Improved Architectures for a Floating-Point Fused Dot Product Unit

Computer Arithmetic(2013)

引用 15|浏览0
暂无评分
摘要
This paper presents improved architectures for a floating-point fused two-term dot product unit. The floating-point fused dot product unit is useful for a wide variety of digital signal processing (DSP) applications including complex multiplication and fast Fourier transform (FFT) and discrete cosine transform (DCT) butterfly operations. In order to improve the performance, a new alignment scheme, early normalization, a four-input leading zero anticipation (LZA), a dual-path algorithm, and pipelining are applied. The proposed designs are implemented for single precision and synthesized with a 45nm standard cell library. The proposed dual-path design reduces the latency by 25% compared to the traditional floating-point fused dot product unit. Based on a data flow analysis, the proposed design can be split into three pipeline stages. Since the latencies of the three stages are fairly well balanced, the throughput is increased by a factor of 2.8 compared to the non-pipelined dual-path design.
更多
查看译文
关键词
digital signal processigng (dsp),two-term dot product unit,butterfly operation,floating-point arithmetic,floating-point fused operations,signal processing,floating-point fused dot product,floating-point fused two-term dot product unit,size 45 nm,standard cell library,high-speed computer arithmetic,improved architectures,product unit,fast fourier transform,dsp applications,dct butterfly operations,complex multiplication,fft,dual-path algorithm,early normalization,traditional floating-point,discrete cosine transform butterfly operations,libraries,pipelining,data flow analysis,non-pipelined dual-path design,four-input leading zero anticipation,nonpipelined dual-path design,alignment scheme,floating-point fused two-term,digital signal processing,proposed design,floating point arithmetic,proposed dual-path design,pipeline processing,vectors,adders,computer architecture
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要