![]() ![]() While using the cuBLAS API to write a tiled BLAS implementation (which achieves even higher performance) is straightforward, a GPU BLAS library which implemented and managed such tiling in a near optimal way would certainly facilitate access to the computing power of the GPU. In these cases it would be useful to have an API which managed the data transfer to and from the GPU automatically and could be used as a direct replacement for CPU BLAS libraries.Īdditionally, there is the common case where the input matrices to the BLAS operations are too large to fit on the GPU. But it is less convenient when just a few BLAS routines need to be accelerated (simple data copy) or when vast amounts of code need to be modified (large programmer effort). Such an API permits the fine tuning required to minimize redundant data copies to and from the GPU in arbitrarily complicated scenarios such that maximum performance is achieved. all relevant data needs to be copied to preallocated GPU memory, followed by deallocation after the computation.a cuBLAS handle needs to be initialized.a CUDA context first needs to be created. ![]() However, cuBLAS can not be used as a direct BLAS replacement for applications originally intended to run on the CPU. CuBLAS is an implementation of the BLAS library that leverages the teraflops of performance provided by NVIDIA GPUs.
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