Enhancing Precision and Bandwidth in Cloud Computing: Implementation of a Novel Floating-Point Format on FPGA

Junjie Hou, Yongxin Zhu, Yulan Shen, Mengjun Li, Qian Wu, Han Wu
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引用次数: 10

Abstract

Cloud computing is a type of Internet-based service computing that provides computing, storage and networking services to multiple users. With the increase of data size, computing capacity runs out quickly in cloud computing services. To fill the shortage of computation capacity, we propose to adopt variable precision by implementing unum (universal number), which is a number format different from IEEE Standard for Floating-Point Arithmetic - IEEE 754 floats. Compared with IEEE 754 floats, the outstanding features of unum are clearance of rounding errors, high information-per-bit and variable precision. As a candidate replacement of IEEE 754 floats, the application of unum can improve the precision in computing, decrease the bit width for high precision numbers. However, unum was only implemented in software model before due to technical complexity, in order to validate the performance on chip, we implement this arithmetic on FPGA for the first time. We also implement an unum based 16-point FFT on FPGA. We validate the design and compare the bit width in computing with IEEE 754 floats, evaluate the power dissipation on FPGA. The experimental results of comparison show that unum arithmetic can ensure correctness even in some extreme arithmetic cases in which IEEE 754 floats cannot work properly, furthermore the bit width of unum is much less than IEEE 754 floats in the same precision.
提高云计算的精度和带宽:一种新型浮点格式在FPGA上的实现
云计算是一种基于互联网的服务计算,为多个用户提供计算、存储和网络服务。随着数据量的增加,云计算服务的计算能力很快就会耗尽。为了弥补计算能力的不足,我们提出通过实现unum(通用数)来实现可变精度,unum是一种不同于IEEE浮点运算标准IEEE 754浮点数的数字格式。与ieee754浮点数相比,unum的突出特点是消除舍入误差,每比特信息量高,精度可变。unum作为IEEE 754浮点数的候选替代品,可以提高计算精度,减少高精度数的位宽。然而,由于技术的复杂性,unum之前只能在软件模型上实现,为了验证芯片上的性能,我们首次在FPGA上实现了该算法。我们还在FPGA上实现了一个基于unum的16点FFT。我们对设计进行了验证,并与IEEE 754浮点数的计算位宽进行了比较,评估了FPGA上的功耗。实验结果表明,即使在IEEE 754浮点数不能正常工作的极端情况下,unum算法也能保证算法的正确性,而且在相同精度下,unum的位宽远小于IEEE 754浮点数。
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