Implementation of RLS-based Adaptive Filterson nVIDIA GeForce Graphics Processing Unit
- Publisher: 電子情報通信学会 = The Institute of Electronics, Information and Communication Engineers
第26回信号処理シンポジウム講演論文集 = Proc. of 25th SIP Symposium,
acm: ComputingMethodologies_COMPUTERGRAPHICS | Software_PROGRAMMINGTECHNIQUES
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.