GPU module

Detailed Description

GPU-accelerated dense linear algebra using NVIDIA CUDA libraries (cuSOLVER and cuBLAS).

This module provides explicit GPU solver classes that coexist with Eigen's CPU solvers. Unlike the LAPACKE dispatch (which replaces the CPU implementation globally), GPU classes are separate types the user instantiates by choice:

#define EIGEN_USE_GPU
#include <contrib/Eigen/GPU>
 
// CPU path (unchanged)
Eigen::LLT<Eigen::MatrixXd> llt_cpu(A);
 
// GPU path (explicit)
Eigen::gpu::LLT<double> llt_gpu(A);   // L stays on device
auto X = llt_gpu.solve(B);            // only B transferred per solve

Requires CUDA 11.4+.

Classes
class	Eigen::gpu::Context
	Unified GPU execution context owning a CUDA stream and library handles. More...
class	Eigen::gpu::DeviceMatrix< Scalar_ >
	RAII wrapper for a dense column-major matrix in GPU device memory. More...
class	Eigen::gpu::HostTransfer< Scalar_ >
	Future for an asynchronous device-to-host matrix transfer. More...
class	Eigen::gpu::LLT< Scalar_, UpLo_ >
	GPU Cholesky (LL^T) decomposition via cuSOLVER. More...
class	Eigen::gpu::LU< Scalar_ >
	GPU LU decomposition with partial pivoting via cuSOLVER. More...