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FPGA BASED IMPLEMENTATION OF A
DOUBLE PRECISION IEEE FLOATING-
         POINT ADDER


                 Presented By
              Somsubhra Ghosh
        Dept. of Electrical Engineering
         JADAVPUR UNIVERSITY
               Kolkata - 700032




                                          1
OUTLINE

 General Structure.
 Simple arithmetic operation of the double precision
floating-point numbers.
 Proposed algorithm .
 Implementation of the algorithm on FPGA.
 Detailed illustration of the first cycle of the algorithm.
 Discussions and simulation results.
 Conclusions.
 References.




                                                               2
GENERAL STRUCTURE
General representation of IEEE 754-2008 double precision floating-point
numbers.



             0                   1-11                  12-64
        (length = 1)         (length = 11)         (length = 52)
          Sign(S)            Exponent(E)          Significand(F)




                                                                          3
SIMPLE ARITHMETIC OPERATION OF THE
  DOUBLE PRECISION FLOATING-POINT
             NUMBERS
•   The required operation is performed by the following formula:



           rnd (sum) rnd (( 1)sa 2ea fa ( 1)( SOP       sb )
                                                               2eb fb)

     where

                S.EFF         sa     sb      SOP
     So,

             sum ( 1)sl 2el ( fl ( 1)S .EFF ( fs 2 | ))


                                                                         4
PROPOSED ALGORITHM
                         •   Two staged pipelined process.

                                                  •     First cycle:
                                                         1. Normalization of the inputs.
                                                         2. Determination of the effective
                                                         sign of operation.
                                                         3. Determination of the
                                                         alignment shift amount, δ or
                                                         MAG_MED signal.
                                                  •     Second cycle:
                                                         1. Addition of the Significand.
                                                         2. Rounding f the result.
                                                         3. Normalization of the result.




Fig. 1. Higher level representation of the algorithm.

                                                                                           5
IMPLEMENTATION OF THE
                 ALGORITHM ON FPGA
•     The implementation off the presented algorithm has been performed using two
      different Xilinx © products, XC2V6000 device of virtex2 family and XC3S1500 of
      spartan-3 family.

TABLE 1. ESTIMATION OF THE USAGE OF RESOURCES IN DEVICE XC2V6000.
                                 Device Utilization Summary
         Logic Utilization             Used                Available   Utilization

    Number of Slice Flip Flops         308                 67,584         0%
     Number of 4 input LUTs            932                 67,584         1%
                                      Logic Distribution
    Number of occupied Slices          546                 33,792         1%
     Total Number of 4 input
                                       932                 67,584         1%
             LUTs
     Number of bonded IOBs             195                   824          23%

       Number of GCLKs                  2                     16          12%

                                                                                       6
IMPLEMENTATION OF THE
          ALGORITHM ON FPGA (Cont.)
TABLE 2. ESTIMATION OF THE USAGE OF RESOURCES IN DEVICE XC3S1500 .

                                   Device Utilization Summary
            Logic Utilization                    Used           Available   Utilization
      Number of Slice Flip Flops                  421           26,624         1%
       Number of 4 input LUTs                     492           26,624         1%
                                          Logic Distribution
     Number of occupied Slices                    491           13,312        3%
    Total Number of 4 input LUTs                  668           26,624        2%
      Number of bonded IOBs                       39             221          17%
            IOB Flip Flops                        15
       Number of Block RAMs                        1               32         3%
         Number of GCLKs                           4               8          50%
         Number of DCMs                            2               4          50%
 Total equivalent gate count for design         89,436

 Additional JTAG gate count for IOBs             1,872



                                                                                          7
DETAILED ILLUSTRATION OF THE
  FIRST CYCLE OF THE ALGORITHM




                                                                                        FB[0:52]
                                                                 FA[0:52]

                                                                             SA

                                                                                  SOP


                                                                                                   SB
                   EA                 EB



                        FLIP FLOPS                                          ONE’S COMPLEMENT                          S.EFF



                                                          FAO[0:52]                FBO[0:52]



               ADDER (5)        ADDER (7)
                                                                             PRESHIFT


                                              SIGN_MED                                                      1     0
                XOR                                          FSOP[-1:53]                                    MUX
                                      XOR
                                                                                                                              0         1
                                                                                                                                  MUX
                                           MAG_MED[5:0]              SHIFT(63)
               ORTREE                                                                                   SHIFT(65)
                                                                                                                                   FL[0:52]


                                                                             0                          1
                             IS_BIG                                                 MUX                                       SHIFT(1)

                                                                                          FSOPA[-1:116]                            FLP[-1:52]

                           SIGN_BIG




Fig. 2. Block level representation of the 1st cycle of the algorithm.
                                                                                                                                                8
DETAILED ILLUSTRATION OF THE
FIRST CYCLE OF THE ALGORITHM
           (CONT.)




Fig. 3. Block level representation of the 2nd cycle of the algorithm.
                                                                        9
DISCUSSIONS AND SIMULATION
                RESULTS




Fig. 4. Simulation of the floating point adder at Xilinx© ISE using the: (a) Behavioral
simulation, (b) Post-route and synthesis simulation, (c) Technical schematic.
                                                                                    10
CONCLUSIONS
 The system has a minimum period of 14.081ns or a maximum frequency
  of 71.017MHz.
 This technique successfully demonstrates a very low latency and a scope
  of achieving an even lower latencies with the use of intricate and more
  complex computational techniques.
 This technique shows significant improvements over the present way of
  performing he arithmetic operations of the floating-point numbers in
  terms of latency, ease, flexibility, and robustness against errors.
 This implementation offers a faster and smarter estimation of the results
  with minimal errors and ensures minimal computational load for the
  system.
REFERENCES
 Peter-Michael Seidel, Guy Even, “Delay-Optimized Implementation of IEEE
  Floating-Point Addition”, IEEE Trans. on Computers, vol. 53, no. 2, pp. 97-
  113, Feb. 2004.
 Karan Gumber, Sharmelee Thangjam, “Performance Analysis of Floating Point
  Adder using VHDL on Reconfigurable Hardware”, International Journal of
  Computer Applications, vol. 46, no. 9, pp. 1-5, May 2012.
 N. Kikkeri, P.M. Seidel, “An FPGA Implementation of a Fully Verified Double
  Precision IEEE Floating-Point Adder”, Proc. of IEEE International Conference
  on Application-specific Systems, Architectures and Processors, pp. 83-88, 9-11
  July 2007.
 A. Tyagi, “A Reduced-Area Scheme for Carry-Select Adders”, IEEE trans. on
  Computers, vol. 42, no. 10, pp. 1163-1170, Oct. 1993.
 A. Beaumont-Smith, N. Burgess, S. Lefrere, C. Lim, “Reduced Latency IEEE
  Floating-Point Standard Adder Architectures,” Proc. of 14th IEEE Symposium
  on Computer Arithmetic, pp. 35-43, 1999.

                                                                             12
REFERENCES (Cont.)
 P. Farmwald, “On the Design of High Performance Digital Arithmetic Units,”
  PhD thesis, Stanford Univ., Aug. 1981.
 A. Nielsen, D. Matula, C. N. Lyu, G. Even, “IEEE Compliant Floating-Point
  Adder that Conforms with the Pipelined Packet-Forwarding Paradigm,” IEEE
  Trans. on Computers, vol. 49, no. 1, pp. 33-47, Jan. 2000.
 N. Quach, N. Takagi, and M. Flynn, “On fast IEEE Rounding”, Technical
  Report CSL-TR-91-459, Stanford Univ., Jan. 1991.
 P.-M. Seidel, “On The Design of IEEE Compliant Floating-Point Units and
  Their Quantitative Analysis”, PhD thesis, Univ. of Saarland, Germany, Dec.
  1999.
 P.-M. Seidel, G. Even, “How Many Logic Levels Does Floating-Point
  Addition Require?”, Proc. of International Conference on Computer Design
  (ICCD ’98): VLSI, in Computers & Processors, pp. 142-149, Oct. 1998.
 W.C. Park, T.D. Han, S.D. Kim, S.B. Yang, “Floating Point Adder/Subtractor
  Performing IEEE Rounding and Addition/Subtraction in Parallel”, IEICE
  Trans. on Information and Systems, vol. 4, pp. 297-305, 1996.

                                                                               13
REFERENCES (Cont.)
 S. Oberman, H. Al-Twaijry, and M. Flynn, “The SNAP Project: Design of
  Floating Point Arithmetic Units”, Proc. of 13th IEEE Symposium on
  Computer Arithmetic, pp. 156-165, 1997.
 S. Oberman, “Floating-Point Arithmetic Unit Including an Efficient Close
  Data Path,” AMD, US patent 6094668, 2000.
 V. Gorshtein, A. Grushin, and S. Shevtsov, “Floating Point Addition Methods
  and Apparatus.” Sun Microsystems, US patent 5808926, 1998.
 G. Even, P.M. Seidel, “A comparison of three rounding algorithms for IEEE
  floating-point multiplication”, Proc. of 14th IEEE Symposium on Computer
  Arithmetic, pp. 225-232, 1999.
 IEEE Computer Society, “IEEE Standard for Floating-Point Arithmetic”,
  IEEE Std. 754 TM-2008 (Revision of IEEE Std 754-1985), Aug. 29, 2008.
 H. D. Nguyen, B. Pasca, T. B. Preuber, “FPGA-Specific Arithmetic
  Optimizations of Short-Latency Adders,” Proc. of 21 st IEEE international
  conference on field programmable logic and applications, pp. 232 – 237,
  2011.

                                                                              14
REFERENCES (Cont.)
 C. Minchola, M. Vazquez, G. Sutter, “A FPGA IEEE-754-2008 DECIMAL64
  FLOATING-POINT ADDER/SUBTRACTOR,” Proc. of VII Southern
  conference on Programmable Logic, pp. 251 – 256, 2011.
 F. Dinechin, H. D. Nguyen, B. Pasca, “Pipelined FPGA Adders,” Proc. of
  International conference on Field Programmable Logic and applications, pp.
  422 – 427, 2010.




                                                                               15
QUESTIONS?




Polygonia interrogationis known as Question Mark
Thank You
            17

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Fpga based implementation of a double precision ieee floating point adder

  • 1. FPGA BASED IMPLEMENTATION OF A DOUBLE PRECISION IEEE FLOATING- POINT ADDER Presented By Somsubhra Ghosh Dept. of Electrical Engineering JADAVPUR UNIVERSITY Kolkata - 700032 1
  • 2. OUTLINE  General Structure.  Simple arithmetic operation of the double precision floating-point numbers.  Proposed algorithm .  Implementation of the algorithm on FPGA.  Detailed illustration of the first cycle of the algorithm.  Discussions and simulation results.  Conclusions.  References. 2
  • 3. GENERAL STRUCTURE General representation of IEEE 754-2008 double precision floating-point numbers. 0 1-11 12-64 (length = 1) (length = 11) (length = 52) Sign(S) Exponent(E) Significand(F) 3
  • 4. SIMPLE ARITHMETIC OPERATION OF THE DOUBLE PRECISION FLOATING-POINT NUMBERS • The required operation is performed by the following formula: rnd (sum) rnd (( 1)sa 2ea fa ( 1)( SOP sb ) 2eb fb) where S.EFF sa sb SOP So, sum ( 1)sl 2el ( fl ( 1)S .EFF ( fs 2 | )) 4
  • 5. PROPOSED ALGORITHM • Two staged pipelined process. • First cycle: 1. Normalization of the inputs. 2. Determination of the effective sign of operation. 3. Determination of the alignment shift amount, δ or MAG_MED signal. • Second cycle: 1. Addition of the Significand. 2. Rounding f the result. 3. Normalization of the result. Fig. 1. Higher level representation of the algorithm. 5
  • 6. IMPLEMENTATION OF THE ALGORITHM ON FPGA • The implementation off the presented algorithm has been performed using two different Xilinx © products, XC2V6000 device of virtex2 family and XC3S1500 of spartan-3 family. TABLE 1. ESTIMATION OF THE USAGE OF RESOURCES IN DEVICE XC2V6000. Device Utilization Summary Logic Utilization Used Available Utilization Number of Slice Flip Flops 308 67,584 0% Number of 4 input LUTs 932 67,584 1% Logic Distribution Number of occupied Slices 546 33,792 1% Total Number of 4 input 932 67,584 1% LUTs Number of bonded IOBs 195 824 23% Number of GCLKs 2 16 12% 6
  • 7. IMPLEMENTATION OF THE ALGORITHM ON FPGA (Cont.) TABLE 2. ESTIMATION OF THE USAGE OF RESOURCES IN DEVICE XC3S1500 . Device Utilization Summary Logic Utilization Used Available Utilization Number of Slice Flip Flops 421 26,624 1% Number of 4 input LUTs 492 26,624 1% Logic Distribution Number of occupied Slices 491 13,312 3% Total Number of 4 input LUTs 668 26,624 2% Number of bonded IOBs 39 221 17% IOB Flip Flops 15 Number of Block RAMs 1 32 3% Number of GCLKs 4 8 50% Number of DCMs 2 4 50% Total equivalent gate count for design 89,436 Additional JTAG gate count for IOBs 1,872 7
  • 8. DETAILED ILLUSTRATION OF THE FIRST CYCLE OF THE ALGORITHM FB[0:52] FA[0:52] SA SOP SB EA EB FLIP FLOPS ONE’S COMPLEMENT S.EFF FAO[0:52] FBO[0:52] ADDER (5) ADDER (7) PRESHIFT SIGN_MED 1 0 XOR FSOP[-1:53] MUX XOR 0 1 MUX MAG_MED[5:0] SHIFT(63) ORTREE SHIFT(65) FL[0:52] 0 1 IS_BIG MUX SHIFT(1) FSOPA[-1:116] FLP[-1:52] SIGN_BIG Fig. 2. Block level representation of the 1st cycle of the algorithm. 8
  • 9. DETAILED ILLUSTRATION OF THE FIRST CYCLE OF THE ALGORITHM (CONT.) Fig. 3. Block level representation of the 2nd cycle of the algorithm. 9
  • 10. DISCUSSIONS AND SIMULATION RESULTS Fig. 4. Simulation of the floating point adder at Xilinx© ISE using the: (a) Behavioral simulation, (b) Post-route and synthesis simulation, (c) Technical schematic. 10
  • 11. CONCLUSIONS  The system has a minimum period of 14.081ns or a maximum frequency of 71.017MHz.  This technique successfully demonstrates a very low latency and a scope of achieving an even lower latencies with the use of intricate and more complex computational techniques.  This technique shows significant improvements over the present way of performing he arithmetic operations of the floating-point numbers in terms of latency, ease, flexibility, and robustness against errors.  This implementation offers a faster and smarter estimation of the results with minimal errors and ensures minimal computational load for the system.
  • 12. REFERENCES  Peter-Michael Seidel, Guy Even, “Delay-Optimized Implementation of IEEE Floating-Point Addition”, IEEE Trans. on Computers, vol. 53, no. 2, pp. 97- 113, Feb. 2004.  Karan Gumber, Sharmelee Thangjam, “Performance Analysis of Floating Point Adder using VHDL on Reconfigurable Hardware”, International Journal of Computer Applications, vol. 46, no. 9, pp. 1-5, May 2012.  N. Kikkeri, P.M. Seidel, “An FPGA Implementation of a Fully Verified Double Precision IEEE Floating-Point Adder”, Proc. of IEEE International Conference on Application-specific Systems, Architectures and Processors, pp. 83-88, 9-11 July 2007.  A. Tyagi, “A Reduced-Area Scheme for Carry-Select Adders”, IEEE trans. on Computers, vol. 42, no. 10, pp. 1163-1170, Oct. 1993.  A. Beaumont-Smith, N. Burgess, S. Lefrere, C. Lim, “Reduced Latency IEEE Floating-Point Standard Adder Architectures,” Proc. of 14th IEEE Symposium on Computer Arithmetic, pp. 35-43, 1999. 12
  • 13. REFERENCES (Cont.)  P. Farmwald, “On the Design of High Performance Digital Arithmetic Units,” PhD thesis, Stanford Univ., Aug. 1981.  A. Nielsen, D. Matula, C. N. Lyu, G. Even, “IEEE Compliant Floating-Point Adder that Conforms with the Pipelined Packet-Forwarding Paradigm,” IEEE Trans. on Computers, vol. 49, no. 1, pp. 33-47, Jan. 2000.  N. Quach, N. Takagi, and M. Flynn, “On fast IEEE Rounding”, Technical Report CSL-TR-91-459, Stanford Univ., Jan. 1991.  P.-M. Seidel, “On The Design of IEEE Compliant Floating-Point Units and Their Quantitative Analysis”, PhD thesis, Univ. of Saarland, Germany, Dec. 1999.  P.-M. Seidel, G. Even, “How Many Logic Levels Does Floating-Point Addition Require?”, Proc. of International Conference on Computer Design (ICCD ’98): VLSI, in Computers & Processors, pp. 142-149, Oct. 1998.  W.C. Park, T.D. Han, S.D. Kim, S.B. Yang, “Floating Point Adder/Subtractor Performing IEEE Rounding and Addition/Subtraction in Parallel”, IEICE Trans. on Information and Systems, vol. 4, pp. 297-305, 1996. 13
  • 14. REFERENCES (Cont.)  S. Oberman, H. Al-Twaijry, and M. Flynn, “The SNAP Project: Design of Floating Point Arithmetic Units”, Proc. of 13th IEEE Symposium on Computer Arithmetic, pp. 156-165, 1997.  S. Oberman, “Floating-Point Arithmetic Unit Including an Efficient Close Data Path,” AMD, US patent 6094668, 2000.  V. Gorshtein, A. Grushin, and S. Shevtsov, “Floating Point Addition Methods and Apparatus.” Sun Microsystems, US patent 5808926, 1998.  G. Even, P.M. Seidel, “A comparison of three rounding algorithms for IEEE floating-point multiplication”, Proc. of 14th IEEE Symposium on Computer Arithmetic, pp. 225-232, 1999.  IEEE Computer Society, “IEEE Standard for Floating-Point Arithmetic”, IEEE Std. 754 TM-2008 (Revision of IEEE Std 754-1985), Aug. 29, 2008.  H. D. Nguyen, B. Pasca, T. B. Preuber, “FPGA-Specific Arithmetic Optimizations of Short-Latency Adders,” Proc. of 21 st IEEE international conference on field programmable logic and applications, pp. 232 – 237, 2011. 14
  • 15. REFERENCES (Cont.)  C. Minchola, M. Vazquez, G. Sutter, “A FPGA IEEE-754-2008 DECIMAL64 FLOATING-POINT ADDER/SUBTRACTOR,” Proc. of VII Southern conference on Programmable Logic, pp. 251 – 256, 2011.  F. Dinechin, H. D. Nguyen, B. Pasca, “Pipelined FPGA Adders,” Proc. of International conference on Field Programmable Logic and applications, pp. 422 – 427, 2010. 15
  • 17. Thank You 17