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Section: New Software and Platforms
Boost.SIMD
Functional Description
Boost.SIMD provides a portable way to vectorize computation on Altivec, SSE or AVX while providing a generic way to extend the set of supported functions and hardwares.
New Results
- Parallel light speed labeling: the world’s fastest connected component labeling for multicore processors
- Opening Polyhedral Compiler's Black Box
- Automating Resource Selection and Configuration in Inter-clouds through a Software Product Line Method
- A Randomized LU-based Solver Using GPU and Intel Xeon Phi Accelerators
- Metaprogramming dense linear algebra solvers. Applications to multi and many-core architectures
- Using Random Butterfly Transformations in Parallel Schur Complement-Based Preconditioning
- LU Preconditioning for Overdetermined Sparse Least Squares Problems
- Dense Symmetric Indefinite Factorization on GPU Accelerated Architectures
- Computing least squares condition numbers on hybrid multicore/GPU systems
- Towards a High-Performance Tensor Algebra Package for Accelerators
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Bibliography