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首页> 外文期刊>Journal of signal processing systems for signal, image, and video technology >Improving Floating-Point Performance in Less Area: Fractured Floating Point Units (FFPUs)
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Improving Floating-Point Performance in Less Area: Fractured Floating Point Units (FFPUs)

机译:在较小的区域中提高浮点性能:浮点单元破裂(FFPU)

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摘要

Embedded systems designers often use fixed-point instead of floating-point due to the performance and area overhead of floating-point units. If the range of floating-point representation is required, the system may use a software-based floating-point library on an integer-only processor to save area-at the cost of much lower performance. Instead, we propose a Fractured Floating Point Unit (FFPU)-a hybrid solution that uses a set of custom hardware instructions to accelerate software-based floating-point emulation. An FFPU is intended as a compromise between software libraries and full FPUs in terms of both area and performance. We present four potential 32-bit FFPU designs for a Nios II soft processor. We compare their performance and area to the baseline Nios II, as well as a Nios II with a complete FPU. We show that an FFPU can improve various floating-point operations, including improving addition and subtraction performance by 24 to 52 percent over the baseline. This performance comes at a resource cost of only an 11 to 29 percent ALM increase, and no increase in DSP blocks.
机译:由于浮点单元的性能和面积开销,嵌入式系统设计人员经常使用定点而不是浮点。如果需要浮点表示的范围,则系统可以在仅整数的处理器上使用基于软件的浮点库来节省面积,但代价是性能要低得多。相反,我们提出了一种脆弱的浮点单元(FFPU)-一种混合解决方案,它使用一组自定义硬件指令来加速基于软件的浮点仿真。 FFPU旨在在面积和性能方面兼顾软件库和完整FPU。我们介绍了针对Nios II软处理器的四种潜在的32位FFPU设计。我们将它们的性能和面积与基准Nios II以及具有完整FPU的Nios II进行了比较。我们表明,FFPU可以改善各种浮点运算,包括将加法和减法性能比基准提高24%至52%。此性能的资源成本仅使ALM增加11%至29%,而DSP块却没有增加。

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