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CUDA is great for big dense matrices, which is incredibly important. But there is a lot more to scientific computing than big dense matrices. Also, CUDA is low
by krastanov 4y ago
CUDA is great for big dense matrices, which is incredibly important. But there is a lot more to scientific computing than big dense matrices.
Also, CUDA is low-level a library by one vendor for one class of hardware. Not a language. Languages serious about scientific computing already have multiple interfaces for CUDA at various level of abstraction.
- plegresl 4y agoThere is a Fortran version of CUDA: https://developer.nvidia.com/cuda-fortran https://developer.nvidia.com/cuda-fortran
- amelius 4y agoThere is cuSparse for sparse matrices: https://docs.nvidia.com/cuda/cusparse/ https://docs.nvidia.com/cuda/cusparse/
- pjmlp 4y agoOne of the reasons why CUDA won over OpenCL is because it is polyglot.
- anlunx 4y agoWhat are some example workloads in scientific computing that are not suitable for CUDA?
- ChrisRackauckas 4y agoAnything that's not linear algebra
- adgjlsfhk1 4y agosolving small and medium sized differential equations, most monte-carlo algorithms