In this exercise you will learn how to create a data dependency data flow graph in both the buffer/accessor and USM models.
Using everything you have learned in previous exercises create an application using the buffer/accessor model which has four kernel functions. These kernel functions can do any computation you like, but they should follow the following dependencies.
(kernel A)
/ \
(kernel B) (kernel C)
\ /
(kernel D)
The important thing here is that kernels B and C must depend on kernel A, kernel
D must depend on kernels B and C and kernels B and C can be executed in any
order and even concurrently if the device permits. Note that in the
buffer/accessor these dependencies are created implicitly using the creation of
accessor
s.
Feel free to use any method of synchronization and copy back you like, but remember to handle errors.
Now do the same again but using the USM model. Note that in the USM model
dependencies are defined explicitly by chaining commands via event
s.
Again feel free to use any method of synchronization and copy back you like, but remember to handle errors.
For For DPC++ (using the Intel DevCloud):
clang++ -fsycl -o sycl-ex-10 -I../External/Catch2/single_include ../Code_Exercises/Exercise_10_Managing_Dependencies/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_10_managing_dependencies_source
./Code_Exercises/Exercise_10_Managing_Dependencies/exercise_10_managing_dependencies_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_10_managing_dependencies_source
./Code_Exercises/Exercise_10_Managing_Dependencies/exercise_10_managing_dependencies_source
alternatively, without cmake:
cd Code_Exercises/Exercise_10_Managing_Dependencies
/path/to/hipsycl/bin/syclcc -o sycl-ex-10 -I../../External/Catch2/single_include --hipsycl-targets="<target specification>" source.cpp
./sycl-ex-10