In this paper, we propose a fast algorithm for computing the Discrete Generalized Fourier Transforms on parallel dodecahedron domains with 3 dimensions and 4 directions. Our fast algorithm (HFFT) reduces the computati...In this paper, we propose a fast algorithm for computing the Discrete Generalized Fourier Transforms on parallel dodecahedron domains with 3 dimensions and 4 directions. Our fast algorithm (HFFT) reduces the computation complexity of DGFT from O(N^6) to O(N^3log N). A parallel implementation is given and it has been run on a Linux Cluster up to 32 CPUs.展开更多
Equipped with 512-bit wide SIMD inst d large numbers of computing cores, the emerging x86-based Intel（R） Many Integrated Core （MIC） Architecture ot only high floating-point performance, but also substantial ...Equipped with 512-bit wide SIMD inst d large numbers of computing cores, the emerging x86-based Intel（R） Many Integrated Core （MIC） Architecture ot only high floating-point performance, but also substantial off-chip memory bandwidth. The 3D FFT （three-di fast Fourier transform） is a widely-studied algorithm; however, the conventional algorithm needs to traverse the three times. In each pass, it computes multiple 1D FFTs along one of three dimensions, giving rise to plenty of rided memory accesses. In this paper, we propose a two-pass 3D FFT algorithm, which mainly aims to reduce of explicit data transfer between the memory and the on-chip cache. The main idea is to split one dimension into ensions, and then combine the transform along each sub-dimension with one of the rest dimensions respectively erence in amount of TLB misses resulting from decomposition along different dimensions is analyzed in detail. el parallelism is leveraged on the many-core system for a high degree of parallelism and better data reuse of loc On top of this, a number of optimization techniques, such as memory padding, loop transformation and vectoriz employed in our implementation to further enhance the performance. We evaluate the algorithm on the Intel（R） PhiTM coprocessor 7110P, and achieve a maximum performance of 136 Gflops with 240 threads in offload mode, which ts the vendor-specific Intel（R）MKL library by a factor of up to 2.22X.展开更多
文摘In this paper, we propose a fast algorithm for computing the Discrete Generalized Fourier Transforms on parallel dodecahedron domains with 3 dimensions and 4 directions. Our fast algorithm (HFFT) reduces the computation complexity of DGFT from O(N^6) to O(N^3log N). A parallel implementation is given and it has been run on a Linux Cluster up to 32 CPUs.
基金supported by the National Natural Science Foundation of China under Grant Nos.61133005,61272136,61221062,61402441,61432018the National High Technology Research and Development 863 Program of China under Grant No.2012AA010903the Chinese Academy of Sciences Special Grant for Postgraduate Research,Innovation and Practice under Grant No.11000GBF01
文摘Equipped with 512-bit wide SIMD inst d large numbers of computing cores, the emerging x86-based Intel（R） Many Integrated Core （MIC） Architecture ot only high floating-point performance, but also substantial off-chip memory bandwidth. The 3D FFT （three-di fast Fourier transform） is a widely-studied algorithm; however, the conventional algorithm needs to traverse the three times. In each pass, it computes multiple 1D FFTs along one of three dimensions, giving rise to plenty of rided memory accesses. In this paper, we propose a two-pass 3D FFT algorithm, which mainly aims to reduce of explicit data transfer between the memory and the on-chip cache. The main idea is to split one dimension into ensions, and then combine the transform along each sub-dimension with one of the rest dimensions respectively erence in amount of TLB misses resulting from decomposition along different dimensions is analyzed in detail. el parallelism is leveraged on the many-core system for a high degree of parallelism and better data reuse of loc On top of this, a number of optimization techniques, such as memory padding, loop transformation and vectoriz employed in our implementation to further enhance the performance. We evaluate the algorithm on the Intel（R） PhiTM coprocessor 7110P, and achieve a maximum performance of 136 Gflops with 240 threads in offload mode, which ts the vendor-specific Intel（R）MKL library by a factor of up to 2.22X.
