In this exercise you will learn how to use different techniques for synchronizing commands and data.
Take a look at the vector add applications using the buffer/accessor model in
exercise 6 and the USM model in exercise 8, and familiarize yourself with how
they call wait
on returned event
s to synchronize the completion of the work.
With those same applications convert them to call wait
on the queue
to
synchronize instead.
Take a look at the vector add application using the buffer/accessor mode in
exercise 6 and how it synchronizes on the destruction of the buffer
s.
Take a look that two applications again and familiarize yourself with how the result of the computation is copied back to the host.
In the case of the application using the buffer/accessor model note how this
occurs implicitly on the destruction of the buffer
.
In the case of the application using the USM model note how this occurs
explicitly by calling memcpy
.
Finally with the application which is using the buffer/accessor model introduce
a host accessor
by calling get_host_access
on the buffer
. The host
accessor
can be used to check the result of the computation on the host while
the buffer
is still alive.
Remember to do this within a scope to ensure the host accessor
is destroyed.
Also note that creating a host accessor
may copy the data back to the original
pointer provided to the buffer
but this is not guaranteed.
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_9
Alternatively from a terminal at the command line:
icpx -fsycl -o sycl-ex-9 -I../External/Catch2/single_include ../Code_Exercises/Exercise_09_Synchronization/source.cpp
./sycl-ex-9
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_9
alternatively, without CMake:
cd Code_Exercises/Exercise_09_Synchronization
/path/to/adaptivecpp/bin/acpp -o sycl-ex-9 -I../../External/Catch2/single_include --acpp-targets="<target specification>" source.cpp
./sycl-ex-9