Affiliation:
1. The Exelixis Lab, Scientific Computing Group, Heidelberg Institute for Theoretical Studies, 69118 Heidelberg, Germany
Abstract
The use of reconfigurable computing for accelerating floating-point intensive codes is becoming common due to the availability of DSPs in new-generation FPGAs. We present the design of an efficient, pipelined floating-point datapath for calculating the logarithm function on reconfigurable devices. We integrate the datapath into a stand-alone LUT-based (Lookup Table) component, the LAU (Logarithm Approximation Unit). We extended the LAU, by integrating two architecturally independent, LAU-based datapaths into a larger component, the VLAU (vector-like LAU). The VLAU produces 2 results/cycle, while occupying the same amount of memory as the LAU. Under single precision, one LAU is 12 and 1.7 times faster than the GNU and Intel Math Kernel Library (MKL) implementations, respectively. The LAU is also 1.6 times faster than the FloPoCo reconfigurable logarithm architecture. Under double precision, one LAU is 20 and 2.6 times faster than the respective GNU and MKL functions and 1.4 times faster than the FloPoCo logarithm. The VLAU is approximately twice as fast as the LAU, both under single and double precision.
Funder
Deutsche Forschungsgemeinschaft
Subject
Hardware and Architecture
Cited by
1 articles.
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