32
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cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
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#build example/main only
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#cmake --build . --config Release --target main
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#build all binary
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cmake --build . --config Release -v
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cd ..
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```
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or
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```
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./examples/sycl/build.sh
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```
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Note:
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- 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.
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### Run
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1. Put model file to folder **models**
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2. Enable oneAPI running environment
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```
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source /opt/intel/oneapi/setvars.sh
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```
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3. List device ID
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Run without parameter:
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```
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./build/bin/ls-sycl-device
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or
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./build/bin/main
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```
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Check the ID in startup log, like:
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```
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found 4 SYCL devices:
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Device 0: Intel(R) Arc(TM) A770 Graphics, compute capability 1.3,
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max compute_units 512, max work group size 1024, max sub group size 32, global mem size 16225243136
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Device 1: Intel(R) FPGA Emulation Device, compute capability 1.2,
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max compute_units 24, max work group size 67108864, max sub group size 64, global mem size 67065057280
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Device 2: 13th Gen Intel(R) Core(TM) i7-13700K, compute capability 3.0,
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max compute_units 24, max work group size 8192, max sub group size 64, global mem size 67065057280
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Device 3: Intel(R) Arc(TM) A770 Graphics, compute capability 3.0,
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max compute_units 512, max work group size 1024, max sub group size 32, global mem size 16225243136
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```
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|Attribute|Note|
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|compute capability 1.3|Level-zero running time, recommended |
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|compute capability 3.0|OpenCL running time, slower than level-zero in most cases|
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4. Set device ID and execute llama.cpp
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Set device ID = 0 by **GGML_SYCL_DEVICE=0**
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```
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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
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```
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or run by script:
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```
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./examples/sycl/run-llama2.sh
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```
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Note:
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- 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.
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5. Check the device ID in output
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Like:
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```
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Using device **0** (Intel(R) Arc(TM) A770 Graphics) as main device
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```
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## Windows
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### Setup Environment
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1. Install Intel GPU driver.
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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).
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2. Install Intel® oneAPI Base toolkit.
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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).
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Recommend to install to default folder: **/opt/intel/oneapi**.
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Following guide uses the default folder as example. If you use other folder, please modify the following guide info with your folder.
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b. Enable oneAPI running environment:
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- In Search, input 'oneAPI'.
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Search & open "Intel oneAPI command prompt for Intel 64 for Visual Studio 2022"
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- In Run:
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In CMD:
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```
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"C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64
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```
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c. Check GPU
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In oneAPI command line:
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```
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sycl-ls
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```
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There should be one or more level-zero devices. Like **[ext_oneapi_level_zero:gpu:0]**.
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Output (example):
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```
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[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]
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[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]
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[opencl:gpu:2] Intel(R) OpenCL Graphics, Intel(R) Iris(R) Xe Graphics OpenCL 3.0 NEO [31.0.101.5186]
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[ext_oneapi_level_zero:gpu:0] Intel(R) Level-Zero, Intel(R) Iris(R) Xe Graphics 1.3 [1.3.28044]
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```
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3. Install cmake & make
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a. Download & install cmake for windows: https://cmake.org/download/
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b. Download & install make for windows provided by mingw-w64: https://www.mingw-w64.org/downloads/
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### Build locally:
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In oneAPI command line window:
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```
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mkdir -p build
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cd build
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@call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 --force
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:: for FP16
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:: faster for long-prompt inference
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:: cmake -G "MinGW Makefiles" .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release -DLLAMA_SYCL_F16=ON
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:: for FP32
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cmake -G "MinGW Makefiles" .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release
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:: build example/main only
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:: make main
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:: build all binary
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make -j
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cd ..
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```
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or
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```
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.\examples\sycl\win-build-sycl.bat
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```
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Note:
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- 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.
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### Run
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1. Put model file to folder **models**
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2. Enable oneAPI running environment
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- In Search, input 'oneAPI'.
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Search & open "Intel oneAPI command prompt for Intel 64 for Visual Studio 2022"
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- In Run:
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In CMD:
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```
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"C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64
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```
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3. List device ID
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Run without parameter:
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```
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build\bin\ls-sycl-device.exe
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or
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build\bin\main.exe
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```
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Check the ID in startup log, like:
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```
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found 4 SYCL devices:
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Device 0: Intel(R) Arc(TM) A770 Graphics, compute capability 1.3,
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max compute_units 512, max work group size 1024, max sub group size 32, global mem size 16225243136
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Device 1: Intel(R) FPGA Emulation Device, compute capability 1.2,
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max compute_units 24, max work group size 67108864, max sub group size 64, global mem size 67065057280
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Device 2: 13th Gen Intel(R) Core(TM) i7-13700K, compute capability 3.0,
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max compute_units 24, max work group size 8192, max sub group size 64, global mem size 67065057280
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Device 3: Intel(R) Arc(TM) A770 Graphics, compute capability 3.0,
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max compute_units 512, max work group size 1024, max sub group size 32, global mem size 16225243136
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```
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|Attribute|Note|
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|-|-|
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|compute capability 1.3|Level-zero running time, recommended |
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|compute capability 3.0|OpenCL running time, slower than level-zero in most cases|
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4. Set device ID and execute llama.cpp
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Set device ID = 0 by **set GGML_SYCL_DEVICE=0**
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```
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set GGML_SYCL_DEVICE=0
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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
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```
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or run by script:
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```
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.\examples\sycl\win-run-llama2.bat
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```
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Note:
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- 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.
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5. Check the device ID in output
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Like:
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```
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Using device **0** (Intel(R) Arc(TM) A770 Graphics) as main device
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```
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## Environment Variable
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#### Build
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|Name|Value|Function|
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|LLAMA_SYCL|ON (mandatory)|Enable build with SYCL code path. <br>For FP32/FP16, LLAMA_SYCL=ON is mandatory.|
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|LLAMA_SYCL_F16|ON (optional)|Enable FP16 build with SYCL code path. Faster for long-prompt inference. <br>For FP32, not set it.|
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|CMAKE_C_COMPILER|icx|Use icx compiler for SYCL code path|
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|CMAKE_CXX_COMPILER|icpx (Linux), icx (Windows)|use icpx/icx for SYCL code path|
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#### Running
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|Name|Value|Function|
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|GGML_SYCL_DEVICE|0 (default) or 1|Set the device id used. Check the device ids by default running output|
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|GGML_SYCL_DEBUG|0 (default) or 1|Enable log function by macro: GGML_SYCL_DEBUG|
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## Known Issue
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- Hang during startup
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llama.cpp use mmap as default way to read model file and copy to GPU. In some system, memcpy will be abnormal and block.
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Solution: add **--no-mmap**.
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## Q&A
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- Error: `error while loading shared libraries: libsycl.so.7: cannot open shared object file: No such file or directory`.
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Miss to enable oneAPI running environment.
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Install oneAPI base toolkit and enable it by: `source /opt/intel/oneapi/setvars.sh`.
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- In Windows, no result, not error.
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Miss to enable oneAPI running environment.
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## Todo
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- Support to build in Windows.
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- Support multiple cards.
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