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SYCL Academy

Exercise 1: Compiling with SYCL

For this first exercise you simply need to install a SYCL implementation and the SYCL Academy dependencies and then verify your installation by comping a source file for SYCL.

1.) Installing a SYCL implementation

To install a SYCL implementation, follow the instructions in the README.md of the SYCL Academy repository.

2.) Verifying your environment

Depending on the SYCL implementation used, the steps to verify your environment might vary.

When using AdaptiveCpp

With AdaptiveCpp, you can skip this step. If you suspect later that your environment might not be set up correctly, you can run acpp-info -l in the bin directory of your AdaptiveCpp installation. It will then print the backends and devices that it sees, for example:

$ acpp-info -l
=================Backend information===================
Loaded backend 0: OpenCL
  Found device: Intel(R) UHD Graphics 620 [0x5917]
  Found device: ComputeAorta x86_64
  Found device: Intel(R) Core(TM) i7-8550U CPU @ 1.80GHz
Loaded backend 1: OpenMP
  Found device: hipSYCL OpenMP host device
Loaded backend 2: CUDA
  Found device: NVIDIA GeForce MX150
Loaded backend 3: Level Zero
  Found device: Intel(R) UHD Graphics 620 [0x5917]

3.) Configuring the exercise project

Once you have confirmed your environment is setup and available you are ready to compile your first SYCL application from source code.

First fetch the tutorial samples from GitHub.

Clone this repository ensuring that you include sub-modules.

git clone --recursive https://github.com/codeplaysoftware/syclacademy.git
mkdir build
cd build

4.) Include the SYCL header file

Then open the source file for this exercise and include the SYCL header file "sycl/sycl.hpp".

Make sure before you do this you define SYCL_LANGUAGE_VERSION to 2020, to enable support for the SYCL 2020 interface.

Once that is done build your source file with your chosen build system.

5.) Compile and run

Once you've done that simply build the exercise with your chosen build system and invoke the executable.

Build And Execution Hints

For DPC++: Using CMake to configure then build the exercise:

mkdir build
cd build
cmake .. "-GUnix Makefiles" -DSYCL_ACADEMY_USE_DPCPP=ON
  -DSYCL_ACADEMY_ENABLE_SOLUTIONS=OFF -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
make exercise_1

Alternatively from a terminal at the command line:

icpx -fsycl -o sycl-ex-1 -I../External/Catch2/single_include ../Code_Exercises/Exercise_01_compiling_with_sycl/source.cpp
./sycl-ex-1

In Intel DevCloud, to run computational applications, you will submit jobs to a queue for execution on compute nodes, especially some features like longer walltime and multi-node computation is only available through the job queue. Please refer to the guide.

So wrap the binary into a script job_submission and run:

qsub job_submission

For AdaptiveCpp:

# <target specification> is a list of backends and devices to target, for example
# "omp;generic" compiles for CPUs with the OpenMP backend and GPUs using the generic single-pass compiler.
# The simplest target specification is "omp" which compiles for CPUs using the OpenMP backend.
cmake -DSYCL_ACADEMY_USE_ADAPTIVECPP=ON -DSYCL_ACADEMY_INSTALL_ROOT=/insert/path/to/AdaptiveCpp -DACPP_TARGETS="<target specification>" ..
make exercise_1

alternatively, without CMake:

cd Code_Exercises/Exercise_01_compiling_with_SYCL
/path/to/AdaptiveCpp/bin/acpp -o sycl-ex-1 -I../../External/Catch2/single_include --acpp-targets="<target specification>" source.cpp
./sycl-ex-1