電子情報通信学会 = The Institute of Electronics, Information and Communication Engineers
抄録
This paper presents efficient implementa- tion of RLS-based adaptive filters with a large number of taps on nVIDIA GeForce graphics processing unit (GPU) and CUDA software development environment. Modification of the order and the combination of calcu- lations reduces the number of accesses to slow off-chip memory. Assigning tasks into multiple threads also takes memory access order into account. For a 4096-tap case, a GPU program is almost three times faster than a CPU program.
Implementation of RLS-based Adaptive Filterson nVIDIA GeForce Graphics Processing Unit
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