首页> 外文会议>Field-Programmable Custom Computing Machines (FCCM), 2012 IEEE 20th Annual International Symposium on >Memory Bandwidth Efficient Two-Dimensional Fast Fourier Transform Algorithm and Implementation for Large Problem Sizes
【24h】

Memory Bandwidth Efficient Two-Dimensional Fast Fourier Transform Algorithm and Implementation for Large Problem Sizes

机译:内存带宽有效的二维快速傅立叶变换算法及大问题规模的实现

获取原文
获取原文并翻译 | 示例

摘要

Prevailing VLSI trends point to a growing gap between the scaling of on-chip processing throughput and off-chip memory bandwidth. An efficient use of memory bandwidth must become a first-class design consideration in order to fully utilize the processing capability of highly concurrent processing platforms like FPGAs. In this paper, we present key aspects of this challenge in developing FPGA-based implementations of two-dimensional fast Fourier transform (2D-FFT) where the large datasets must reside off-chip in DRAM. Our scalable implementations address the memory bandwidth bottleneck through both (1) algorithm design to enable efficient DRAM access patterns and (2) data path design to extract the maximum compute throughput for a given level of memory bandwidth. We present results for double-precision 2D-FFT up to size 2,048-by-2,048. On an Alter a DE4 platform our implementation of the 2,048-by-2,048 2D-FFT can achieve over 19.2 Gflop/s from the 12 GByte/s maximum DRAM bandwidth available. The results also show that our FPGA-based implementations of 2D-FFT are more efficient than 2D-FFT running on state-of-the-art CPUs and GPUs in terms of the bandwidth and power efficiency.
机译:流行的VLSI趋势表明,片上处理吞吐量的缩放比例与片外存储器带宽之间的差距越来越大。为了充分利用高度并行的处理平台(如FPGA)的处理能力,必须有效地利用存储器带宽。在本文中,我们在开发基于FPGA的二维快速傅里叶变换(2D-FFT)的实现中提出了这一挑战的关键方面,在该实现中,大型数据集必须位于片外DRAM中。我们的可扩展实现通过以下两种方法解决了内存带宽瓶颈:(1)算法设计以实现有效的DRAM访问模式,以及(2)数据路径设计以针对给定级别的内存带宽提取最大的计算吞吐量。我们提出了大小为2,048 x 2048的双精度2D-FFT的结果。在Alter DE4平台上,我们实现的2,048×2,048 2D-FFT可以从12 GB / s的最大可用DRAM带宽中实现超过19.2 Gflop / s。结果还表明,就带宽和功率效率而言,我们基于FPGA的2D-FFT实现比在最先进的CPU和GPU上运行的2D-FFT效率更高。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号