Numerical Computations with GPUs
This book brings together research on numerical methods adapted for Graphics Processing Units (GPUs). It explains recent efforts to adapt classic numerical methods, including solution of linear equations and FFT, for massively parallel GPU architectures. This volume consolidates recent research and...
| Συγγραφή απο Οργανισμό/Αρχή: | |
|---|---|
| Άλλοι συγγραφείς: | |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2014.
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Accelerating Numerical Dense Linear Algebra Calculations with GPUs
- A Guide to Implement Tridiagonal Solvers on GPUs
- Batch Matrix Exponentiation
- Efficient Batch LU and QR Decomposition on GPU
- A Flexible CUDA LU-Based Solver for Small, Batched Linear Systems
- Sparse Matrix-Vector Product
- Solving Ordinary Differential Equations on GPUs
- GPU-based integration of large numbers of independent ODE systems
- Finite and spectral element methods on unstructured grids for flow and wave propagation problems
- A GPU implementation for solving the Convection Diffusion equation using the Local Modified SOR method
- Pseudorandom numbers generation for Monte Carlo simulations on GPUs: Open CL approach
- Monte Carlo Automatic Integration with Dynamic Parallelism in CUDA
- GPU-Accelerated computation routines for quantum trajectories method
- Monte Carlo Simulation of Dynamic Systems on GPUs
- Fast Fourier Transform (FFT) on GPUs
- A Highly Efficient FFT Using Shared-Memory Multiplexing
- Increasing parallelism and reducing thread contentions in mapping localized N-body simulations to GPUs.
