A high-performance inner-product processor for real and complex numbers.

A novel, high-performance fixed-point inner-product processor based on a redundant binary number system is investigated in this dissertation. This scheme decreases the number of partial products to 50%, while achieving better speed and area performance, as well as providing pipeline extension opportunities. When modified Booth coding is used, partial products are reduced by almost 75%, thereby significantly reducing the multiplier addition depth. The design is applicable for digital signal and image processing applications that require real and/or complex numbers inner-product arithmetic, such as digital filters, correlation and convolution. This design is well suited for VLSI implementation and can also be embedded as an inner-product core inside a general purpose or DSP FPGA-based processor. Dynamic control of the computing structure permits different computations, such as a variety of inner-product real and complex number computations, parallel multiplication for real and complex numbers, and real and complex number division. The same structure can also be controlled to accept redundant binary number inputs for multiplication and inner-product computations. An improved 2's-complement to redundant binary converter is also presented

High speed world level finite field multipliers in F2m

Finite fields have important applications in number theory, algebraic geometry, Galois theory, cryptography, and coding theory. Recently, the use of finite field arithmetic in the area of cryptography has increasingly gained importance. Elliptic curve and El-Gamal cryptosystems are two important examples of public key cryptosystems widely used today based on finite field arithmetic. Research in this area is moving toward finding new architectures to implement the arithmetic operations more efficiently. Two types of finite fields are commonly used in practice, prime field GF(p) and the binary extension field GF(2 m). The binary extension fields are attractive for high speed cryptography applications since they are suitable for hardware implementations. Hardware implementation of finite field multipliers can usually be categorized into three categories: bit-serial, bit-parallel, and word-level architectures. The word-level multipliers provide architectural flexibility and trade-off between the performance and limitations of VLSI implementation and I/O ports, thus it is of more practical significance. In this work, different word level architectures for multiplication using binary field are proposed. It has been shown that the proposed architectures are more efficient compared to similar proposals considering area/delay complexities as a measure of performance. Practical size multipliers for cryptography applications have been realized in hardware using FPGA or standard CMOS technology, to similar proposals considering area/delay complexities as a measure of performance. Practical size multipliers for cryptography applications have been realized in hardware using FPGA or standard CMOS technology. Also different VLSI implementations for multipliers were explored which resulted in more efficient implementations for some of the regular architectures. The new implementations use a simple module designed in domino logic as the main building block for the multiplier. Significant speed improvements was achieved designing practical size multipliers using the proposed methodology

High sample-rate Givens rotations for recursive least squares

The design of an application-specific integrated circuit of a parallel array processor is considered for recursive least squares by QR decomposition using Givens rotations, applicable in adaptive filtering and beamforming applications. Emphasis is on high sample-rate operation, which, for this recursive algorithm, means that the time to perform arithmetic operations is critical. The algorithm, architecture and arithmetic are considered in a single integrated design procedure to achieve optimum results. A realisation approach using standard arithmetic operators, add, multiply and divide is adopted. The design of high-throughput operators with low delay is addressed for fixed- and floating-point number formats, and the application of redundant arithmetic considered. New redundant multiplier architectures are presented enabling reductions in area of up to 25%, whilst maintaining low delay. A technique is presented enabling the use of a conventional tree multiplier in recursive applications, allowing savings in area and delay. Two new divider architectures are presented showing benefits compared with the radix-2 modified SRT algorithm. Givens rotation algorithms are examined to determine their suitability for VLSI implementation. A novel algorithm, based on the Squared Givens Rotation (SGR) algorithm, is developed enabling the sample-rate to be increased by a factor of approximately 6 and offering area reductions up to a factor of 2 over previous approaches. An estimated sample-rate of 136 MHz could be achieved using a standard cell approach and O.35pm CMOS technology. The enhanced SGR algorithm has been compared with a CORDIC approach and shown to benefit by a factor of 3 in area and over 11 in sample-rate. When compared with a recent implementation on a parallel array of general purpose (GP) DSP chips, it is estimated that a single application specific chip could offer up to 1,500 times the computation obtained from a single OP DSP chip

Parallel data compression

Data compression schemes remove data redundancy in communicated and stored data and increase the effective capacities of communication and storage devices. Parallel algorithms and implementations for textual data compression are surveyed. Related concepts from parallel computation and information theory are briefly discussed. Static and dynamic methods for codeword construction and transmission on various models of parallel computation are described. Included are parallel methods which boost system speed by coding data concurrently, and approaches which employ multiple compression techniques to improve compression ratios. Theoretical and empirical comparisons are reported and areas for future research are suggested

Digit-Level Serial-In Parallel-Out Multiplier Using Redundant Representation for a Class of Finite Fields

Two digit-level finite field multipliers in F2m using redundant representation are presented. Embedding F2m in cyclotomic field F2(n) causes a certain amount of redundancy and consequently performing field multiplication using redundant representation would require more hardware resources. Based on a specific feature of redundant representation in a class of finite fields, two new multiplication algorithms along with their pertaining architectures are proposed to alleviate this problem. Considering area-delay product as a measure of evaluation, it has been shown that both the proposed architectures considerably outperform existing digit-level multipliers using the same basis. It is also shown that for a subset of the fields, the proposed multipliers are of higher performance in terms of area-delay complexities among several recently proposed optimal normal basis multipliers. The main characteristics of the postplace&route application specific integrated circuit implementation of the proposed multipliers for three practical digit sizes are also reported