FINUFFT

https://finufft.readthedocs.io/en/latest/
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FINUFFT is a library to compute efficiently the three most common types of nonuniform fast Fourier...
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### Basic FINUFFT Build, Test, and Install

Source: https://finufft.readthedocs.io/en/latest/_sources/install.rst.txt

A quick start guide for building FINUFFT from source, running tests, and installing it to a specified prefix. This process creates a static library by default.

```bash
git clone https://github.com/flatironinstitute/finufft.git
cd finufft
cmake -S . -B build -DFINUFFT_BUILD_TESTS=ON --install-prefix /path/to/install
cmake --build build --parallel
ctest --test-dir build
cmake --install build
```

--------------------------------

### Install FINUFFT with pip

Source: https://finufft.readthedocs.io/en/latest/python.html

Installs the latest precompiled binaries of FINUFFT from PyPI. This is the easiest way to get started.

```bash
pip install finufft

```

--------------------------------

### Build and Test cufinufft on GPU

Source: https://finufft.readthedocs.io/en/latest/devnotes.html

This script outlines the steps to set up a GPU environment, load necessary modules, build the cufinufft library with CUDA support, and run tests. It includes Python environment setup and installation.

```bash
srun -p gpu -C v100 -c 10 -n 1 --gpus=1 --pty bash
cd path/to/finufft

CUDAARCH=$(nvidia-smi --query-gpu=compute_cap --format=csv,noheader|head -n 1| sed 's/\.//')

module -q purge
module -q load gcc python cmake fftw cuda
python -m venv venv --system-site-packages
source venv/bin/activate
pip install --upgrade pip

mkdir -p build && cd build
cmake -DFINUFFT_BUILD_TESTS=on -DFINUFFT_BUILD_EXAMPLES=on -DFINUFFT_USE_CUDA=on \
    -DCMAKE_CUDA_ARCHITECTURES=$CUDAARCH -DCMAKE_BUILD_TYPE=RelWithDebInfo ..
make -j 10

ctest

LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$PWD pip install -e ../python/cufinufft

LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$PWD python -m pytest --framework=numba ../python/cufinufft

```

--------------------------------

### CMake Package Consumption Example

Source: https://finufft.readthedocs.io/en/latest/changelog.html

Demonstrates how to consume a FINUFFT installation using CMake's find_package. Ensures correct header inclusion and target resolution for consumers.

```cmake
find_package(finufft REQUIRED)

```

--------------------------------

### Build FINUFFT Examples

Source: https://finufft.readthedocs.io/en/latest/install.html

Compiles the example programs for FINUFFT. Does not require WSL or 64-bit gnu-make.

```bash
make examples

```

--------------------------------

### Install cufinufft with pip

Source: https://finufft.readthedocs.io/en/latest/python_gpu.html

Use this command to install the Python interface for cuFINUFFT. Ensure you have the necessary CUDA toolkit installed.

```bash
pip install cufinufft
```

--------------------------------

### Fortran Compilation with Dynamic Library

Source: https://finufft.readthedocs.io/en/latest/_sources/fortran.rst.txt

Example compilation command linking against the FINUFFT dynamic library. Uses rpath for easier execution from different directories. Replace $FINUFFT with the actual install path.

```bash
  gfortran -I../../include simple1d1.f -o simple1d1 -L../../lib -Wl,-rpath=$FINUFFT/lib -lfinufft
```

--------------------------------

### Install Language Interfaces on Ubuntu

Source: https://finufft.readthedocs.io/en/latest/install.html

Installs Fortran, Python, and Octave language interfaces using apt-get.

```bash
sudo apt-get gfortran python3 python3-pip octave liboctave-dev

```

--------------------------------

### Install Python Interface from Source

Source: https://finufft.readthedocs.io/en/latest/install_gpu.html

Install the Python interface of cuFINUFFT from its source directory after building the shared library.

```bash
pip install python/cufinufft

```

--------------------------------

### Install Xcode Command Line Tools

Source: https://finufft.readthedocs.io/en/latest/install.html

Installs essential command-line tools for development on macOS. Run this if you don't have Xcode installed.

```bash
xcode-select --install

```

--------------------------------

### Example Platform-Specific make.inc Files

Source: https://finufft.readthedocs.io/en/latest/install.html

These are examples of platform-specific make.inc files available in the make-platforms directory. Users can choose one as their make.inc for macOS or Windows.

```bash
make-platforms/make.inc.macosx_clang

```

```bash
make-platforms/make.inc.macosx_gcc-14

```

```bash
make-platforms/make.inc.windows_msys

```

--------------------------------

### Install cuFINUFFT Python Interface from Source

Source: https://finufft.readthedocs.io/en/latest/_sources/install_gpu.rst.txt

Install the Python interface for cuFINUFFT after building the shared library. Ensure a compatible GPU framework (CuPy, Numba, PyTorch, PyCuda) is installed separately.

```bash
pip install python/cufinufft
```

--------------------------------

### Build cuFINUFFT with Testing Enabled

Source: https://finufft.readthedocs.io/en/latest/_sources/install_gpu.rst.txt

Configure and build cuFINUFFT with testing enabled to verify the installation and functionality of the GPU library.

```bash
cmake -D FINUFFT_USE_CUDA=ON -D BUILD_TESTING=ON -D FINUFFT_BUILD_TESTS=ON ..
cmake --build . --parallel
```

--------------------------------

### Install Language Interfaces on Fedora/CentOS

Source: https://finufft.readthedocs.io/en/latest/install.html

Installs Fortran and Octave language interfaces using yum.

```bash
sudo yum install gcc-gfortran octave octave-devel

```

--------------------------------

### Linux Dependency Installation (Ubuntu)

Source: https://finufft.readthedocs.io/en/latest/_sources/install.rst.txt

Installs base dependencies including FFTW3 on Ubuntu systems using apt-get.

```bash
sudo apt-get install make build-essential libfftw3-dev
```

--------------------------------

### Install Base Dependencies on Fedora/CentOS

Source: https://finufft.readthedocs.io/en/latest/install.html

Installs essential build tools and the FFTW3 library on Fedora/CentOS systems using yum.

```bash
sudo yum install make gcc gcc-c++ fftw-devel libgomp

```

--------------------------------

### Install Octave and Compile Octave Interface

Source: https://finufft.readthedocs.io/en/latest/install.html

Installs Octave using Homebrew and compiles the Octave interface for FINUFFT. This also runs a self-test for the Octave interface.

```bash
brew install octave
make octave

```

--------------------------------

### Run FINUFFT Tests

Source: https://finufft.readthedocs.io/en/latest/install.html

Executes the test suite for FINUFFT to verify the installation. Requires WSL and 64-bit gnu-make.

```bash
make test

```

--------------------------------

### Install Python and FINUFFT (Python-only)

Source: https://finufft.readthedocs.io/en/latest/install.html

Installs Python 3 and the FINUFFT Python package using pip. Use this if you only need the Python interface.

```bash
brew install python3
pip3 install finufft

```

--------------------------------

### Build cuFINUFFT with CMake

Source: https://finufft.readthedocs.io/en/latest/_sources/install_gpu.rst.txt

Use this command to build the cuFINUFFT library with CUDA support. Ensure the Nvidia CUDA toolchain is installed.

```bash
mkdir build
cd build
cmake -D FINUFFT_USE_CUDA=ON ..
cmake --build . --parallel
```

--------------------------------

### Install FINUFFT Python module from source

Source: https://finufft.readthedocs.io/en/latest/_sources/install.rst.txt

Compile and install the FINUFFT Python module locally to achieve better performance by exploiting CPU capabilities. This uses the modern pyproject.toml build system.

```shell
pip install python/finufft
```

--------------------------------

### Clone and Compile FINUFFT for PowerPC

Source: https://finufft.readthedocs.io/en/latest/install.html

Clone the FINUFFT repository, copy a platform-specific make.inc file, and compile the library. This is an example for a PowerPC architecture.

```bash
git clone https://github.com/flatironinstitute/finufft.git
cd finufft
cp make-platforms/make.inc.powerpc make.inc
make test -j

```

--------------------------------

### Fortran Example File List

Source: https://finufft.readthedocs.io/en/latest/fortran.html

Lists the available Fortran demo files for NUFFT transforms, categorized by dimension and interface type. Includes notes on precision and modifications from CMCL codes.

```text
simple1d1.f        - 1D type 1, simple interface, default and various opts
guru1d1.f          - 1D type 1, guru interface, default and various opts
guru1d1_adjoint.f  - adjoint of 1D type 1, guru interface, default opts
guru1d2_adjoint.f  - adjoint of 1D type 2, guru interface, default and various opts
nufft1d_demo.f     - 1D types 1,2,3, minimally changed from CMCL demo codes
nufft2d_demo.f     - 2D "
nufft3d_demo.f     - 3D "
nufft2dmany_demo.f - 2D types 1,2,3, vectorized (many strengths) interface
simple1d1.f90      - modern Fortran90 version of simple1d1 using module
```

--------------------------------

### GNU Make Build for PowerPC

Source: https://finufft.readthedocs.io/en/latest/_sources/install.rst.txt

Illustrates the classic GNU Make build process. Clone the repository, copy the appropriate platform-specific make.inc file, and then run 'make test'.

```bash
git clone https://github.com/flatironinstitute/finufft.git
cd finufft
cp make-platforms/make.inc.powerpc make.inc
make test -j
```

--------------------------------

### Linking FINUFFT Shared Library (Linux/macOS)

Source: https://finufft.readthedocs.io/en/latest/_sources/install.rst.txt

Example of linking the FINUFFT shared library to a C++ executable. Adjust include and library paths based on your installation prefix. The '-Wl,-rpath' flag is crucial for shared library loading.

```bash
g++ -o simple1d1 ../examples/simple1d1.cpp -I$HOME/local/include -L$HOME/local/lib64 -Wl,-rpath $HOME/local/lib64 -lfinufft -O2
```

--------------------------------

### Compile FINUFFT from source

Source: https://finufft.readthedocs.io/en/latest/python.html

Installs FINUFFT by compiling from source, using the --no-binary option. This allows for custom compilation flags like -march=native for potential performance improvements.

```bash
pip install --no-binary finufft finufft

```

--------------------------------

### Install Python and FINUFFT on macOS

Source: https://finufft.readthedocs.io/en/latest/_sources/install.rst.txt

Install Python 3 and the finufft Python package using pip on macOS. This is a simplified installation for Python-only users.

```bash
brew install python3
pip3 install finufft
```

--------------------------------

### Link to Installed FINUFFT Package

Source: https://finufft.readthedocs.io/en/latest/_sources/install.rst.txt

Consume an already installed FINUFFT package by finding it with find_package and linking it to your executable. Ensure CMake can locate the installation prefix.

```cmake
find_package(finufft REQUIRED)
target_link_libraries(your_executable [PUBLIC|PRIVATE|INTERFACE] finufft::finufft)
```

--------------------------------

### Install Homebrew and Dependencies on macOS

Source: https://finufft.readthedocs.io/en/latest/_sources/install.rst.txt

Install Homebrew package manager and essential libraries like libomp and fftw on macOS. This command assumes Homebrew is already installed.

```bash
brew install libomp fftw
```

--------------------------------

### Interactive GPU Shell Setup and Finufft Build

Source: https://finufft.readthedocs.io/en/latest/_sources/devnotes.rst.txt

This snippet outlines the steps to acquire an interactive GPU shell, load necessary modules, build a Python virtual environment, and compile Finufft with CUDA support. It includes setting up build configurations and running standard tests.

```sh
# to grab an interactive GPU shell -- here with 10 cores for building and a v100 for
# testing. You could just as easily try this on your workstation
srun -p gpu -C v100 -c 10 -n 1 --gpus=1 --pty bash
cd path/to/finufft

# get the local card to this machine's compute capability. If you know it you can obviously type it yourself
CUDAARCH=$(nvidia-smi --query-gpu=compute_cap --format=csv,noheader|head -n 1| sed 's/\.//')

# Load modules and build a venv. We typically recommend using venvs that fall back our our
# default packages with the python module (--system-site-packages)
module -q purge
module -q load gcc python cmake fftw cuda
python -m venv venv --system-site-packages
source venv/bin/activate
pip install --upgrade pip

# building. Feel free to tweak whatever
mkdir -p build && cd build
cmake -DFINUFFT_BUILD_TESTS=on -DFINUFFT_BUILD_EXAMPLES=on -DFINUFFT_USE_CUDA=on \
    -DCMAKE_CUDA_ARCHITECTURES=$CUDAARCH -DCMAKE_BUILD_TYPE=RelWithDebInfo ..
make -j 10

# for standard tests
ctest

# python install. Needs build from before since installer searches for libcufinufft.so in
# LD_LIBRARY_PATH (and default path)
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$PWD pip install -e ../python/cufinufft

# python tests. we have other GPU framework support, but you need to make sure they're
# installed (numba, pycuda, torch, cupy). This LD_LIBRARY_PATH may or may not be necessary,
# depending on if an RPATHing issue appears. Fix upstream at time of writing
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$PWD python -m pytest --framework=numba ../python/cufinufft
```

--------------------------------

### Set Points and Execute cuFINUFFT Plan

Source: https://finufft.readthedocs.io/en/latest/c_gpu.html

Configure the plan with the input points and then execute the plan to compute the NUDFT. The results are stored in d_f.

```c
cufinufftf_setpts(plan, M, d_x, NULL, NULL, 0, NULL, NULL, NULL);

cufinufftf_execute(plan, d_c, d_f);

```

--------------------------------

### Install Homebrew Dependencies

Source: https://finufft.readthedocs.io/en/latest/install.html

Installs OpenMP and FFTW libraries using Homebrew. These are common dependencies for scientific computing.

```bash
brew install libomp fftw

```

--------------------------------

### Initialize CUFINUFFT Options Structure

Source: https://finufft.readthedocs.io/en/latest/c_gpu.html

This snippet shows how to initialize the options structure for GPU computations. You must create this structure and then pass its address to the plan creation functions.

```c
cufinufft_opts opts;
cufinufft_default_opts(&opts);

```

--------------------------------

### Create and Execute a FINUFFT Plan

Source: https://finufft.readthedocs.io/en/latest/python.html

This snippet demonstrates how to initialize a FINUFFT plan for a type 1 transform, set non-uniform points, and execute the transform on source strengths. Ensure NumPy and FINUFFT are imported.

```python
import numpy as np
import finufft

# set up parameters
n_modes = (1000, 2000)
n_pts = 100000
nufft_type = 1
n_trans = 4

# generate nonuniform points
x = 2 * np.pi * np.random.uniform(size=n_pts)
y = 2 * np.pi * np.random.uniform(size=n_pts)

# generate source strengths
c = (np.random.standard_normal(size=(n_trans, n_pts))
     + 1J * np.random.standard_normal(size=(n_trans, n_pts)))

# initialize the plan
plan = finufft.Plan(nufft_type, n_modes, n_trans)

# set the nonuniform points
plan.setpts(x, y)

# execute the plan
f = plan.execute(c)

```

--------------------------------

### C++ Finufft Plan Creation with Options

Source: https://finufft.readthedocs.io/en/latest/changelog.html

Demonstrates the C++/C interface for Finufft where 'opts' is passed as a pointer, a change from previous versions where it was passed by reference.

```cpp
// C++/C interface
struct nufft_opts opts;
// ... initialize opts ...
finufft_plan plan = finufft_makeplan(..., &opts, ...);
```

--------------------------------

### Build and test FINUFFT with MSYS/MinGW on Windows

Source: https://finufft.readthedocs.io/en/latest/_sources/install.rst.txt

For users on Windows with MSYS and MinGW compilers, copy the appropriate make.inc file and then run the build and test commands. This setup is for local compilation.

```shell
cp make-platforms/make.inc.windows_msys make.inc
make test -j
```

--------------------------------

### cuFINUFFT C API Overview

Source: https://finufft.readthedocs.io/en/latest/_sources/c_gpu.rst.txt

This section outlines the general workflow and available functions for using the cuFINUFFT C interface. It covers the steps for creating, executing, and destroying plans, along with notes on precision and version compatibility.

```APIDOC
## cuFINUFFT C API

This API closely matches the plan interface to FINUFFT and is modeled after FFTW and NFFT.
It offers both double (`cufinufft`) and single (`cufinufftf`) precision versions.

### Workflow

1.  **Make a plan**: `cufinufftf_makeplan` or `cufinufft_makeplan`
2.  **Set nonuniform points**: `cufinufftf_setpts` or `cufinufft_setpts`
3.  **Execute transform**: `cufinufftf_execute` or `cufinufft_execute`
4.  **Destroy plan**: `cufinufftf_destroy` or `cufinufft_destroy`

### Functions

*   `cufinufftf_makeplan(int type, int dim, int *nmodes, int sign, int ntrans, REAL eps, cufinufftf_plan *plan, void *options)`
*   `cufinufftf_setpts(cufinufftf_plan plan, int M, REAL *x, int xstd, REAL *y, int ystd, REAL *z, int zstd)`
*   `cufinufftf_execute(cufinufftf_plan plan, void *c, void *f)`
*   `cufinufftf_destroy(cufinufftf_plan plan)`

(Double precision versions use `cufinufft_` prefix and `DOUBLE` type for `REAL`.)

### Example Usage (Single Precision)

```c
#include <cufinufft.h>
#include <stdlib.h>
#include <stdio.h>
#include <math.h>
#include <complex.h>
#include <cuComplex.h>

int main() {
    const int M = 100000, N = 10000;
    int64_t modes[1] = {N};

    float *x;
    float _Complex *c, *f;
    float *d_x;
    cuFloatComplex *d_c, *d_f;
    cufinufftf_plan plan;

    // Allocate host arrays
    x = (float *) malloc(M * sizeof(float));
    c = (float _Complex *) malloc(M * sizeof(float _Complex));
    f = (float _Complex *) malloc(N * sizeof(float _Complex));

    // Fill host arrays with data
    srand(0);
    for(int j = 0; j < M; ++j) {
        x[j] = 2 * M_PI * (((float) rand()) / RAND_MAX - 1);
        c[j] = (2 * ((float) rand()) / RAND_MAX - 1) + I * (2 * ((float) rand()) / RAND_MAX - 1);
    }

    // Allocate device arrays and copy data
    cudaMalloc(&d_x, M * sizeof(float));
    cudaMalloc(&d_c, M * sizeof(float _Complex));
    cudaMalloc(&d_f, N * sizeof(float _Complex));
    cudaMemcpy(d_x, x, M * sizeof(float), cudaMemcpyHostToDevice);
    cudaMemcpy(d_c, c, M * sizeof(float _Complex), cudaMemcpyHostToDevice);

    // Create plan
    cufinufftf_makeplan(1, 1, modes, 1, 1, 1e-6, &plan, NULL);

    // Set points and execute transform (example)
    // cufinufftf_setpts(plan, M, d_x, 0, NULL, 0, NULL, 0);
    // cufinufftf_execute(plan, d_c, d_f);

    // Destroy plan
    // cufinufftf_destroy(plan);

    // Free host memory
    free(x);
    free(c);
    free(f);

    // Free device memory (omitted for brevity)

    return 0;
}
```
```

--------------------------------

### Install CuPy for CUDA 11.x

Source: https://finufft.readthedocs.io/en/latest/install_gpu.html

Install the CuPy library, a dependency for the Python interface, specifically for CUDA 11.x versions.

```bash
pip install cupy-cuda11x

```

--------------------------------

### Install CuPy for CUDA 11.x

Source: https://finufft.readthedocs.io/en/latest/_sources/install_gpu.rst.txt

Install the CuPy library, a dependency for the cuFINUFFT Python interface, specifying the CUDA version.

```bash
pip install cupy-cuda11x
```

--------------------------------

### Linux Dependency Installation (Fedora/CentOS)

Source: https://finufft.readthedocs.io/en/latest/_sources/install.rst.txt

Installs base dependencies including FFTW3 and OpenMP support on Fedora/CentOS systems using yum.

```bash
sudo yum install make gcc gcc-c++ fftw-devel libgomp
```

--------------------------------

### Configure cuFINUFFT with GPU and Testing Enabled

Source: https://finufft.readthedocs.io/en/latest/install_gpu.html

Use this CMake command to configure the build with CUDA support and enable testing flags.

```bash
cmake -D FINUFFT_USE_CUDA=ON -D BUILD_TESTING=ON -D FINUFFT_BUILD_TESTS=ON ..

```

--------------------------------

### Install FINUFFT Python requirements

Source: https://finufft.readthedocs.io/en/latest/_sources/install.rst.txt

Install the necessary Python packages listed in the requirements.txt file for FINUFFT. This should be done after activating a virtual environment.

```shell
pip install -r python/requirements.txt
```
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