NVIDIA cuDSS
NVIDIA cuDSS (Preview) is an optimized, first-generation GPU-accelerated Direct Sparse Solver library for solving linear systems with very sparse matrices. Direct Sparse Solvers are an important part of numerical computing for real-time applications like autonomous driving and process simulation, where increasing complexity and high throughput demands a robust direct solver.
Key Features
GPU-accelerated Solver
Capitalizing on the CPUâs sequential computing and the GPUâs parallel computing, cuDSS leverages both the CPU and GPU to solve sparse matrices with only a few non-zero elements per row. The result is significantly higher performance than CPU-only solvers .
Core Functionality Support
cuDSS solves sparse linear systems on single-GPU, multi-GPU, and multi-node platforms, including support for refactorization in cases with multiple systems, and different reorderings and types of matrices. cuDSS is also built to be stable, regardless of matrix size. Â
Optimized for NVIDIA GPUs
cuDSS supports all NVIDIA GPUs, Pascal and newer, allowing you to integrate direct sparse solvers across a variety of NVIDIA-powered platforms. cuDSS also benefits from the Grace Hopper Superchip architecture.
cuDSS Performance
Resources
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