Skip to content

Latest commit

 

History

History
160 lines (111 loc) · 5.1 KB

README.md

File metadata and controls

160 lines (111 loc) · 5.1 KB
Raw

SYCL Academy

Exercise 5: Device Selection

In this exercise you will learn how to create a device selector that will choose a device for you to enqueue work to.

1.) Query the device of your queue

When you default construct a queue the runtime will use the default_selector to choose a device.

Try querying the device associated with the queue and information about it.

Remember the device associated with a queue can be retrieved using the get_device member function and information about a device can be queried using the get_info member function template.

2.) Try other device selectors

Replace the default selector with one of the other standard device selectors that are provided by SYCL such as the cpu_selector, gpu_selector or host_selector and see which device those choose.

3.) Create your own device selector

Create a device selector using the template below, implementing the function call operator, using various device and platform info queries like the one we used earlier to query the device name and then use that device selector in the queue constructor:

class my_device_selector : public device_selector {
 public:
  my_device_selector() {}

  virtual int operator()(const device &device) const { /* scoring logic */ }
};

Remember the platform associated with a device can be retrieved using the get_platform member function.

Remember that the value returned from the device selector's function call operator will represent the score for each device, and a device with a negative score will never be chosen.

SYCL Academy

Exercise 1: Compiling with SYCL

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

1.) Installing ComputeCpp

To install ComputeCpp follow the instructions in the README.md of the SYCL Academy repository for installing ComputeCpp and the necessary OpenCL drivers.

2.) Verifying your environment

ComputeCpp includes a tool called computecpp_info which lists all the devices available on your machine and displays which are setup with the correct drivers.

Open a console and run the executable located in the 'bin' directory of the ComputeCpp release package:

./computecpp_info

Look for the lines that say:

  Device is supported                     : YES - Tested internally by Codeplay
  Software Ltd.

You can also add the option --verbose to display further information about the devices.

From this output you can confirm your environment is setup correctly.

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

4.) Include the SYCL header file

Then open the source file for this exercise and include the SYCL header file "CL/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 For DPC++ (using the Intel DevCloud):

clang++ -fsycl -o sycl-ex-5 -I../External/Catch2/single_include ../Code_Exercises/Exercise_05_Device_Selection/source.cpp

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 abvailable through the job queue. Please refer to the guide.

So wrap the binary into a script job_submission and run:

qsub job_submission

For ComputeCpp:

cmake -DSYCL_ACADEMY_USE_COMPUTECPP=ON -DSYCL_ACADEMY_INSTALL_ROOT=/insert/path/to/computecpp ..
make exercise_05_device_selection_source
./Code_Exercises/Exercise_05_Device_Selection/exercise_04_handling_errors source

For hipSYCL:

# <target specification> is a list of backends and devices to target, for example
# "omp;hip:gfx900,gfx906" compiles for CPUs with the OpenMP backend and for AMD Vega 10 (gfx900) and Vega 20 (gfx906) GPUs using the HIP backend.
# The simplest target specification is "omp" which compiles for CPUs using the OpenMP backend.
cmake -DSYCL_ACADEMY_USE_HIPSYCL=ON -DSYCL_ACADEMY_INSTALL_ROOT=/insert/path/to/hipsycl -DHIPSYCL_TARGETS="<target specification>" ..
make exercise_05_device_selection_source
./Code_Exercises/Exercise_05_Device_Selection/exercise_05_device_selection_source

alternatively, without cmake:

cd Code_Exercises/Exercise_05_Device_Selection
/path/to/hipsycl/bin/syclcc -o sycl-ex-5 -I../../External/Catch2/single_include --hipsycl-targets="<target specification>" source.cpp
./sycl-ex-5