Addressing Inefficiency of Floating-Point Operations in Cloud Computing: Implementation and a Case Study of Variable Precision Computing

摘要

Cloud computing is increasingly becoming a significant solution for providing scalable computing resources via Internet [1]. However, as the increasing of data size in cloud computing applications and precision requirement in some special scenarios, bandwidth and precision are highly valued in floating-point associated applications, optimizing existing floating-point arithmetic is a significant way to improve current situation. Unum (universal number) arithmetic is a new floating-point arithmetic presented by John L. Gustafson in 2013, being compared with IEEE 754 floats, the outstanding features of unum are clearance of rounding errors, high informationper-bit and variable precision. However, unum was only implemented in software before due to technical complexity, we implement unum arithmetic on FPGA for the first time. We also implement unum based 16-point FFT on FPGA to demonstrate the advantages of unum arithmetic against IEEE 754 floats. We validate the design and contrast the precision and bit width in computing with IEEE 754 floats, evaluate the power efficiency of the designed module. The comparison results show that unum need less bit width than IEEE 754 floats under same precision, it can decrease bandwidth requirement in computing, and ensure correctness even in some extreme arithmetic cases in which IEEE 754 floats cannot work properly.