Analyzing the impact of heterogeneous blocks on FPGA placement quality
Chang Xu, Wentai Zhang, Guojie Luo
Abstract
Chang Xu, Wentai Zhang, Guojie Luo
Abstract
In this paper we propose a quantitative approach to analyze the impact of heterogeneous blocks (H-blocks) on the FPGA placement quality. The basic idea is to construct synthetic heterogeneous placement benchmarks with known optimal wire-length to facilitate the quantitative analysis. To the best of our knowledge, this is the first work that enables the construction of wirelength-optimal heterogeneous placement examples. Besides analyzing the quality of existing placers, we further decompose the impacts of H-blocks from the architectural aspect and netlist aspect. Our analysis shows that a heterogeneous design hides the wirelength degradation by a more compact netlist than its homogeneous version; however, the heterogeneity results in a optimality gap of 52% in wirelength, where 25% is from architectural heterogeneity and 27% is from netlist heterogeneity. Therefore, new heterogeneous placement algorithms are needed to bridge the optimality gap and improve design quality.
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In this paper we propose a quantitative approach to analyze the impact of heterogeneous blocks (H-blocks) on the FPGA placement quality. The basic idea is to construct synthetic heterogeneous placement benchmarks with known optimal wire-length to facilitate the quantitative analysis. To the best of our knowledge, this is the first work that enables the construction of wirelength-optimal heterogeneous placement examples. Besides analyzing the quality of existing placers, we further decompose the impacts of H-blocks from the architectural aspect and netlist aspect. Our analysis shows that a heterogeneous design hides the wirelength degradation by a more compact netlist than its homogeneous version; however, the heterogeneity results in a optimality gap of 52% in wirelength, where 25% is from architectural heterogeneity and 27% is from netlist heterogeneity. Therefore, new heterogeneous placement algorithms are needed to bridge the optimality gap and improve design quality.
Key concepts: Netlist, Computer science, Field-programmable gate array, Placement, Quality (philosophy), Construct (python library), Homogeneous, Parallel computing