As the name suggests, elementary functions play a vital role in scientific computations. Yet due to their inherent nature, they are a considerable computing task by themselves. Not surprisingly, since the dawn of computing, the goal of speeding up elementary function computation has been pursued. This paper describes new hardware based algorithms for the computation of the common elementary functions, namely division, logarithm, reciprocal square root, arc tangent, sine and cosine. These algorithms exploit microscopic parallelism using specialized hardware with heavy use of truncation based on detailed accuracy analysis. The contribution of this work lies in the fact that these algorithms are very fast and yet are accurate. If we let the time to perform an IEEE Standard 754 double precision floating point multiplication be /spl tau//sub /spl times//, our algorithms to achieve roughly 3.68/spl tau//sub /spl times//,4.56/spl tau//sub /spl times//, 5.25/spl tau//sub /spl times//, 3.69/spl tau//sub /spl times//, 7.06/spl tau//sub /spl times//, and 6.5/spl tau//sub /spl times//, for division, logarithm, square root, exponential, are tangent and complex exponential (sine and cosine) respectively. The trade-off is the need for tables and some specialized hardware. The total amount of tables required, however, is less than 128 Kbytes. We discuss the hardware, algorithmic and accuracy aspects of these algorithms. >
['W.F. Wong', 'E. Gogo']
Fast hardware-based algorithms for elementary function computations using rectangular multipliers