add support for compiling lambda constraints

Author: benvanwerkhoven

.gitignore

@@ -2,6 +2,8 @@
 poetry.lock
 noxenv.txt
 noxsettings.toml
+hyperparamtuning/
+*.prof
 
 ### Python ###
 *.pyc
@@ -16,6 +18,8 @@ push_to_pypi.sh
 .nfs*
 *.log
 *.json
+!kernel_tuner/schema/T1/1.0.0/input-schema.json
+!test/test_T1_input.json
 *.csv
 .cache
 *.ipynb_checkpoints

CHANGELOG.md

@@ -3,12 +3,17 @@ All notable changes to this project will be documented in this file.
 This project adheres to [Semantic Versioning](http://semver.org/).
 
 ## Unreleased
+<!-- ## [1.1.0] - 2025 ?? -->
+- Additional improvements to search space construction
+- changed HIP python bindings from pyhip-interface to the official hip-python
+- Added Python 3.13 and experimental 3.14 support
+- Dropped Python 3.8 and 3.9 support (due to incompatibility with newer scipy versions)
 
 ## [1.0.0] - 2024-04-04
 - HIP backend to support tuning HIP kernels on AMD GPUs
 - Experimental features for mixed-precision and accuracy tuning
 - Experimental features for OpenACC tuning
-- Major speedup due to new parser and using revamped python-constraint for searchspace building
+- Major speedup due to new parser and using revamped python-constraint for search space construction
 - Implemented ability to use `PySMT` and `ATF` for searchspace building
 - Added Poetry for dependency and build management
 - Switched from `setup.py` and `setup.cfg` to `pyproject.toml` for centralized metadata, added relevant tests

INSTALL.rst

@@ -20,7 +20,7 @@ Linux users could type the following to download and install Python 3 using Mini
     wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
     bash Miniconda3-latest-Linux-x86_64.sh
 
-You are of course also free to use your own Python installation, and the Kernel Tuner is developed to be fully compatible with Python 3.9 and newer.
+You are of course also free to use your own Python installation, and the Kernel Tuner is developed to be fully compatible with Python 3.10 and newer.
 
 Installing Python Packages
 --------------------------
@@ -124,31 +124,26 @@ Or you could install Kernel Tuner and PyOpenCL together if you haven't done so a
 
 If this fails, please see the PyOpenCL installation guide (https://wiki.tiker.net/PyOpenCL/Installation)
 
-HIP and PyHIP
--------------
+HIP and HIP Python
+------------------
 
-Before we can install PyHIP, you'll need to have the HIP runtime and compiler installed on your system.
+Before we can install HIP Python, you'll need to have the HIP runtime and compiler installed on your system.
 The HIP compiler is included as part of the ROCm software stack. Here is AMD's installation guide:
 
 * `ROCm Documentation: HIP Installation Guide <https://docs.amd.com/bundle/HIP-Installation-Guide-v5.3/page/Introduction_to_HIP_Installation_Guide.html>`__
 
-After you've installed HIP, you will need to install PyHIP. Run the following command in your terminal to install:
+After you've installed HIP, you will need to install HIP Python. Run the following command in your terminal to install:
 
-.. code-block:: bash
-
-    pip install pyhip-interface
+First identify the first three digits of the version number of your ROCm™ installation.
+Then install the HIP Python package(s) as follows:
 
-Alternatively, you can install PyHIP from the source code. First, clone the repository from GitHub:
-
-.. code-block:: bash
+.. code-block:: shell
 
-    git clone https://github.com/jatinx/PyHIP
-
-Then, navigate to the repository directory and run the following command to install:
-
-.. code-block:: bash
+    python3 -m pip install -i https://test.pypi.org/simple hip-python~=$rocm_version
+    # if you want to install the CUDA Python interoperability package too, run:
+    python3 -m pip install -i https://test.pypi.org/simple hip-python-as-cuda~=$rocm_version
 
-    python setup.py install
+For other installation options check `hip-python on GitHub <https://github.com/ROCm/hip-python>`_
 
 Installing the git version
 --------------------------
@@ -171,7 +166,7 @@ The runtime dependencies are:
 
 - `cuda`: install pycuda along with kernel_tuner
 - `opencl`: install pycuda along with kernel_tuner
-- `hip`: install pyhip along with kernel_tuner
+- `hip`: install HIP Python along with kernel_tuner
 - `tutorial`: install packages required to run the guides
 
 These can be installed by appending e.g. ``-E cuda -E opencl -E hip``.

README.md

@@ -32,7 +32,7 @@ What Kernel Tuner does:
 
 ## Installation
 
-- First, make sure you have your [CUDA](https://kerneltuner.github.io/kernel_tuner/stable/install.html#cuda-and-pycuda), [OpenCL](https://kerneltuner.github.io/kernel_tuner/stable/install.html#opencl-and-pyopencl), or [HIP](https://kerneltuner.github.io/kernel_tuner/stable/install.html#hip-and-pyhipl) compiler installed
+- First, make sure you have your [CUDA](https://kerneltuner.github.io/kernel_tuner/stable/install.html#cuda-and-pycuda), [OpenCL](https://kerneltuner.github.io/kernel_tuner/stable/install.html#opencl-and-pyopencl), or [HIP](https://kerneltuner.github.io/kernel_tuner/stable/install.html#hip-and-hip-python) compiler installed
 - Then type: `pip install kernel_tuner[cuda]`, `pip install kernel_tuner[opencl]`, or `pip install kernel_tuner[hip]`
 - or why not all of them: `pip install kernel_tuner[cuda,opencl,hip]`