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International Journal of Advances in Engineering & Technology, May 2012.
©IJAET                                                             ISSN: 2231-1963



   HIGH SPEED REVERSE CONVERTER FOR HIGH DYNAMIC
                 RANGE MODULI SET
        MohammadReza Taheri1, Abdolreza Pirhoseinlo2, Mojtaba Esmaeildoust3,
                   Mohammad Esmaeildoust4, Keivan Navi4
            1
          Microelectronic Laboratory of Shahid Beheshti University, GC, Tehran, Iran
            2
           Department of Computer Engineering, Islamic Azad University, Arak, Iran
    3
      Computer Engineering Department, Faculty of Engineering, University of Guilan, Iran
  4
    Faculty of Electrical and Computer Engg., Shahid Beheshti University, GC, Tehran, Iran




ABSTRACT
In this paper a new reverse converter architecture for the five moduli set {2n, 2n/2-1, 2n/2+1, 2n+1, 22n-1-1} is
presented. The proposed converter is designed in two levels architecture by using of New Chinese Reminder
Theorem-I (New CRT-I) and Mixed Radix Conversion (MRC). The proposed architecture has achieved
significant improvement in terms of delay of the reverse converter compared to state-of-the-art reverse
converters.

KEYWORDS: Residue Number System, Digital Circuits, Residue Arithmetic, Reverse Converter

  I.     INTRODUCTION
The residue number system is non-weighted number systems. Using this property has the advantages
such as carry free operations, parallelism, fault tolerance and low power design in very large scale
integration technology [1]. Speed up arithmetic operation in residue number system obtains by
decomposing large binary operation into smaller residues. Therefore large number computations are
replaced by smaller parallel operations. During the past decade, RNS has been widely used in the
applications which requires intensive computation such image processing [2-3], Digital Signal
Processing[4-6], and cryptography [7-9]. RNS based processors, unlike the binary systems,bear the
extra cost of two components. These two components are the binary-to-residue (forward)and residue-
to-binary (reverse) converters. Forward converter, converts thebinary number into its equivalent
residues and reverse converter, converts the residues into their equivalent weighted number.
Arithmetic unit is the core of RNS which performs arithmetic operations required by the application
in parallel without carry propagation between residues digits. Reverse converter is a difficult process
that affects the performance of the RNS. Form of the moduli set and number of moduli that chosen for
RNS processor affects on dynamic range, speed and its VLSI implementation [10]. Different moduli
set have been suggested for RNS. Most popular moduli set for past decade was {2n, 2n-1, 2n
+1} where efficient reverse converter for this moduli set reported in [11]. For more parallelism four
and five moduli sets are presented such as {2n, 2n–1, 2n+1, 22n+1–1}, {22n, 2n–1, 2n+1, 22n+1}[12], {2n,
2n–1, 2n+1, 2n+1–1, 2n–1–1} [13], {2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1–1} [14] and {2n, 2n/2–1, 2n/2+1, 2n+1,
22n+1–1} [15] are presented. Among the five moduli sets, moduli set {2n, 2n–1, 2n+1, 2n+1–1, 2n–1–1}
enjoys well formed moduli with efficient arithmetic operation. The reverse converter for this moduli
set has very high latency and hardware costbecause of inefficient multiplicative inverses. In order to
achieve better trade-off between efficiency of arithmetic operation and reverse converter, other
unbalanced moduli sets {2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1–1} [14] and {2n, 2n/2–1, 2n/2+1, 2n+1, 22n+1–1}



       26                                                                        Vol. 3, Issue 2, pp. 26-37
International Journal of Advances in Engineering & Technology, May 2012.
©IJAET                                                             ISSN: 2231-1963
[15] with very simple hardware implementations of their reverse converter with higher speed
compared to [13] are presented.
In this paper another design of reverse converter for the five moduli set {2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1–
1} is presented. Two level designs are used in designing the proposed architecture by using New
CRT-I and MRC for first and second level design, respectively. The proposed adder-based reverse
converter has achieved faster implementation compared to other five moduli sets.
This paper is organized as follow, in section II the background of RNS is reviewed, in next section
new reverse converter in two levels design for mentioned moduli set is proposed, in forth section
hardware implementation of proposed reverse converter is represented and finally section V
concludesthe paper.

II.     PREVIOUS WORKS
Different moduli set have been proposed for RNS. Three moduli set {2n, 2n–1, 2n+1} was the most
popular moduli set in the past decade which different reverse converters for this moduli set is reported
in [16-20]. The best hardware implementation of the reverse converter for this moduli set is reported
in [11]. In this report, three different design of residue to binary converters for the moduli set {2n, 2n–
1, 2n+1} by using n-bit and 2n-bit adders are presented. Converter which is based on 2n-bit adder
requires near half hardware area and better delay in comparison with previous works in this class of
moduli set. The dynamic range of this moduli set is not qualified for applications which require larger
dynamic range with more parallelism. Therefore another class of moduli set with more moduli or
more dynamic range or both is reported in literatures. One of these approach is four moduli sets with
4n-bit dynamic range like {2n–3, 2n+1, 2n–1, 2n+3} [21], {2n–1, 2n, 2n+1, 2n+1–1} and {2n–1, 2n, 2n+1,
2n+1+1} [22], {2n, 2n+1–1, 2n–1, 2n–1–1}[23]. In [21], three different design of the reverse converters
for the moduli set {2n–3, 2n+1, 2n–1, 2n+3} are reported. The first design does not need any ROM and
designed by adder base structure whereas others need ROM as well as combinational logic. In [22],
two residue to binary converters for the two moduli set {2n–1, 2n, 2n+1, 2n+1–1} and {2n–1, 2n, 2n+1,
2n+1+1} are presented. The reverse converter of these moduli set are designed by MRC technique
which apply on the two moduli set {{2n, 2n–1, 2n+1}, 2n+1–1} and {{2n, 2n–1, 2n+1}, 2n+1–1},
respectively. The hardware cost is more economical than previous methods. Also residue to binary
conversion delay also is reduced in this design. Efficient designs of residue to binary converter for the
moduli set {2n, 2n+1–1, 2n–1, 2n–1–1} is reported in [23]. This moduli set is completely free from
modulo 2k+1 type which results in high-speed modulo arithmetic. MRC algorithm is used to design
residue to binary converter architectures. In [24], three moduli set {2n, 22n–1, 22n+1} with 5n-bit
dynamic range is presented. Chinese Remainder Theorem is used for design reverse converter for this
moduli set. Simple hardware implementation by using only one CSA followed by a 4n bit modulo
24n 1 adder, and a few gates, results in remarkable delay of reverse conversion. In [25], reverse
  −
converter for mosuli set {2n–1, 2n, 2n+1, 22n+1} with efficiency in delay conversion and hardware cost
of its implementation with using CRT algorithm is presented. The disadvantage of these two moduli
sets reported in [24-25] is use of modulo 22n+1 which increase the latency of the RNS arithmetic unit.
For overcome this problem moduli set {2n–1, 2n, 2n+1, 22n+1–1}[12] is presented. In this work, New
CRT-II is employed for designing an efficient reverse conversion. In class of five moduli with 5n-bit
dynamic range, moduli set such as {2n, 2n–1, 2n+1, 2n–2(n+1)/2 +1,2n+2(n+1)/2+1}[26], {2n, 2n–1, 2n+1,
2n+1–1, 2n–1–1}[13], {2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1–1} [14] and {2n, 2n/2–1, 2n/2+1, 2n+1, 22n+1–1} [15]
are presented. In [26] with using CRT, a full adder based reverse converter presented for the moduli
set {2n, 2n–1, 2n+1, 2n–2(n+1)/2 +1, 2n+2(n+1)/2+1}. The problem of this moduli system is that the speed of
the arithmetic unit of RNS is restricted to the low-performance modulo 2n+2(n+1)/2+1. Cao et al. [13]
proposed balanced and well-formed moduli set {2n, 2n–1, 2n+1, 2n+1–1, 2n–1–1} with efficient RNS
arithmetic unit. In other hand the dynamic range of this moduli set are sufficient for today’s necessity.
The only disadvantage of this moduli set is its complex reverse converter due to inefficient forms of
multiplicative inverse that lead to increasing the cost and the delay of reverse converter. Unbalanced
moduli sets {2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1–1} and {2n, 2n/2–1, 2n/2+1, 2n+1, 22n+1–1} with very simple
hardware implementations of their reverse converter with higher speed compared to [13] and [26].
These moduli sets provides better trade-off between efficiency of arithmetic operation and reverse
converter are presented.

      27                                                                    Vol. 3, Issue 2, pp. 26-37
International Journal of Advances in Engineering & Technology, May 2012.
©IJAET                                                             ISSN: 2231-1963

III.         RELATED BACKGROUND
Chinese Reminder Theorem (CRT)converts an RNS number into its equivalent weighted Number as
follows:
                                  n
                          X =    ∑xN
                                 i =1
                                          i    i   Pi M i                                                              (1)
                                                                M

Where

                            M = P1 P2 ...Pn

                            Pn , M i = M / Pi

                            N i = M i−1 Pi

The CRT can be implemented in parallel channels followed by a modulus M adder.Modulo M
reduction has very large latency and this can leads to inefficient hardware implementation of the
reverse converter for high dynamic range moduli sets.
The weighted number X can be computed by New CRT-I as follows:

                                   k 1 ( x 2 − x 1 ) + k 2 P2 ( x 3 − x 2 ) + ...
              X = x 1 + P1 ×                                                                                           (2)
                                        + k n −1P2 P3 ...Pn −1 ( x n − x n −1 )     P2 P3 ...Pn

Where

                             k1 × P P P ... P = 1
                                   1
                                         2 3       n


                             k 2 × P × P2 P ... P = 1
                                    1
                                                       3    n


                             kn−1 × P × P2 × ... × Pn−1 P = 1
                                     1
                                                                         n




Compared to CRT, the size of the final modulo reduction is reduced in New CRT-I. Mixed Radix
Conversion (MRC) is another algorithm to convert the residues into the weighted number. To
calculate Xfrom its residues by MRC, we have
                                        n −1
                           X = vn ∏ Pi + ... + v3 P2 P + v2 P + v1
                                                      1      1                                                         (3)
                                        i =1
The coefficients vis can be obtained from residues by
                                v1 = x1                                                                                (4)
                                                       −1
                       v2 = ( x2 − v1 ) P1                                                                             (5)
                                                            P2 P
                                                                2

                                              −1                    −1
                  v3 = (( x3 − v1 ) P1                     − v2 ) P2                                                   (6)
                                                   P3                    P3 P
                                                                             3

In the general case, we have

                                −1           −1                      −1
        vn   = ((( x n − v1 ) P1 P − v 2 ) P2 P − ⋅ ⋅ ⋅ − v n −1 ) Pn −1 P                                             (7)
                                   n            n                         n Pn

 P1−1        indicates the multiplicative inverse of Pj modulus Pj .
        Pj


IV.          REVERSE CONVERTER DESIGN
In order to efficient design of reverse converter for the moduli set{2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1–1},
two levels of design are employed. First level is designed by using New CRT-I and considering


        28                                                                                        Vol. 3, Issue 2, pp. 26-37
International Journal of Advances in Engineering & Technology, May 2012.
©IJAET                                                             ISSN: 2231-1963
subset{2n/2–1, 2n/2+1, 2n+1, 22n–1–1}and in second level subset {(2n/2–1)( 22n–1–1), 2n} is designed by
using MRC.

3.1. First Level Design
In order to calculate the weighted number Z from its residues in subset {2n/2–1, 2n/2+1, 2n+1, 22n–1–1}
by using New CRT-I, we have

               Z = x1 + P k1 ( x2 − x1 ) + k2 P2 ( x3 − x2 ) + k3 P2 P3 ( x4 − x3 ) P P P
                         1
                                                                                                                                                      (8)
                                                                                                              2 3 4

                                                                              n                       n
By considering P = 2 2 n −1 − 1, P2 = 2n + 1, P3 = 2 2 + 1, P4 = 2 2 − 1 , we have
                1



                            2 n −1
                                              k 1 (x 2 − x 1 ) + k 2 (2n + 1)(x 3 − x 2 ) +
             Z = x 1 + (2            − 1)                                     n
                                                                                                                                                      (9)
                                                          k 3 (2n + 1)(2 2 + 1)(x 4 − x 3 )                   22 n −1


For the required multiplicative inverse in Eq. 9,we have

                      k 1 × (2 2 n −1 − 1) 22 n −1 = 1 → k 1 = −2

                      k 2 × (2 2 n −1 − 1)(2 n + 1) 2n −1 = 1 → k 2 = −1

                                                                                                                  n
                                                                  n                                                 −1
                                2 n −1                n
                      k3 × (2            − 1)(2 + 1)(2 + 1)           2
                                                                                      n
                                                                                          2 −1
                                                                                                 = 1 → k3 = −2    2
                                                                                  2


Eq. 9 can be rewritten as

                             Z = x 1 + (22n −1 − 1)Y                                                                                                 (10)
To calculate Y we have

                                     (−2)( x2 − x1 ) + ( −1)(2n + 1)( x3 − x2 ) +
                         Y=                           n                           n
                                                                                                                                                     (11)
                                             (−2 2 −1 )(2n + 1)(2 2 + 1)( x4 − x3 )                           2   2n
                                                                                                                       −1
Eq. 11 can be rewrite as

                       Y = Z 1 + Z 2 + Z 3 22 n −1                                                                                                   (12)
Where
                                     Z 1 = ( −2)( x 2 − x 1 ) 22 n −1

                           Z 2 = ( −1)(2n + 1)( x3 − x2 ) 22 n −1

                                             2 −1
                                         n                                n
                     Z3 = (−2                       )(2 n + 1)(2 2 + 1)( x 4 − x 3 ) 2 2 n −1

By considering x1 = x1,2 n −2 K x1,0 , x2 = x2,n K x2,0 , x3 = x3, n K x3,0 and x4 = x4, n                                               K x4,0 , for Z1 we
                                                                                                          2                       2 −1

have

                          Z1 = 2 × ( x1 − x2 ) 22 n −1                                                                                               (13)

             Z1 = 2 × ( x1,2 n − 2 K x1,0 − x2,n K x2,0 ) 22 n −1                                                                                    (14)




       29                                                                                                                   Vol. 3, Issue 2, pp. 26-37
International Journal of Advances in Engineering & Technology, May 2012.
©IJAET                                                             ISSN: 2231-1963

                                                   
  Z1 = 2 ×  0 x1,2 n − 2 K x1,0 − 0L3 x2, n K x2,0 
                                   1   2   00                                                                               (15)
                                                   
                                   ( n −1)bit       22 n −1


          Z1 = x1,2 n −2 K x1,0 0 + 11...1 x2,n K x2,01
                                    {                                                                                       (16)
                                            ( n − 2 )bit                     2n
                                                                           2 −1

                  Z 1 = Z 11 + Z 12 22 n −1                                                                                 (17)
Where

                         Z 11 = x 1,2n −2 ...x 1,0 0

                     Z12 = 11L1 x2, n K x2,01
                           {
                             ( n − 2 )bit

For Z2 we have

                  Z 2 = −(2n + 1)( x3 − x2 )                                                                                (18)
                                                           22 n −1

                                                                 
                                                                 
                 (       )
        Z 2 = − 2n + 1  00L 0 x3, n 2 K x3,0 − 00L 0 x2,n K x2,0 
                         1 3 2                  1 3 2                                                                       (19)
                         3 n−1bit
                                                ( n −1)bit       
                       2 
                                                                  22 n −1

                 x2,n −1 K x2,0 00L 0 x2,n + 00L 0 x2,n K x2,0 −
                                1 3
                                  2          1 3
                                               2
                                    ( n −1)bit               ( n −1)bit

          Z2 =                                                                                                            (20)
                                                                
                00L 0 x3, n K x3,0 00L 0 + 00L 0 x3, n 2 K x3,0 
                 1 3 2
                     2              1 3 1 3
                                      2        2
                ( n 2 −1)bit        n bit  3
                                            
                                                   
                                               n −1bit
                                                                 
                                           2                   22 n −1

                     x2,n −1 K x2,0 00L 0 x2,n + 00L 0 x2, n K x2,0 +
                                    1 3
                                      2          1 3
                                                   2
                                              ( n −1)bit             ( n −1)bit
              Z2 =       11L1 x3, n K x3,0 11L1 x3, n 2 K x3,0
                         { 2               {1 24                                                                            (21)
                          n                     4 3      n 
                           −1bit                          −1bit          n 
                          2                              2                +1 bit
                                                                             2              22 n −1
Therefore

                                Z 2 = Z 21 + Z 22 + Z 23 2 2 n −1                                                           (22)

Where


                         Z 21 = x2,n −1 K x2,0 00L 0 x2,n
                                               1 3
                                                 2
                                                              ( n −1)bit            22 n −1




                         Z 22 = 00L 0 x2,n K x2,0
                                1 3
                                  2
                                        ( n −1)bit                        22 n −1



     30                                                                                                 Vol. 3, Issue 2, pp. 26-37
International Journal of Advances in Engineering & Technology, May 2012.
©IJAET                                                             ISSN: 2231-1963



                       Z 23 = 11L1 x3, n K x3,0 11L1 x3, n 2 K x3,0
                              { 2               {1 24
                              n               n 
                                                       4 3
                                  −1bit                         −1bit       n 
                                 2                             2             +1bit
                                                                                2             22 n −1


For Z3 we have

                     Z3 = (−2 2 −1 )(2n + 1)(2 2 + 1)( x4 − x3 )
                                 n                      n
                                                                                                                                    (23)
                                                                                 22 n −1


                         n                       n
                                                            (
              Z3 = (−2 2 −1 )(2n + 1)(2 2 + 1) x4, n 2 −1 K x4,0 − x3, n 2 K x3,0                         )   22 n −1
                                                                                                                                    (24)



                           2n + 1 x4,n −1 K x4,0 x4, n −1 K x4,0 −
                             (         )(                                         )
                                            2         2
                                                                                
                                                                            
                −2 2 −1 ×   n  
                  n


           Z3 =                                                                                                                   (25)
                            2 2 + 1  00L 0 x3,n K x3,0 00L 0 x3, n K x3,0  
                                         1 3 2
                                            2               1 3 2
                                                              2
                                                                               
                                      n -1 bit        n 
                                                             -1 bit
                                                                              
                                       2 
                                                          2               
                                                                                                              2 2 n −1




                         − x4 x4 x4 x4 + x n K x3,0 00L 0 x3 00L 0 x3, n 2 
                                                       1 3 1 3
                                                          2          2
                                            3, −1
                                               2        n        n       
                   n −1                                 -1 bit
                                                        2 
                                                                    -1 bit
                                                                   2       
                  2 2 ×                                                                                                           (26)
             Z3 =               + 00L 0 x3, n 2 K x3,0 00L 0 x3, n 2 K x3,0
                                 1 32                 1 32                  
                                  n 
                                    -1 bit
                                                       n 
                                                        -1 bit             
                                  2                 2                   
                                                                                                              2 2 n −1




                         x 4,0 x4 x4 x4 x  n     K x4,1 + x3,0 00L 0 x3 00L 0 x3,n 2 K x3,1
                                                               1 3 1 3
                                                                 2        2
                                         4, −1
                                           2                        n           n 
                                                                     -1 bit      -1 bit
                  Z3 =
                                                                    2           2                                               (27)
                                     + x3,n 2 K x3,0 00L 0 x3,n 2 K x3,0 00L 0
                                                     1 3
                                                       2                 1 3
                                                                           2
                                                        n                        n 
                                                         -1 bit                   -1  bit
                                                        2                        2                         2 2 n −1



                    Z 3 = z31 + z32 + z33 22 n −1                                                                                   (28)

where

                                     Z31 = x 4,0 x4 x4 x4 x           n       K x4,1
                                                                    4, −1
                                                                      2


                             Z 32 = x3,0 00L 0 x3 00L 0 x3, n 2 K x3,1
                                         1 3 1 3
                                           2        2
                                            n                  n 
                                             -1  bit            -1  bit
                                            2                  2 


                       Z 33 = x3, n 2 K x3,0 00L 0 x3, n 2 K x3,0 00L 0
                                             1 3
                                               2                  1 3
                                                                    2
                                                     n                            n 
                                                      -1 bit                       -1 bit
                                                     2                            2 




     31                                                                                                       Vol. 3, Issue 2, pp. 26-37
International Journal of Advances in Engineering & Technology, May 2012.
©IJAET                                                             ISSN: 2231-1963
Therefore Y can be calculated as

                  Y = z11 + z12 + z21 + z22 + z23 + z31 + z32 + z33 22 n −1                         (29)

Hardware implementation ofEq. 29 is shown in figure 1. Bit organizer provides the required operands
in Eq. 29. Carry Save Adders (CSA) with End Around Carry (EAC) are used to reduce the number of
operands and then Modulo 22n–1 Adder (MA (22n–1)) is employed to calculate the Y.




                                   Figure 1. Hardware implementation of Y

After calculation of Y, to realize Z we have

                       Z = x 1 + (22 n −1 − 1)Y                                                     (30)

                       Z = x1 + Y 00L 0 − Y
                                  1 3
                                    2                                                               (31)
                                    ( 2 n −1)bit

                                 Z = Y x 1 −Y                                                       (32)

3.2. Second Level Design

Second level of the design consider the moduli set {(22n–1)( 22n–1–1), 2n} by using MRC. Considering
P1234 = (22n–1)( 22n–1–1) and using MRC we have

                             x = v 1 + v 2 p1234                                                    (33)

                              v1 = Z                                                                (34)

                               v2 = ( x5 − z ) P −1
                                                1234                                                (35)
                                                       2n 2n




     32                                                                       Vol. 3, Issue 2, pp. 26-37
International Journal of Advances in Engineering & Technology, May 2012.
©IJAET                                                             ISSN: 2231-1963
For the required multiplicative inverses, we have

                                      P −1
                                       1234           → k (22 n − 1)(22 n −1 − 1)               =1
                                                 2n                                        2n


                              P−1
                               1234          =1
                                        2n


Therefore

                                   v2 = x5 − Yx1 + Y                2n
                                                                                                                                (36)

Eq. 36 can be rewritten as

              v2 = x5, n −1 K x5,0 − Y2 n −1 K Y0 x1,2 n − 2 K x1,0 + Y2 n −1 KY0                    2n
                                                                                                                                (37)

                  v2 = x5,n −1 K x5,0 − x1n −1 K x1,0 + Yn −1 K Y0                         2n
                                                                                                                                (38)

                        v2 = x5 + v21 + v22 + 1 2n                                                                              (39)

Where

                                             v21 = x1,n −1 K x1,0
                                             v22 = Yn−1 KY0

Therefore

              X = v 1 + v 2 (22 n − 1)(22 n −1 − 1)                                                                             (40)

             X = Yx1 − Y + (v2 00L 0 − v2 )(2 2 n −1 − 1)
                               1 3
                                 2                                                                                              (41)
                                             2 n bit


          X = Yx1 − Y + v2 00L 0 − v2 00L 0 − v2 00L 0 + v2
                           1 3
                             2        1 3
                                        2        1 3
                                                   2                                                                            (42)
                                    4 n −1 bit            2 n bit        2 n −1 bit


                   X = v2Yx1 + v2Y + v211L1 + 2 + v2                                                                            (43)

             X = v 2Y x 1 + v 2Y + v 2 00L 0 + v 2 + 1 + 100L 0
                                                          1 3
                                                            2                                                                   (44)
                                                                                      2n


                  X = v 2Y x 1 + v 2Y + v 2 00L 0v 2 + 1 0L 0 1
                                            1 3
                                              2          {                                                                      (45)
                                                            ( n −1)bit        ( 2 n −1)bit

                   K 1 = v 2Y x 1                                                                                               (46)

                    K 2 = v 2Y                                                                                                  (47)

            K 3 = v2 00 L 0 v2
                     1 3
                       2                                                                                                        (48)
                      ( n −1)bit

              K 4 = 1 0L 0 1
                      {                                                                                                         (49)
                       ( 2 n −1)bit



     33                                                                                                   Vol. 3, Issue 2, pp. 26-37
International Journal of Advances in Engineering & Technology, May 2012.
©IJAET                                                             ISSN: 2231-1963
Therefore

            X = K1 + K 2 + K 3 + K 4                                                               (50)

Hardware implementation of X is shown in figure 2. First v2 in Eq. 39 is implemented by
using an n bit CSA followed by the Carry Propagate Adder (CPA). Then bit organizer in
figure 2, provides the required shift and negation required in Eq. 46-49. In next step, two
CSA followed by the CPA calculate the final result of X according to Eq. 50.




                                 Figure 2. Hardware implementation of X

                 Table 1. Delay and area comparison of five moduli sets reverse converters

            Converter          Hardware requirements         Conversion delay
              [13]    ((5n2+43n+m* )/6+16n–1)AFA +(6n+1)ANOT  (18n+L*+7)tFA
                              (10n+5)AFA+(7n–5)AXNOR
              [14]             +(7n–5)AOR +(2n–3)AXOR        (13n+1)tFA+3tNOT
                              +(2n–3)AAND+(8n+2)ANOT
                            (12.5n+6)AFA+(4.5n–1)AXNOR
              [15]          +(4.5n–1)AOR + (1.5n–1)AXOR      (12n+6)tFA+3tNOT
                             +(1.5n–1)AAND+(7n+1)ANOT
                             (17n +n/2+2)AFA+(4n)AXNOR
            Proposed            +(4n)AOR +(8n–5)AXOR            (10n+ 6)tFA
                               +(8n–5)AAND+(7n/2)ANOT

 V.     COMPARISON
Details of area and delay comparisons of the proposed reverse converter for the moduli set {22n–1–1,
2n+1, 2n/2–1, 2n/2+1, 2n} with other five moduli sets reported in [13], [14] and [15] are shown in table
1. In order to achieve fair comparison, in calculations of delay and area, assumptions such as
considered in [14-15] are employed. According to the obtained result in table 1, the proposed
converter has (10n+6)tFA, where tFA denotes the delay of one bit full adder. The reverse converter

      34                                                                     Vol. 3, Issue 2, pp. 26-37
International Journal of Advances in Engineering & Technology, May 2012.
©IJAET                                                             ISSN: 2231-1963
proposed in [13] has the delay of (13n+1)tFA. Therefore the proposed converter for the moduli set
{22n+1–1, 2n+1, 2n/2–1, 2n/2+1, 2n} with different levels of the design compared to [14] achieved in
more speed in reverse conversion.Comparison with other five moduli sets are shown in table 1. It can
be seen that the proposed reverse converter for the moduli set {22n+1–1, 2n+1, 2n/2–1, 2n/2+1, 2n} has
achieved fastest implementation compared to other five moduli reverse converters.

VI.     CONCLUSION
We have presented a simple and efficient reverse converter architecture for the five moduli set {22n+1–
1, 2n+1, 2n/2–1, 2n/2+1, 2n}. Two levels design, New CRT-I for subset {2n/2–1, 2n/2+1, 2n+1, 22n–1–1}
and MRC for superset {(22n–1)( 22n–1–1), 2n} are employed. Higher speed of the reverse converter has
achieved compared to other five moduli set reverse converters in literature.

REFERENCES
    [1]. K. Navi, A. S. Molahosseini, M. Esmaeildoust, (2011) "How to Teach Residue Number System to
         Computer Scientists and Engineers," IEEE Transactions on Education, Vol. 54, Issue. 1, pp. 156-163.
    [2]. W. Wei et al., (2004)“RNS application for digital image processing,” Proceedings of the 4th IEEE
         international workshop on system-on-chip for real time applications. pp. 77 - 80.
    [3]. A. Ammar, A. Al kabbany, M. Youssef, and A. Emam, (2001)“A secure image coding using residue
         number systems,” Proc. of the 18th National Radio Science Conference.
    [4]. G.C. Cardarilli, A. Nannarelli and M. Re, (2007) “Residue Number System for Low-Power DSP
         Applications,” Proc. of 41nd IEEE Asilomar Conference on Signals, Systems, and Computers.
    [5]. R. Conway and J. Nelson, (2004) “Improved RNS FIR Filter Architectures,” IEEE Transactions on
         Circuits and Systems-II, Vol. 51, No. 1, pp. 26-28.
    [6]. W. K. Jenkins and B. J. Leon, (1977) “The use of residue number systems in the design of finite
         impulse response digital filters,” IEEE Transactions on Circuits and Systems, vol. CAS-24, pp. 191–
         201.
    [7]. J. C. Bajard, L. Imbert, (2004) "A Full RNS Implementation of RSA," IEEE Transactions on
         Computers, vol. 53, no. 6, pp. 769-774.
    [8]. Marzie Gerami, Mohammad Esmaeildoust, Shirin Rezaei, Keivan Navi and Omid Hashemipour,
         (2011) “Four Moduli RNS Bases for Efficient Design of Modular Multiplication,” Journal of
         Computations & Modelling, vol.1, no.2, 73-96.
    [9]. D. M. Schinianakis, A. P. Fournaris, H. E. Michail, A. P. Kakarountas, andT. Stouraitis, (2009) “An
         RNS Implementation of an Fp Elliptic CurvePoint Multiplier”, IEEE TRANSACTIONS ON
         CIRCUITS AND SYSTEMS—I, VOL. 56, NO. 6.
    [10]. K. Navi, M. Esmaeildoust, and A. S. Molahosseini, (2011) "A General Reverse Converter
         Architecture with Low Complexity and High Performance," IEICE Transactions on Information and
         Systems, Vol. E94-D, No.2, pp. 264-273.
    [11]. Y. Wang, X. Song, M. Aboulhamid and H. Shen, (2002) “Adder based residue to binary numbers
         converters for (2n–1, 2n, 2n+1),”IEEE Transactions on Signal Processing, vol. 50, no. 7, pp. 1772-1779.
    [12]. A. S. Molahosseini, K. Navi, C. Dadkhah, O. Kavehei and S. Timarchi, (2010) " Efficient Reverse
          Converter Designs for the new 4-Moduli Sets {2n–1, 2n, 2n+1, 22n+1–1} and {2n–1, 2n+1, 22n, 22n+1}
          Based on New CRTs," IEEE Transaction on Circuit and System I, Vol. 57, No. 4, pp. 823-835.
    [13]. B. Cao, C.H. Chang and T. Srikanthan, (2007) “A Residue-to-Binary Converter for a New Five-
         Moduli Set,”IEEE Transactions on Circuits and Systems-I, vol. 54, no. 5, pp.1041–1049.
    [14]. A.S. Molahosseini, C. Dadkhah, K. Navi, (2009) “A New Five-Moduli Set for Efficient Hardware
         Implementation of the Reverse Converter,” IEICE Electronics Express, vol. 6, no. 14, pp. 1006-1012.
    [15]. Mohammad Esmaeildoust, Keivan Navi and MohammadReza Taheri, (2010) “High speed reverse
          converter for new five-moduli set {2n, 22n+1–1, 2n/2–1, 2n/2+1, 2n+1}”, IEICE Electron. Express, Vol. 7,
          No. 3, pp.118-125.
    [16]. D. Gallaher, F. Petry, and P. Srinivasan, (1997) “The digital parallel method for fast RNS to weighted
          number system conversion for specific moduli {2n, 2n−1, 2n+1},” IEEE Trans. Circuits Syst. II, vol.
          44, pp. 53–57.
    [17]. S. Piestrak,(1995) “A high-speed realization of a residue to binary number system converter,” IEEE
          Trans. Circuits Syst. II, vol. 42.
    [18]. R. Conway and J. Nelson,(1999) “Fast converter for 3 moduli RNS using new property of CRT,”
          IEEE Trans. Comput., vol. 48, pp. 852–860.
    [19]. B. Vinnakota and V. V. B. Rao,(1994) “Fast conversion techniques for binary-residue number
          systems,” IEEE Trans. Circuits Syst. I, vol. 41, pp. 927–929.


      35                                                                         Vol. 3, Issue 2, pp. 26-37
International Journal of Advances in Engineering & Technology, May 2012
                                                                   2012.
©IJAET                                                             ISSN: 2231-1963
    [20]. M. Bhardwaj, A. B. Premkumar, and T. Srikanthan, (1998) “Breaking the 2n       2n-bit carry propagation
          barrier in residue to binary conversion for the {2n, 2n−1, 2n+1}module set,” IEEE Trans. Circuits Syst.
          II, vol. 45, pp. 998–1002.
    [21]. P.V.A. Mohan,(2008) “New reverse converters for the moduli set {2n−3, 2n−1, 2n+1, 2n+3},” Elsevier
          Journal of Electronics and Communications (AEU), vol. 62, no. 9, pp. 6 658.
                                                                                 643-658.
    [22]. P. V. A. Mohan and A. B. Premkumar, (2007) “RNS-to-Binary Converters for Two Four
                                                                      Binary                     Four-Moduli Set
          {2n–1, 2n, 2n+1, 2n+1–1} and {2n–1, 2n, 2n+1, 2n+1+1},”IEEE Transactions on Circuits and Systems-I,
                                 1}
          vol. 54, no. 6, pp. 1245-1254.
                                    1254.
    [23]. Mohammad Esmaeildoust, Keivan Navi, MohammadReza Taheri, Amir Sabbagh Molahosseini and
          Siavash Khodambashi, (2012) “Efficient RNS to binary converters for the new 4         4-moduli set {2n,
           n+1      n      n–1
          2 –1, 2 –1, 2 –1}”, IEICE Electron. Express Vol. 9, No. 1, pp.1-7.
                                                   Express,
    [24]. Arash Hariri, Keivan Navi and Reza Rastegar, (2008)“A new high dynamic range moduli set with
                                                                    “A
          efficient reverse converter”, International Journal of Computers and Mathematics with Applications,
          Elsevier, vol. 55 n.4, p.660
                                 p.660-668.
    [25]. B. Cao, C. H. Chang and T. Srikanthan, (2003) “An Efficient Reverse Converter for the 4
                                                                     cient                           4-Moduli Set
          {2n–1, 2n, 2n+1, 22n+1} Based on the New Chinese Remainder Theorem,” IEEE Transactions on
          Circuits and Systems-I, vol. 50, no. 10, pp. 1296
                                 I,                    1296-1303.
    [26]. A. A. Hiasat, (2005) “VLSI implementation of New Arithmetic Residue to Binary decoders,” IEEE
                                                                             Residue
          Transactions on VLSI Systems, vol. 13, no. 1, pp. 153153-158.


    Authors

Mohammadreza Taheri received B        B.Sc. degree in hardware engineering from
Isfahan University, Iran, in 2007, and the M.Sc degree at the Science and Research
                                           M.Sc.
University branch of IAU, Tehran, Iran, in 2011 in computer system architecture.
He is currently research assistance in Microelectronic Laboratory of Shahid
Beheshti University, Tehran, Iran. His research interests include Cryptography,
Computer Arithmetic with emphasis on Residue Number System and VLSI
modeling and design of ultra-low power arithmetic circuits.
                              low



Abdolreza Pirhoseinlo was born in Tehran, Iran, in 1977. He received the B.Sc.
degree from Islamic Azad University (IAU), Arak Branch (Arak, Iran) in 2002. He
                          University
is M.Sc. student in Computer Architecture at IAU, Arak Branch. He is working on
computer arithmetic especially on residue number system.




Mojtaba Esmaeildoust is B.Sc. student in hardware engineering in University of
                                                                 University
Guilan since 2009. His research interests include VLSI design, and public key
cryptography with emphasis on elliptic curve cryptography.




Mohammad Esmaeildoust is Ph.D. candidate in Computer architecture at Shahid
Beheshti University of Technology (Tehran, Iran). He received his M.Sc. degree in
Computer architecture at Shahid Beheshti University of Technology (Tehran, Iran)
in 2008. He received his B.Sc. degree in 2006 from shahed University in Hardware
Engineering. His research interests include public key cryptography, reconfigurable
           .
computing, VLSI design, and computer arithmetic especially on residue number
system.



     36                                                                         Vol. 3, Issue 2, pp. 26-37
International Journal of Advances in Engineering & Technology, May 2012.
©IJAET                                                             ISSN: 2231-1963
Keivan Navi received the B.Sc. and M.Sc. degrees in computer hardware
engineering from Beheshti University, Tehran, Iran, in 1987 and Sharif University
of Technology, Tehran, Iran, in 1990, respectively. He also received the Ph.D.
degree in computer architecture from Paris XI University, Paris, France, in 1995.
He is currently Associate Professor in faculty of electrical and computer
engineering of Beheshti University. His research interests include VLSI design,
single electron transistors (SET), carbon nano tube, computer arithmetic,
interconnection network and quantum computing. He has published over 70 ISI
and research journal papers and over 70 IEEE, international and national conference paper.




     37                                                                 Vol. 3, Issue 2, pp. 26-37

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HIGH SPEED REVERSE CONVERTER FOR HIGH DYNAMIC RANGE MODULI SET

  • 1. International Journal of Advances in Engineering & Technology, May 2012. ©IJAET ISSN: 2231-1963 HIGH SPEED REVERSE CONVERTER FOR HIGH DYNAMIC RANGE MODULI SET MohammadReza Taheri1, Abdolreza Pirhoseinlo2, Mojtaba Esmaeildoust3, Mohammad Esmaeildoust4, Keivan Navi4 1 Microelectronic Laboratory of Shahid Beheshti University, GC, Tehran, Iran 2 Department of Computer Engineering, Islamic Azad University, Arak, Iran 3 Computer Engineering Department, Faculty of Engineering, University of Guilan, Iran 4 Faculty of Electrical and Computer Engg., Shahid Beheshti University, GC, Tehran, Iran ABSTRACT In this paper a new reverse converter architecture for the five moduli set {2n, 2n/2-1, 2n/2+1, 2n+1, 22n-1-1} is presented. The proposed converter is designed in two levels architecture by using of New Chinese Reminder Theorem-I (New CRT-I) and Mixed Radix Conversion (MRC). The proposed architecture has achieved significant improvement in terms of delay of the reverse converter compared to state-of-the-art reverse converters. KEYWORDS: Residue Number System, Digital Circuits, Residue Arithmetic, Reverse Converter I. INTRODUCTION The residue number system is non-weighted number systems. Using this property has the advantages such as carry free operations, parallelism, fault tolerance and low power design in very large scale integration technology [1]. Speed up arithmetic operation in residue number system obtains by decomposing large binary operation into smaller residues. Therefore large number computations are replaced by smaller parallel operations. During the past decade, RNS has been widely used in the applications which requires intensive computation such image processing [2-3], Digital Signal Processing[4-6], and cryptography [7-9]. RNS based processors, unlike the binary systems,bear the extra cost of two components. These two components are the binary-to-residue (forward)and residue- to-binary (reverse) converters. Forward converter, converts thebinary number into its equivalent residues and reverse converter, converts the residues into their equivalent weighted number. Arithmetic unit is the core of RNS which performs arithmetic operations required by the application in parallel without carry propagation between residues digits. Reverse converter is a difficult process that affects the performance of the RNS. Form of the moduli set and number of moduli that chosen for RNS processor affects on dynamic range, speed and its VLSI implementation [10]. Different moduli set have been suggested for RNS. Most popular moduli set for past decade was {2n, 2n-1, 2n +1} where efficient reverse converter for this moduli set reported in [11]. For more parallelism four and five moduli sets are presented such as {2n, 2n–1, 2n+1, 22n+1–1}, {22n, 2n–1, 2n+1, 22n+1}[12], {2n, 2n–1, 2n+1, 2n+1–1, 2n–1–1} [13], {2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1–1} [14] and {2n, 2n/2–1, 2n/2+1, 2n+1, 22n+1–1} [15] are presented. Among the five moduli sets, moduli set {2n, 2n–1, 2n+1, 2n+1–1, 2n–1–1} enjoys well formed moduli with efficient arithmetic operation. The reverse converter for this moduli set has very high latency and hardware costbecause of inefficient multiplicative inverses. In order to achieve better trade-off between efficiency of arithmetic operation and reverse converter, other unbalanced moduli sets {2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1–1} [14] and {2n, 2n/2–1, 2n/2+1, 2n+1, 22n+1–1} 26 Vol. 3, Issue 2, pp. 26-37
  • 2. International Journal of Advances in Engineering & Technology, May 2012. ©IJAET ISSN: 2231-1963 [15] with very simple hardware implementations of their reverse converter with higher speed compared to [13] are presented. In this paper another design of reverse converter for the five moduli set {2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1– 1} is presented. Two level designs are used in designing the proposed architecture by using New CRT-I and MRC for first and second level design, respectively. The proposed adder-based reverse converter has achieved faster implementation compared to other five moduli sets. This paper is organized as follow, in section II the background of RNS is reviewed, in next section new reverse converter in two levels design for mentioned moduli set is proposed, in forth section hardware implementation of proposed reverse converter is represented and finally section V concludesthe paper. II. PREVIOUS WORKS Different moduli set have been proposed for RNS. Three moduli set {2n, 2n–1, 2n+1} was the most popular moduli set in the past decade which different reverse converters for this moduli set is reported in [16-20]. The best hardware implementation of the reverse converter for this moduli set is reported in [11]. In this report, three different design of residue to binary converters for the moduli set {2n, 2n– 1, 2n+1} by using n-bit and 2n-bit adders are presented. Converter which is based on 2n-bit adder requires near half hardware area and better delay in comparison with previous works in this class of moduli set. The dynamic range of this moduli set is not qualified for applications which require larger dynamic range with more parallelism. Therefore another class of moduli set with more moduli or more dynamic range or both is reported in literatures. One of these approach is four moduli sets with 4n-bit dynamic range like {2n–3, 2n+1, 2n–1, 2n+3} [21], {2n–1, 2n, 2n+1, 2n+1–1} and {2n–1, 2n, 2n+1, 2n+1+1} [22], {2n, 2n+1–1, 2n–1, 2n–1–1}[23]. In [21], three different design of the reverse converters for the moduli set {2n–3, 2n+1, 2n–1, 2n+3} are reported. The first design does not need any ROM and designed by adder base structure whereas others need ROM as well as combinational logic. In [22], two residue to binary converters for the two moduli set {2n–1, 2n, 2n+1, 2n+1–1} and {2n–1, 2n, 2n+1, 2n+1+1} are presented. The reverse converter of these moduli set are designed by MRC technique which apply on the two moduli set {{2n, 2n–1, 2n+1}, 2n+1–1} and {{2n, 2n–1, 2n+1}, 2n+1–1}, respectively. The hardware cost is more economical than previous methods. Also residue to binary conversion delay also is reduced in this design. Efficient designs of residue to binary converter for the moduli set {2n, 2n+1–1, 2n–1, 2n–1–1} is reported in [23]. This moduli set is completely free from modulo 2k+1 type which results in high-speed modulo arithmetic. MRC algorithm is used to design residue to binary converter architectures. In [24], three moduli set {2n, 22n–1, 22n+1} with 5n-bit dynamic range is presented. Chinese Remainder Theorem is used for design reverse converter for this moduli set. Simple hardware implementation by using only one CSA followed by a 4n bit modulo 24n 1 adder, and a few gates, results in remarkable delay of reverse conversion. In [25], reverse − converter for mosuli set {2n–1, 2n, 2n+1, 22n+1} with efficiency in delay conversion and hardware cost of its implementation with using CRT algorithm is presented. The disadvantage of these two moduli sets reported in [24-25] is use of modulo 22n+1 which increase the latency of the RNS arithmetic unit. For overcome this problem moduli set {2n–1, 2n, 2n+1, 22n+1–1}[12] is presented. In this work, New CRT-II is employed for designing an efficient reverse conversion. In class of five moduli with 5n-bit dynamic range, moduli set such as {2n, 2n–1, 2n+1, 2n–2(n+1)/2 +1,2n+2(n+1)/2+1}[26], {2n, 2n–1, 2n+1, 2n+1–1, 2n–1–1}[13], {2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1–1} [14] and {2n, 2n/2–1, 2n/2+1, 2n+1, 22n+1–1} [15] are presented. In [26] with using CRT, a full adder based reverse converter presented for the moduli set {2n, 2n–1, 2n+1, 2n–2(n+1)/2 +1, 2n+2(n+1)/2+1}. The problem of this moduli system is that the speed of the arithmetic unit of RNS is restricted to the low-performance modulo 2n+2(n+1)/2+1. Cao et al. [13] proposed balanced and well-formed moduli set {2n, 2n–1, 2n+1, 2n+1–1, 2n–1–1} with efficient RNS arithmetic unit. In other hand the dynamic range of this moduli set are sufficient for today’s necessity. The only disadvantage of this moduli set is its complex reverse converter due to inefficient forms of multiplicative inverse that lead to increasing the cost and the delay of reverse converter. Unbalanced moduli sets {2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1–1} and {2n, 2n/2–1, 2n/2+1, 2n+1, 22n+1–1} with very simple hardware implementations of their reverse converter with higher speed compared to [13] and [26]. These moduli sets provides better trade-off between efficiency of arithmetic operation and reverse converter are presented. 27 Vol. 3, Issue 2, pp. 26-37
  • 3. International Journal of Advances in Engineering & Technology, May 2012. ©IJAET ISSN: 2231-1963 III. RELATED BACKGROUND Chinese Reminder Theorem (CRT)converts an RNS number into its equivalent weighted Number as follows: n X = ∑xN i =1 i i Pi M i (1) M Where M = P1 P2 ...Pn Pn , M i = M / Pi N i = M i−1 Pi The CRT can be implemented in parallel channels followed by a modulus M adder.Modulo M reduction has very large latency and this can leads to inefficient hardware implementation of the reverse converter for high dynamic range moduli sets. The weighted number X can be computed by New CRT-I as follows: k 1 ( x 2 − x 1 ) + k 2 P2 ( x 3 − x 2 ) + ... X = x 1 + P1 × (2) + k n −1P2 P3 ...Pn −1 ( x n − x n −1 ) P2 P3 ...Pn Where k1 × P P P ... P = 1 1 2 3 n k 2 × P × P2 P ... P = 1 1 3 n kn−1 × P × P2 × ... × Pn−1 P = 1 1 n Compared to CRT, the size of the final modulo reduction is reduced in New CRT-I. Mixed Radix Conversion (MRC) is another algorithm to convert the residues into the weighted number. To calculate Xfrom its residues by MRC, we have n −1 X = vn ∏ Pi + ... + v3 P2 P + v2 P + v1 1 1 (3) i =1 The coefficients vis can be obtained from residues by v1 = x1 (4) −1 v2 = ( x2 − v1 ) P1 (5) P2 P 2 −1 −1 v3 = (( x3 − v1 ) P1 − v2 ) P2 (6) P3 P3 P 3 In the general case, we have −1 −1 −1 vn = ((( x n − v1 ) P1 P − v 2 ) P2 P − ⋅ ⋅ ⋅ − v n −1 ) Pn −1 P (7) n n n Pn P1−1 indicates the multiplicative inverse of Pj modulus Pj . Pj IV. REVERSE CONVERTER DESIGN In order to efficient design of reverse converter for the moduli set{2n, 2n/2–1, 2n/2+1, 2n+1, 22n–1–1}, two levels of design are employed. First level is designed by using New CRT-I and considering 28 Vol. 3, Issue 2, pp. 26-37
  • 4. International Journal of Advances in Engineering & Technology, May 2012. ©IJAET ISSN: 2231-1963 subset{2n/2–1, 2n/2+1, 2n+1, 22n–1–1}and in second level subset {(2n/2–1)( 22n–1–1), 2n} is designed by using MRC. 3.1. First Level Design In order to calculate the weighted number Z from its residues in subset {2n/2–1, 2n/2+1, 2n+1, 22n–1–1} by using New CRT-I, we have Z = x1 + P k1 ( x2 − x1 ) + k2 P2 ( x3 − x2 ) + k3 P2 P3 ( x4 − x3 ) P P P 1 (8) 2 3 4 n n By considering P = 2 2 n −1 − 1, P2 = 2n + 1, P3 = 2 2 + 1, P4 = 2 2 − 1 , we have 1 2 n −1 k 1 (x 2 − x 1 ) + k 2 (2n + 1)(x 3 − x 2 ) + Z = x 1 + (2 − 1) n (9) k 3 (2n + 1)(2 2 + 1)(x 4 − x 3 ) 22 n −1 For the required multiplicative inverse in Eq. 9,we have k 1 × (2 2 n −1 − 1) 22 n −1 = 1 → k 1 = −2 k 2 × (2 2 n −1 − 1)(2 n + 1) 2n −1 = 1 → k 2 = −1 n n −1 2 n −1 n k3 × (2 − 1)(2 + 1)(2 + 1) 2 n 2 −1 = 1 → k3 = −2 2 2 Eq. 9 can be rewritten as Z = x 1 + (22n −1 − 1)Y (10) To calculate Y we have (−2)( x2 − x1 ) + ( −1)(2n + 1)( x3 − x2 ) + Y= n n (11) (−2 2 −1 )(2n + 1)(2 2 + 1)( x4 − x3 ) 2 2n −1 Eq. 11 can be rewrite as Y = Z 1 + Z 2 + Z 3 22 n −1 (12) Where Z 1 = ( −2)( x 2 − x 1 ) 22 n −1 Z 2 = ( −1)(2n + 1)( x3 − x2 ) 22 n −1 2 −1 n n Z3 = (−2 )(2 n + 1)(2 2 + 1)( x 4 − x 3 ) 2 2 n −1 By considering x1 = x1,2 n −2 K x1,0 , x2 = x2,n K x2,0 , x3 = x3, n K x3,0 and x4 = x4, n K x4,0 , for Z1 we 2 2 −1 have Z1 = 2 × ( x1 − x2 ) 22 n −1 (13) Z1 = 2 × ( x1,2 n − 2 K x1,0 − x2,n K x2,0 ) 22 n −1 (14) 29 Vol. 3, Issue 2, pp. 26-37
  • 5. International Journal of Advances in Engineering & Technology, May 2012. ©IJAET ISSN: 2231-1963   Z1 = 2 ×  0 x1,2 n − 2 K x1,0 − 0L3 x2, n K x2,0  1 2 00 (15)    ( n −1)bit  22 n −1 Z1 = x1,2 n −2 K x1,0 0 + 11...1 x2,n K x2,01 { (16) ( n − 2 )bit 2n 2 −1 Z 1 = Z 11 + Z 12 22 n −1 (17) Where Z 11 = x 1,2n −2 ...x 1,0 0 Z12 = 11L1 x2, n K x2,01 { ( n − 2 )bit For Z2 we have Z 2 = −(2n + 1)( x3 − x2 ) (18) 22 n −1     ( ) Z 2 = − 2n + 1  00L 0 x3, n 2 K x3,0 − 00L 0 x2,n K x2,0  1 3 2 1 3 2 (19)   3 n−1bit  ( n −1)bit  2    22 n −1 x2,n −1 K x2,0 00L 0 x2,n + 00L 0 x2,n K x2,0 − 1 3 2 1 3 2 ( n −1)bit ( n −1)bit Z2 =   (20)    00L 0 x3, n K x3,0 00L 0 + 00L 0 x3, n 2 K x3,0  1 3 2 2 1 3 1 3 2 2  ( n 2 −1)bit n bit 3   n −1bit   2   22 n −1 x2,n −1 K x2,0 00L 0 x2,n + 00L 0 x2, n K x2,0 + 1 3 2 1 3 2 ( n −1)bit ( n −1)bit Z2 = 11L1 x3, n K x3,0 11L1 x3, n 2 K x3,0 { 2 {1 24 (21) n  4 3 n   −1bit  −1bit n  2  2   +1 bit 2  22 n −1 Therefore Z 2 = Z 21 + Z 22 + Z 23 2 2 n −1 (22) Where Z 21 = x2,n −1 K x2,0 00L 0 x2,n 1 3 2 ( n −1)bit 22 n −1 Z 22 = 00L 0 x2,n K x2,0 1 3 2 ( n −1)bit 22 n −1 30 Vol. 3, Issue 2, pp. 26-37
  • 6. International Journal of Advances in Engineering & Technology, May 2012. ©IJAET ISSN: 2231-1963 Z 23 = 11L1 x3, n K x3,0 11L1 x3, n 2 K x3,0 { 2 {1 24 n  n  4 3  −1bit  −1bit n  2  2   +1bit 2  22 n −1 For Z3 we have Z3 = (−2 2 −1 )(2n + 1)(2 2 + 1)( x4 − x3 ) n n (23) 22 n −1 n n ( Z3 = (−2 2 −1 )(2n + 1)(2 2 + 1) x4, n 2 −1 K x4,0 − x3, n 2 K x3,0 ) 22 n −1 (24)  2n + 1 x4,n −1 K x4,0 x4, n −1 K x4,0 − ( )(  )  2 2     −2 2 −1 ×   n   n Z3 =  (25)   2 2 + 1  00L 0 x3,n K x3,0 00L 0 x3, n K x3,0   1 3 2 2 1 3 2 2       n -1 bit n   -1 bit    2    2   2 2 n −1  − x4 x4 x4 x4 + x n K x3,0 00L 0 x3 00L 0 x3, n 2  1 3 1 3 2 2  3, −1 2 n  n   n −1   -1 bit 2   -1 bit 2   2 2 ×  (26) Z3 = + 00L 0 x3, n 2 K x3,0 00L 0 x3, n 2 K x3,0  1 32 1 32   n   -1 bit n   -1 bit   2  2   2 2 n −1 x 4,0 x4 x4 x4 x n K x4,1 + x3,0 00L 0 x3 00L 0 x3,n 2 K x3,1 1 3 1 3 2 2 4, −1 2 n  n   -1 bit  -1 bit Z3 = 2  2  (27) + x3,n 2 K x3,0 00L 0 x3,n 2 K x3,0 00L 0 1 3 2 1 3 2 n  n   -1 bit  -1  bit 2  2  2 2 n −1 Z 3 = z31 + z32 + z33 22 n −1 (28) where Z31 = x 4,0 x4 x4 x4 x n K x4,1 4, −1 2 Z 32 = x3,0 00L 0 x3 00L 0 x3, n 2 K x3,1 1 3 1 3 2 2 n  n   -1  bit  -1  bit 2  2  Z 33 = x3, n 2 K x3,0 00L 0 x3, n 2 K x3,0 00L 0 1 3 2 1 3 2 n  n   -1 bit  -1 bit 2  2  31 Vol. 3, Issue 2, pp. 26-37
  • 7. International Journal of Advances in Engineering & Technology, May 2012. ©IJAET ISSN: 2231-1963 Therefore Y can be calculated as Y = z11 + z12 + z21 + z22 + z23 + z31 + z32 + z33 22 n −1 (29) Hardware implementation ofEq. 29 is shown in figure 1. Bit organizer provides the required operands in Eq. 29. Carry Save Adders (CSA) with End Around Carry (EAC) are used to reduce the number of operands and then Modulo 22n–1 Adder (MA (22n–1)) is employed to calculate the Y. Figure 1. Hardware implementation of Y After calculation of Y, to realize Z we have Z = x 1 + (22 n −1 − 1)Y (30) Z = x1 + Y 00L 0 − Y 1 3 2 (31) ( 2 n −1)bit Z = Y x 1 −Y (32) 3.2. Second Level Design Second level of the design consider the moduli set {(22n–1)( 22n–1–1), 2n} by using MRC. Considering P1234 = (22n–1)( 22n–1–1) and using MRC we have x = v 1 + v 2 p1234 (33) v1 = Z (34) v2 = ( x5 − z ) P −1 1234 (35) 2n 2n 32 Vol. 3, Issue 2, pp. 26-37
  • 8. International Journal of Advances in Engineering & Technology, May 2012. ©IJAET ISSN: 2231-1963 For the required multiplicative inverses, we have P −1 1234 → k (22 n − 1)(22 n −1 − 1) =1 2n 2n P−1 1234 =1 2n Therefore v2 = x5 − Yx1 + Y 2n (36) Eq. 36 can be rewritten as v2 = x5, n −1 K x5,0 − Y2 n −1 K Y0 x1,2 n − 2 K x1,0 + Y2 n −1 KY0 2n (37) v2 = x5,n −1 K x5,0 − x1n −1 K x1,0 + Yn −1 K Y0 2n (38) v2 = x5 + v21 + v22 + 1 2n (39) Where v21 = x1,n −1 K x1,0 v22 = Yn−1 KY0 Therefore X = v 1 + v 2 (22 n − 1)(22 n −1 − 1) (40) X = Yx1 − Y + (v2 00L 0 − v2 )(2 2 n −1 − 1) 1 3 2 (41) 2 n bit X = Yx1 − Y + v2 00L 0 − v2 00L 0 − v2 00L 0 + v2 1 3 2 1 3 2 1 3 2 (42) 4 n −1 bit 2 n bit 2 n −1 bit X = v2Yx1 + v2Y + v211L1 + 2 + v2 (43) X = v 2Y x 1 + v 2Y + v 2 00L 0 + v 2 + 1 + 100L 0 1 3 2 (44) 2n X = v 2Y x 1 + v 2Y + v 2 00L 0v 2 + 1 0L 0 1 1 3 2 { (45) ( n −1)bit ( 2 n −1)bit K 1 = v 2Y x 1 (46) K 2 = v 2Y (47) K 3 = v2 00 L 0 v2 1 3 2 (48) ( n −1)bit K 4 = 1 0L 0 1 { (49) ( 2 n −1)bit 33 Vol. 3, Issue 2, pp. 26-37
  • 9. International Journal of Advances in Engineering & Technology, May 2012. ©IJAET ISSN: 2231-1963 Therefore X = K1 + K 2 + K 3 + K 4 (50) Hardware implementation of X is shown in figure 2. First v2 in Eq. 39 is implemented by using an n bit CSA followed by the Carry Propagate Adder (CPA). Then bit organizer in figure 2, provides the required shift and negation required in Eq. 46-49. In next step, two CSA followed by the CPA calculate the final result of X according to Eq. 50. Figure 2. Hardware implementation of X Table 1. Delay and area comparison of five moduli sets reverse converters Converter Hardware requirements Conversion delay [13] ((5n2+43n+m* )/6+16n–1)AFA +(6n+1)ANOT (18n+L*+7)tFA (10n+5)AFA+(7n–5)AXNOR [14] +(7n–5)AOR +(2n–3)AXOR (13n+1)tFA+3tNOT +(2n–3)AAND+(8n+2)ANOT (12.5n+6)AFA+(4.5n–1)AXNOR [15] +(4.5n–1)AOR + (1.5n–1)AXOR (12n+6)tFA+3tNOT +(1.5n–1)AAND+(7n+1)ANOT (17n +n/2+2)AFA+(4n)AXNOR Proposed +(4n)AOR +(8n–5)AXOR (10n+ 6)tFA +(8n–5)AAND+(7n/2)ANOT V. COMPARISON Details of area and delay comparisons of the proposed reverse converter for the moduli set {22n–1–1, 2n+1, 2n/2–1, 2n/2+1, 2n} with other five moduli sets reported in [13], [14] and [15] are shown in table 1. In order to achieve fair comparison, in calculations of delay and area, assumptions such as considered in [14-15] are employed. According to the obtained result in table 1, the proposed converter has (10n+6)tFA, where tFA denotes the delay of one bit full adder. The reverse converter 34 Vol. 3, Issue 2, pp. 26-37
  • 10. International Journal of Advances in Engineering & Technology, May 2012. ©IJAET ISSN: 2231-1963 proposed in [13] has the delay of (13n+1)tFA. Therefore the proposed converter for the moduli set {22n+1–1, 2n+1, 2n/2–1, 2n/2+1, 2n} with different levels of the design compared to [14] achieved in more speed in reverse conversion.Comparison with other five moduli sets are shown in table 1. It can be seen that the proposed reverse converter for the moduli set {22n+1–1, 2n+1, 2n/2–1, 2n/2+1, 2n} has achieved fastest implementation compared to other five moduli reverse converters. VI. CONCLUSION We have presented a simple and efficient reverse converter architecture for the five moduli set {22n+1– 1, 2n+1, 2n/2–1, 2n/2+1, 2n}. Two levels design, New CRT-I for subset {2n/2–1, 2n/2+1, 2n+1, 22n–1–1} and MRC for superset {(22n–1)( 22n–1–1), 2n} are employed. Higher speed of the reverse converter has achieved compared to other five moduli set reverse converters in literature. REFERENCES [1]. K. Navi, A. S. Molahosseini, M. Esmaeildoust, (2011) "How to Teach Residue Number System to Computer Scientists and Engineers," IEEE Transactions on Education, Vol. 54, Issue. 1, pp. 156-163. [2]. W. Wei et al., (2004)“RNS application for digital image processing,” Proceedings of the 4th IEEE international workshop on system-on-chip for real time applications. pp. 77 - 80. [3]. A. Ammar, A. Al kabbany, M. Youssef, and A. Emam, (2001)“A secure image coding using residue number systems,” Proc. of the 18th National Radio Science Conference. [4]. G.C. Cardarilli, A. Nannarelli and M. Re, (2007) “Residue Number System for Low-Power DSP Applications,” Proc. of 41nd IEEE Asilomar Conference on Signals, Systems, and Computers. [5]. R. Conway and J. Nelson, (2004) “Improved RNS FIR Filter Architectures,” IEEE Transactions on Circuits and Systems-II, Vol. 51, No. 1, pp. 26-28. [6]. W. K. Jenkins and B. J. Leon, (1977) “The use of residue number systems in the design of finite impulse response digital filters,” IEEE Transactions on Circuits and Systems, vol. CAS-24, pp. 191– 201. [7]. J. C. Bajard, L. Imbert, (2004) "A Full RNS Implementation of RSA," IEEE Transactions on Computers, vol. 53, no. 6, pp. 769-774. [8]. Marzie Gerami, Mohammad Esmaeildoust, Shirin Rezaei, Keivan Navi and Omid Hashemipour, (2011) “Four Moduli RNS Bases for Efficient Design of Modular Multiplication,” Journal of Computations & Modelling, vol.1, no.2, 73-96. [9]. D. M. Schinianakis, A. P. Fournaris, H. E. Michail, A. P. Kakarountas, andT. Stouraitis, (2009) “An RNS Implementation of an Fp Elliptic CurvePoint Multiplier”, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—I, VOL. 56, NO. 6. [10]. K. Navi, M. Esmaeildoust, and A. S. Molahosseini, (2011) "A General Reverse Converter Architecture with Low Complexity and High Performance," IEICE Transactions on Information and Systems, Vol. E94-D, No.2, pp. 264-273. [11]. Y. Wang, X. Song, M. Aboulhamid and H. Shen, (2002) “Adder based residue to binary numbers converters for (2n–1, 2n, 2n+1),”IEEE Transactions on Signal Processing, vol. 50, no. 7, pp. 1772-1779. [12]. A. S. Molahosseini, K. Navi, C. Dadkhah, O. Kavehei and S. Timarchi, (2010) " Efficient Reverse Converter Designs for the new 4-Moduli Sets {2n–1, 2n, 2n+1, 22n+1–1} and {2n–1, 2n+1, 22n, 22n+1} Based on New CRTs," IEEE Transaction on Circuit and System I, Vol. 57, No. 4, pp. 823-835. [13]. B. Cao, C.H. Chang and T. Srikanthan, (2007) “A Residue-to-Binary Converter for a New Five- Moduli Set,”IEEE Transactions on Circuits and Systems-I, vol. 54, no. 5, pp.1041–1049. [14]. A.S. Molahosseini, C. Dadkhah, K. Navi, (2009) “A New Five-Moduli Set for Efficient Hardware Implementation of the Reverse Converter,” IEICE Electronics Express, vol. 6, no. 14, pp. 1006-1012. [15]. Mohammad Esmaeildoust, Keivan Navi and MohammadReza Taheri, (2010) “High speed reverse converter for new five-moduli set {2n, 22n+1–1, 2n/2–1, 2n/2+1, 2n+1}”, IEICE Electron. Express, Vol. 7, No. 3, pp.118-125. [16]. D. Gallaher, F. Petry, and P. Srinivasan, (1997) “The digital parallel method for fast RNS to weighted number system conversion for specific moduli {2n, 2n−1, 2n+1},” IEEE Trans. Circuits Syst. II, vol. 44, pp. 53–57. [17]. S. Piestrak,(1995) “A high-speed realization of a residue to binary number system converter,” IEEE Trans. Circuits Syst. II, vol. 42. [18]. R. Conway and J. Nelson,(1999) “Fast converter for 3 moduli RNS using new property of CRT,” IEEE Trans. Comput., vol. 48, pp. 852–860. [19]. B. Vinnakota and V. V. B. Rao,(1994) “Fast conversion techniques for binary-residue number systems,” IEEE Trans. Circuits Syst. I, vol. 41, pp. 927–929. 35 Vol. 3, Issue 2, pp. 26-37
  • 11. International Journal of Advances in Engineering & Technology, May 2012 2012. ©IJAET ISSN: 2231-1963 [20]. M. Bhardwaj, A. B. Premkumar, and T. Srikanthan, (1998) “Breaking the 2n 2n-bit carry propagation barrier in residue to binary conversion for the {2n, 2n−1, 2n+1}module set,” IEEE Trans. Circuits Syst. II, vol. 45, pp. 998–1002. [21]. P.V.A. Mohan,(2008) “New reverse converters for the moduli set {2n−3, 2n−1, 2n+1, 2n+3},” Elsevier Journal of Electronics and Communications (AEU), vol. 62, no. 9, pp. 6 658. 643-658. [22]. P. V. A. Mohan and A. B. Premkumar, (2007) “RNS-to-Binary Converters for Two Four Binary Four-Moduli Set {2n–1, 2n, 2n+1, 2n+1–1} and {2n–1, 2n, 2n+1, 2n+1+1},”IEEE Transactions on Circuits and Systems-I, 1} vol. 54, no. 6, pp. 1245-1254. 1254. [23]. Mohammad Esmaeildoust, Keivan Navi, MohammadReza Taheri, Amir Sabbagh Molahosseini and Siavash Khodambashi, (2012) “Efficient RNS to binary converters for the new 4 4-moduli set {2n, n+1 n n–1 2 –1, 2 –1, 2 –1}”, IEICE Electron. Express Vol. 9, No. 1, pp.1-7. Express, [24]. Arash Hariri, Keivan Navi and Reza Rastegar, (2008)“A new high dynamic range moduli set with “A efficient reverse converter”, International Journal of Computers and Mathematics with Applications, Elsevier, vol. 55 n.4, p.660 p.660-668. [25]. B. Cao, C. H. Chang and T. Srikanthan, (2003) “An Efficient Reverse Converter for the 4 cient 4-Moduli Set {2n–1, 2n, 2n+1, 22n+1} Based on the New Chinese Remainder Theorem,” IEEE Transactions on Circuits and Systems-I, vol. 50, no. 10, pp. 1296 I, 1296-1303. [26]. A. A. Hiasat, (2005) “VLSI implementation of New Arithmetic Residue to Binary decoders,” IEEE Residue Transactions on VLSI Systems, vol. 13, no. 1, pp. 153153-158. Authors Mohammadreza Taheri received B B.Sc. degree in hardware engineering from Isfahan University, Iran, in 2007, and the M.Sc degree at the Science and Research M.Sc. University branch of IAU, Tehran, Iran, in 2011 in computer system architecture. He is currently research assistance in Microelectronic Laboratory of Shahid Beheshti University, Tehran, Iran. His research interests include Cryptography, Computer Arithmetic with emphasis on Residue Number System and VLSI modeling and design of ultra-low power arithmetic circuits. low Abdolreza Pirhoseinlo was born in Tehran, Iran, in 1977. He received the B.Sc. degree from Islamic Azad University (IAU), Arak Branch (Arak, Iran) in 2002. He University is M.Sc. student in Computer Architecture at IAU, Arak Branch. He is working on computer arithmetic especially on residue number system. Mojtaba Esmaeildoust is B.Sc. student in hardware engineering in University of University Guilan since 2009. His research interests include VLSI design, and public key cryptography with emphasis on elliptic curve cryptography. Mohammad Esmaeildoust is Ph.D. candidate in Computer architecture at Shahid Beheshti University of Technology (Tehran, Iran). He received his M.Sc. degree in Computer architecture at Shahid Beheshti University of Technology (Tehran, Iran) in 2008. He received his B.Sc. degree in 2006 from shahed University in Hardware Engineering. His research interests include public key cryptography, reconfigurable . computing, VLSI design, and computer arithmetic especially on residue number system. 36 Vol. 3, Issue 2, pp. 26-37
  • 12. International Journal of Advances in Engineering & Technology, May 2012. ©IJAET ISSN: 2231-1963 Keivan Navi received the B.Sc. and M.Sc. degrees in computer hardware engineering from Beheshti University, Tehran, Iran, in 1987 and Sharif University of Technology, Tehran, Iran, in 1990, respectively. He also received the Ph.D. degree in computer architecture from Paris XI University, Paris, France, in 1995. He is currently Associate Professor in faculty of electrical and computer engineering of Beheshti University. His research interests include VLSI design, single electron transistors (SET), carbon nano tube, computer arithmetic, interconnection network and quantum computing. He has published over 70 ISI and research journal papers and over 70 IEEE, international and national conference paper. 37 Vol. 3, Issue 2, pp. 26-37