llama.cpp/README_sycl.md

llama.cpp for SYCL

Background

OS

Intel GPU

Linux

Environment Variable

Known Issue

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 (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	Ongoing

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
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.

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 .

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

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

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	use icpx 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

• 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.

• 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.

Todo

• Support to build in Windows.

• Support multiple cards.