Abstract: Equipped with 512-bit wide SIMD instructions and large numbers of computing cores, the emerging x86-based Intel^® Many Integrated Core (MIC) Architecture provides not only high floating-point performance, but also substantial off-chip memory bandwidth. The 3D FFT (three-dimensional fast Fourier transform) is a widely-studied algorithm; however, the conventional algorithm needs to traverse the data array three times. In each pass, it computes multiple 1D FFTs along one of three dimensions, giving rise to plenty of non-unit strided memory accesses. In this paper, we propose a two-pass 3D FFT algorithm, which mainly aims to reduce the amount of explicit data transfer between the memory and the on-chip cache. The main idea is to split one dimension into two sub-dimensions, and then combine the transform along each sub-dimension with one of the rest dimensions respectively. The difference in amount of TLB misses resulting from decomposition along different dimensions is analyzed in detail. Multi-level parallelism is leveraged on the many-core system for a high degree of parallelism and better data reuse of local cache. On top of this, a number of optimization techniques, such as memory padding, loop transformation and vectorization, are employed in our implementation to further enhance the performance. We evaluate the algorithm on the Intel^® Xeon Phi^TM coprocessor 7110P, and achieve a maximum performance of 136 Gflops with 240 threads in o2oad mode, which beats the vendor-specific Intel^® MKL library by a factor of up to 2.22X.