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| An Efficient Implementation of Double Precision 1-D FFT for GPUs Using CUDA |
| Yanjun Liu, Licai Guo, Bin Luo, Xingyi Zhang |
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Abstract Fast Fourier Transform (FFT) is a well known and widely used tool in
many scientific and engineering fields. CUFFT, which is the NVIDIA's
FFT library included in the CUDA toolkit, supports double precision
FFTs. However, the implementation of CUFFT is not very efficient.
In this paper, we implement an efficient double-precision
Cooley-tukey algorithm for GPUs using CUDA. Some programming
techniques are employed to exploit the hardware characteristics.
These techniques include on-chip shared memory utilization, removing
redundant computation, and coalescing the global memory access.
Experiments show that the performance of our 1-D FFT is as fast as
CUFFT. Furthermore, the performance of our FFT implementation is more
than twice faster than CUFFT for small input sizes.
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