This project provides a Python interface to a DPC++ implementation of Generalized Minimal RESidual (GMRES) algorithm for solving sparse linear systems. The implementation is optimized for parallel execution on GPUs and multicore CPUs.

The Python interface has an optional parameter target_device that controls whether GMRES runs on CPU or GPU, as follows:

• target_device = "DEFAULT": Selects the most performant device (chosen by sycl::default_selector_v)
• target_device = "CPU": Selects the CPU
• target_device = "GPU": Selects the most performant, compatible GPU

The DPC++ documentation here covers most of the system requirements.

Other miscellaneous requirements are listed below.

• Operating system: Windows 10/11
• Python version: 3+ (see setup.py for package dependencies)
• Eigen and Pybind11 (included as git submodules).
• To run the example problem in gmres_examples.dp.cpp, HDF5 must be installed in the location specified in CMakelists.txt.
• Device compatibility: The current CMake build configuration targets Intel CPUs and GPUs.
• Running GMRESpy requires that sycl7.dll is in the PATH variable of the environment. This should already be the case for the Intel OneAPI command prompt. Otherwise, sycl7.dll can be found in the OneAPI installation directory, e.g. C:\Program Files (x86)\Intel\oneAPI\2024.0\bin.

In addition to the other requirements, building / installing requires CMake 3.23.0+ and Ninja.

To build directly without Python, run the following from the Intel OneAPI command prompt:

git clone https://github.com/caleb399/GMRESpy.git
cd GMRESpy
mkdir build & cd build
CMake -GNinja ..
ninja all

This will build the Python module dependency gmres_dpcpp.pyd and an executable dpcpp_gmres.exe containing an example problem.

To install the Python module, it is recommended to use a virtual environment. First open the OneAPI command prompt, and enter:

python -m venv GMRESpy
.\GMRESpy\Scripts\activate.bat

Then, run the following:

git clone https://github.com/caleb399/GMRESpy.git
cd GMRESPy\GMRESpy
pip install .
cd ..

Before using GMRESpy, be sure to delete the original GMRESpy directory or navigate to a different directory. This ensures that Python will correctly load the GMRESpy package from installed site-packages directory.

See src\examples\gmres_benchmarks.py for example usage.

• Solution of a 524288 x 524288 sparse linear system (test_data\test1.h5)
• Number of nonzeros: 3667968
• GMRES parameters: restart = 80, rtol = 1e-5
• For the scipy benchmarks, OMP_NUM_THREADS was set to either 4 or 8, depending on which one gave the fastest time.

Note: This project is in an early stage of development. Features and documentation may be incomplete or subject to change.

To-do list (in no particular order):

• Add pybind11 interface for double precision types (already present in the DPC++ code)
• Add support for additional sparse matrix formats.
• Add build options for targeting NVIDIA and AMD GPUs.
• Improve error handling on the DPC++ side.