Data Parallel Control

Data Parallel Control or dpctl is a Python library that allows users to control the execution placement of a compute kernel on an XPU.

The compute kernel can be a code:

written by the user, e.g., using numba-dpex
that is part of a library, such as oneMKL

The dpctl library is built upon the SYCL standard. It also implements Python bindings for a subset of the standard runtime classes that allow users to:

query platforms
discover and represent devices and sub-devices
construct contexts and queues

dpctl features classes for SYCL Unified Shared Memory (USM) management and implements a tensor array API.

The library helps authors of Python native extensions written in C, Cython, or pybind11 to access dpctl objects representing SYCL devices, queues, memory, and tensors.

Dpctl is the core part of a larger family of data-parallel Python libraries and tools to program on XPUs.

Installing

You can install the library with conda and pip. It is also available in the Intel(R) Distribution for Python (IDP).

Inte(R) oneAPI

You can find the most recent release of dpctl every quarter as part of the Intel(R) oneAPI releases.

To get the library from the latest oneAPI release, follow the instructions from Intel(R) oneAPI installation guide.

NOTE: You need to install the Intel(R) oneAPI Basekit to get IDP and dpctl.

Conda

To install dpctl from the Intel(R) channel on Anaconda cloud, use the following command:

conda install dpctl -c intel

PyPi

To install dpctl from PyPi, run the following command:

pip3 install dpctl

Installing the bleeding edge

To try out the current master, install it from our development channel on Anaconda cloud:

conda install dpctl -c dppy\label\dev

Building

Refer to our Documentation for more information on setting up a development environment and building dpctl from the source.

Running Examples

Find our examples here.

To run these examples, use:

for script in `ls examples/python/`;
    do echo "executing ${script}";
    python examples/python/${script};
done

Cython extensions

See examples of building Cython extensions with DPC++ compiler that interoperates with dpctl in the cython folder.

To build these examples, run:

CC=icx CXX=dpcpp python setup.py build_ext --inplace

To execute extensions, refer to the run.py script in each folder.

Running Tests

Tests are located here.

To run the tests, use:

pytest --pyargs dpctl

jjerphan/dpctl