首页> 外文会议>International Symposium on Advances in Visual Computing(ISVC 2007); 20071126-28; Lake Tahoe,NV(US) >Reducing Storage Requirements in Accelerating Algorithm of Global BioSequence Alignment on FPGA
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Reducing Storage Requirements in Accelerating Algorithm of Global BioSequence Alignment on FPGA

机译:降低FPGA上全局生物序列比对的加速算法中的存储需求

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In the paper, we present storage optimization scheme for hardware accelerating Needleman-Wunsch algorithm. The scheme exploits the characteristics of back-tracking phase in which the back-trace path only travels in a constrained area. Our analysis shows that in addition to logic element resource and memory capacity, the number of RAM blocks is also one of the constrained factors for hardware accelerating bio-sequence alignment. The optimized algorithm only store part of the score matrix to reduce storage usages of FPGA RAM blocks, and implement more processing element in FPGA. We fit our design on FPGA chips EP2S130 and XC2VP70. The experimental results show that the peak performance can reach 77.7 GCUPS (Giga cell updates per second) and 46.82 GCUPS respectively. Our implementation is superior to related works in clock frequency, the maximal PE number and peak performance, respectively.
机译:在本文中,我们提出了用于硬件加速Needleman-Wunsch算法的存储优化方案。该方案利用了回溯阶段的特征,其中回溯路径仅在受限区域中传播。我们的分析表明,除了逻辑元素资源和存储容量外,RAM块的数量也是硬件加速生物序列比对的约束因素之一。经过优化的算法仅存储部分评分矩阵,以减少FPGA RAM模块的存储使用量,并在FPGA中实现更多处理元素。我们将设计适合FPGA芯片EP2S130和XC2VP70。实验结果表明,峰值性能可以分别达到77.7 GCUPS(每秒千兆单元更新)和46.82 GCUPS。我们的实现在时钟频率,最大PE数和峰值性能方面分别优于相关工作。

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