My setup for SYCL development on linux. I have a minimal setup to play around and work on SYCL.
What is SYCL?
- SYCL is basically cross platform framework that enables parallel programming same code to run on different gpus and cpus. It isn’t used much but it is helpful in learning about parallel programming and gpu programming. In case you only have Intel integrated gpus this can be a good alternative.
How I installed it?
- There are a couple of ways to install and run sycl one is adaptivecpp which I haven’t used the other is Intel One Api Toolkit You can download a script that when I executed I got compiler and other stuff installed in home directory I added source env_var to ~/.bashrc to make my system simpler.
source ~/intel/oneapi/setvars.shI haven’t used modules but I have setup my cmake to enable modules as well this is my minimal cmake setup
cmake_minimum_required(VERSION 4.3.2)
set(CMAKE_EXPERIMENTAL_CXX_IMPORT_STD "451f2fe2-a8a2-47c3-bc32-94786d8fc91b")
project(one_api)
project(one_api LANGUAGES CXX)
set(CMAKE_CXX_MODULE_STD ON)
SET(BOOST_UT_CXX_MODULES ON)
set(CMAKE_CXX_STANDARD 26)
set(CMAKE_BUILD_WITH_INSTALL_RPATH TRUE)
add_executable(my_program main.cpp)
target_compile_features(my_program PRIVATE cxx_std_26)
target_compile_options(my_program PRIVATE -fsycl -Wno-reserved-module-identifier)
target_link_options(my_program PRIVATE -fsycl -Wno-reserved-module-identifier)
#target_sources(my_program PUBLIC FILE_SET all_my_modules TYPE CXX_MODULES FILES)A note on code
Just to test my setup i have this code to find number of cores in gpu and cpu, it uses c++20 onwards.
#include<print>
#include<sycl/sycl.hpp>
int main() {
const sycl::device dev{sycl::gpu_selector_v};
const sycl::device host{sycl::cpu_selector_v};
auto dev_cores = dev.get_info<sycl::info::device::max_compute_units>();
auto host_cores = host.get_info<sycl::info::device::max_compute_units>();
std::println("gpu cores {}", dev_cores);
std::println("cpu cores {}", host_cores);
}