Systolic array implementation of Euclid's algorithm for inversion and division in GF(2m)

[[abstract]]This paper presents a new systolic VLSI architecture for computing inverses and divisions in finite fields GF(2m) based on a variant of Euclid's algorithm. It is highly regular, modular, and thus well suited to VLSI implementation. It has O(m2) area complexity and can produce one result per clock cycle with a latency of 8m-2 clock cycles. As compared to existing related systolic architectures with the same throughput performance, the proposed one gains a significant improvement in area complexity[[fileno]]2030102030060[[department]]電機工程學

Novel digit-serial systolic array implementation of Euclid's algorithm for division in GF(2m)

[[abstract]]In this paper, a novel digit-serial systolic array for computing divisions in GF(2m) over the standard basis is presented. To the authors' knowledge, this is the very first digit-serial systolic divider for GF(2m). The proposed architecture possesses the features of regularity, modularity, and unidirectional data flow. Thus, it is well suited to be implemented using VLSI techniques with fault-tolerant design. One important feature of the proposed architecture is that different throughput performances can be easily achieved by varying the digit size. By choosing the digit size appropriately, the proposed digit-serial architecture can meet the throughput requirement of a certain application with minimum hardware.[[fileno]]2030102030012[[department]]電機工程學

Bit-serial Systolic Array Implementation Of Euclid's Algorithm For Inversion And Division In GF(2/supm)

[[abstract]]This paper presents two serial-in serial-out systolic arrays for inversion or division in GF(2") with the standard basis representation. They can produce results at a rate of one per m cycles after an initial delay of 5m - 4 cycles. The proposed arrays involve unidirectional data flow and are highly regular and modular. Thus, they are well suited to VLSI implemenitation with fault-tolerant design. As compared to existing related systolic designs with the same time complexity and I/O format, our proposed arrays gain a significant improvement in hardware area.[[fileno]]2030102030035[[department]]電機工程學

A VLSI synthesis of a Reed-Solomon processor for digital communication systems

The Reed-Solomon codes have been widely used in digital communication systems such as computer networks, satellites, VCRs, mobile communications and high- definition television (HDTV), in order to protect digital data against erasures, random and burst errors during transmission. Since the encoding and decoding algorithms for such codes are computationally intensive, special purpose hardware implementations are often required to meet the real time requirements. -- One motivation for this thesis is to investigate and introduce reconfigurable Galois field arithmetic structures which exploit the symmetric properties of available architectures. Another is to design and implement an RS encoder/decoder ASIC which can support a wide family of RS codes. -- An m-programmable Galois field multiplier which uses the standard basis representation of the elements is first introduced. It is then demonstrated that the exponentiator can be used to implement a fast inverter which outperforms the available inverters in GF(2m). Using these basic structures, an ASIC design and synthesis of a reconfigurable Reed-Solomon encoder/decoder processor which implements a large family of RS codes is proposed. The design is parameterized in terms of the block length n, Galois field symbol size m, and error correction capability t for the various RS codes. The design has been captured using the VHDL hardware description language and mapped onto CMOS standard cells available in the 0.8-µm BiCMOS design kits for Cadence and Synopsys tools. The experimental chip contains 218,206 logic gates and supports values of the Galois field symbol size m = 3,4,5,6,7,8 and error correction capability t = 1,2,3, ..., 16. Thus, the block length n is variable from 7 to 255. Error correction t and Galois field symbol size m are pin-selectable. -- Since low design complexity and high throughput are desired in the VLSI chip, the algebraic decoding technique has been investigated instead of the time or transform domain. The encoder uses a self-reciprocal generator polynomial which structures the codewords in a systematic form. At the beginning of the decoding process, received words are initially stored in the first-in-first-out (FIFO) buffer as they enter the syndrome module. The Berlekemp-Massey algorithm is used to determine both the error locator and error evaluator polynomials. The Chien Search and Forney's algorithms operate sequentially to solve for the error locations and error values respectively. The error values are exclusive or-ed with the buffered messages in order to correct the errors, as the processed data leave the chip

A single chip VLSI Reed-Solomon decoder

A new VLSI design of a pipeline Reed-Solomon decoder is presented. The transform decoding technique used in a previous design is replaced by a time domain algorithm. A new architecture that implements such an algorithm permits efficient pipeline processing with minimum circuitry. A systolic array is also developed to perform erasure corrections in the new design. A modified form of Euclid's algorithm is implemented by a new architecture that maintains the throughput rate with less circuitry. Such improvements result in both enhanced capability and a significant reduction in silicon area, therefore making it possible to build a pipeline (31,15)RS decoder on a single VLSI chip

The Telecommunications and Data Acquisition Report

Developments in space communications, radio navigation, radio science, ground-base radio astronomy, reports on the Deep Space Network (DSN) and its Ground Communications Facility (GCF), and applications of radio interferometry at microwave frequencies are discussed

New Hardware Algorithms and Designs for Montgomery Modular Inverse Computation in Galois Fields GF(p) and GF(2n)

The computation of the inverse of a number in finite fields, namely Galois Fields GF(p) or GF(2n), is one of the most complex arithmetic operations in cryptographic applications. In this work, we investigate the GF(p) inversion and present several phases in the design of efficient hardware implementations to compute the Montgomery modular inverse. We suggest a new correction phase for a previously proposed almost Montgomery inverse algorithm to calculate the inversion in hardware. It is also presented how to obtain a fast hardware algorithm to compute the inverse by multi-bit shifting method. The proposed designs have the hardware scalability feature, which means that the design can fit on constrained areas and still handle operands of any size. In order to have long-precision calculations, the module works on small precision words. The word-size, on which the module operates, can be selected based on the area and performance requirements. The upper limit on the operand precision is dictated only by the available memory to store the operands and internal results. The scalable module is in principle capable of performing infinite-precision Montgomery inverse computation of an integer, modulo a prime number. We also propose a scalable and unified architecture for a Montgomery inverse hardware that operates in both GF(p) and GF(2n) fields. We adjust and modify a GF(2n) Montgomery inverse algorithm to benefit from multi-bit shifting hardware features making it very similar to the proposed best design of GF(p) inversion hardware. We compare all scalable designs with fully parallel ones based on the same basic inversion algorithm. All scalable designs consumed less area and in general showed better performance than the fully parallel ones, which makes the scalable design a very efficient solution for computing the long precision Montgomery inverse

New Hardware Algorithms and Designs for Montgomery Modular Inverse Computation in Galois Fields GF(p) and GF(2n)

The computation of the inverse of a number in finite fields, namely Galois Fields GF(p) or GF(2n), is one of the most complex arithmetic operations in cryptographic applications. In this work, we investigate the GF(p) inversion and present several phases in the design of efficient hardware implementations to compute the Montgomery modular inverse. We suggest a new correction phase for a previously proposed almost Montgomery inverse algorithm to calculate the inversion in hardware. It is also presented how to obtain a fast hardware algorithm to compute the inverse by multi-bit shifting method. The proposed designs have the hardware scalability feature, which means that the design can fit on constrained areas and still handle operands of any size. In order to have long-precision calculations, the module works on small precision words. The word-size, on which the module operates, can be selected based on the area and performance requirements. The upper limit on the operand precision is dictated only by the available memory to store the operands and internal results. The scalable module is in principle capable of performing infinite-precision Montgomery inverse computation of an integer, modulo a prime number. We also propose a scalable and unified architecture for a Montgomery inverse hardware that operates in both GF(p) and GF(2n) fields. We adjust and modify a GF(2n) Montgomery inverse algorithm to benefit from multi-bit shifting hardware features making it very similar to the proposed best design of GF(p) inversion hardware. We compare all scalable designs with fully parallel ones based on the same basic inversion algorithm. All scalable designs consumed less area and in general showed better performance than the fully parallel ones, which makes the scalable design a very efficient solution for computing the long precision Montgomery inverse

New Hardware Algorithms and Designs for Montgomery Modular Inverse Computation in Galois Fields GF(p) and GF(2n)

The computation of the inverse of a number in finite fields, namely Galois Fields GF(p) or GF(2n), is one of the most complex arithmetic operations in cryptographic applications. In this work, we investigate the GF(p) inversion and present several phases in the design of efficient hardware implementations to compute the Montgomery modular inverse. We suggest a new correction phase for a previously proposed almost Montgomery inverse algorithm to calculate the inversion in hardware. It is also presented how to obtain a fast hardware algorithm to compute the inverse by multi-bit shifting method. The proposed designs have the hardware scalability feature, which means that the design can fit on constrained areas and still handle operands of any size. In order to have long-precision calculations, the module works on small precision words. The word-size, on which the module operates, can be selected based on the area and performance requirements. The upper limit on the operand precision is dictated only by the available memory to store the operands and internal results. The scalable module is in principle capable of performing infinite-precision Montgomery inverse computation of an integer, modulo a prime number. We also propose a scalable and unified architecture for a Montgomery inverse hardware that operates in both GF(p) and GF(2n) fields. We adjust and modify a GF(2n) Montgomery inverse algorithm to benefit from multi-bit shifting hardware features making it very similar to the proposed best design of GF(p) inversion hardware. We compare all scalable designs with fully parallel ones based on the same basic inversion algorithm. All scalable designs consumed less area and in general showed better performance than the fully parallel ones, which makes the scalable design a very efficient solution for computing the long precision Montgomery inverse