Skip to content

Latest commit

 

History

History
140 lines (105 loc) · 4.71 KB

File metadata and controls

140 lines (105 loc) · 4.71 KB

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]

If you're using DevCloud via SSH

If you have not already installed SYCLAcademy, follow this guide to perform the installation.

Go to the Compiling_with_SYCL directory: From the syclacademy directory

cd build/Code_Exercises/Compiling_with_SYCL

and continue to 4

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

If you are using DevCloud via SSH:

If you haven't done so already, follow this guide to build the exercise directory structure.

From the syclacademy directory

cd build/Code_Exercises/Compiling_with_SYCL
and execute:
* ```make Compiling_with_SYCL_source```   - to build source.cpp
* ```make Compiling_with_SYCL_solution``` - to build the solution provided
* ```make``` - to build both

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][devcloud-job-submission].

So wrap the binary into a script `job_submission`

#!/bin/bash ./Compiling_with_SYCL_source

and run:
```sh
qsub -l nodes=1:gpu:ppn=2 -d . job_submission

The stdout will be stored in job_submission.o<job id> and stderr in job_submission.e<job id>.

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 Compiling_with_SYCL_source

Alternatively from a terminal at the command line:

icpx -fsycl -o Compiling_with_SYCL_source -I../External/Catch2/single_include ../Code_Exercises/Compiling_with_SYCL/source.cpp
./Compiling_with_SYCL_source

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 Compiling_with_SYCL_source

alternatively, without CMake:

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