Adder Based Residue to Binary Number Converters for (2n - 1; 2n; 2n + 1)

Copyright © 2002 IEEEBased on an algorithm derived from the new Chinese remainder theorem I, we present three new residue-to-binary converters for the residue number system (2n-1, 2n, 2n+1) designed using 2n-bit or n-bit adders with improvements on speed, area, or dynamic range compared with various previous converters. The 2n-bit adder based converter is faster and requires about half the hardware required by previous methods. For n-bit adder-based implementations, one new converter is twice as fast as the previous method using a similar amount of hardware, whereas another new converter achieves improvement in either speed, area, or dynamic range compared with previous convertersYuke Wang, Xiaoyu Song, Mostapha Aboulhamid and Hong She

Design and Implementation of an RNS-based 2D DWT Processor

No abstract availabl

Optimization of new Chinese Remainder theorems using special moduli sets

The residue number system (RNS) is an integer number representation system, which is capable of supporting parallel, high-speed arithmetic. This system also offers some useful properties for error detection, error correction and fault tolerance. It has numerous applications in computation-intensive digital signal processing (DSP) operations, like digital filtering, convolution, correlation, Discrete Fourier Transform, Fast Fourier Transform, direct digital frequency synthesis, etc. The residue to binary conversion is based on Chinese Remainder Theorem (CRT) and Mixed Radix Conversion (MRC). However, the CRT requires a slow large modulo operation while the MRC requires finding the mixed radix digits which is a slow process. The new Chinese Remainder Theorems (CRT I, CRT II and CRT III) make the computations faster and efficient without any extra overheads. But, New CRTs are hardware intensive as they require many inverse modulus operators, modulus operators, multipliers and dividers. Dividers and inverse modulus operators in turn needs many half and full adders and subtractors. So, some kind of optimization is necessary to implement these theorems practically. In this research, for the optimization, new both co-prime and non co-prime multi modulus sets are proposed that simplify the new Chinese Remainder theorems by eliminating the huge summations, inverse modulo operators, and dividers. Furthermore, the proposed hardware optimization removes the multiplication terms in the theorems, which further simplifies the implementation

Design of reverse converters for the multi-moduli residue number systems with moduli of forms 2a, 2b - 1, 2c + 1

Residue number system (RNS) is a non-weighted integer number representation system that is capable of supporting parallel, carry-free and high speed arithmetic. This system is error-resilient and facilitates error detection, error correction and fault tolerance in digital systems. It finds applications in Digital Signal Processing (DSP) intensive computations like digital filtering, convolution, correlation, Discrete Fourier Transform, Fast Fourier Transform, etc. The basis for an RNS system is a moduli set consisting of relatively prime integers. Proper selection of this moduli set plays a significant role in RNS design because the speed of internal RNS arithmetic circuits as well as the speed and complexity of the residue to binary converter (R/B or Reverse Converter) have a large dependency on the form and number of the selected moduli. Moduli of forms 2a, 2b- 1, 2c + 1 (a, b and c are natural numbers) have the most use in RNS moduli sets as these moduli can be efficiently implemented using usual binary hardware that lead to simple design. Another important consideration for the reverse converter design is the selection of an appropriate conversion algorithm from Chinese Remainder Theorem (CRT), Mixed Radix Conversion (MRC) and the new Chinese Remainder Theorems (New CRT I and New CRT II). This research is focused on designing reverse converters for the multi-moduli RNS sets especially four and five moduli sets with moduli of forms 2a, 2b- 1, 2c + 1 . The residue to binary converters are designed by applying the above conversion algorithms in different possible ways and facilitating the use of modulo (2k) and modulo (2k – 1) adders that lead to simple design of adder based architectures and VLSI efficient implementations (k is a natural number). The area and delay of the proposed converters is analyzed and an efficient reverse converter is suggested from each of the various four and five moduli set converters for a given dynamic range

Application-Specific Number Representation

Reconfigurable devices, such as Field Programmable Gate Arrays (FPGAs), enable application- specific number representations. Well-known number formats include fixed-point, floating- point, logarithmic number system (LNS), and residue number system (RNS). Such different number representations lead to different arithmetic designs and error behaviours, thus produc- ing implementations with different performance, accuracy, and cost. To investigate the design options in number representations, the first part of this thesis presents a platform that enables automated exploration of the number representation design space. The second part of the thesis shows case studies that optimise the designs for area, latency or throughput from the perspective of number representations. Automated design space exploration in the first part addresses the following two major issues: ² Automation requires arithmetic unit generation. This thesis provides optimised arithmetic library generators for logarithmic and residue arithmetic units, which support a wide range of bit widths and achieve significant improvement over previous designs. ² Generation of arithmetic units requires specifying the bit widths for each variable. This thesis describes an automatic bit-width optimisation tool called R-Tool, which combines dynamic and static analysis methods, and supports different number systems (fixed-point, floating-point, and LNS numbers). Putting it all together, the second part explores the effects of application-specific number representation on practical benchmarks, such as radiative Monte Carlo simulation, and seismic imaging computations. Experimental results show that customising the number representations brings benefits to hardware implementations: by selecting a more appropriate number format, we can reduce the area cost by up to 73.5% and improve the throughput by 14.2% to 34.1%; by performing the bit-width optimisation, we can further reduce the area cost by 9.7% to 17.3%. On the performance side, hardware implementations with customised number formats achieve 5 to potentially over 40 times speedup over software implementations