# LibTileSpTRSV

**Repository Path**: ssslab/libtilesptrsv

## Basic Information

- **Project Name**: LibTileSpTRSV
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: AGPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-02-10
- **Last Updated**: 2026-02-25

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# TileSpTRSV-CMake-Library
**tilesptrsv** implements tiled algorithms for parallel SpTRSV on modern GPUs, and design an adaptive selection method that can automatically select the best formats and kernels according to input sparsity structures.

## Paper information
Zhengyang Lu, Weifeng Liu. "TileSpTRSV: a tiled algorithm for parallel sparse triangular solve on GPUs". CCF Transactions on High Performance Computing(CCF THPC). 2023.

## Installation
NVIDIA GPU with compute capability at least 3.5 (NVIDIA 4090 as tested) * NVIDIA nvcc CUDA compiler and CUDA Toolkit (CUDA v11.1 as tested). The GPU test programs have been tested on Ubuntu 18.04/20.04, and are expected to run correctly under other Linux distributions.

## Build as a library (CMake)
This project builds a library named **libtilesptrsv** and installs headers under `include/`.

1. Configure and build:
```
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build -j
```

2. (Optional) Install:
```
cmake --install build --prefix /your/prefix
```

### CMake options
- `TILESPTRSV_MAT_VAL_TYPE`: set `MAT_VAL_TYPE` (default: `double`). Example: `-DTILESPTRSV_MAT_VAL_TYPE=float`
- `CMAKE_CUDA_ARCHITECTURES`: set CUDA SMs (default: `61;80`). Example: `-DCMAKE_CUDA_ARCHITECTURES=80`

## Execution of tilesptrsv
Our test programs currently support input files encoded using the matrix market format. All matrix market datasets used in this evaluation are publicly available from the SuiteSparse Matrix Collection.
The legacy Makefile build for the test executable is preserved in the repository, but the recommended build system is CMake.