Decimal Multiplication in FPGA with a Novel Decimal Adder/Subtractor

Financial and commercial data are mostly represented in decimal format. To avoid errors introduced when converting some decimal fractions to binary, these data are processed with decimal arithmetic. Most processors only have hardwired binary arithmetic units. So, decimal operations are executed with slow software-based decimal arithmetic functions. For the fast execution of decimal operations, dedicated hardware units have been proposed and designed in FPGA. Decimal multiplication is found in most decimal-based applications and so its optimized design is very important for fast execution. In this paper two new parallel decimal multipliers in FPGA are proposed. These are based on a new decimal adder/subtractor also proposed in this paper. The new decimal multipliers improve state-of-the-art parallel decimal multipliers. Compared to previous architectures, implementation results show that the proposed multipliers achieve 26% better area and 12% better performance. Also, the new decimal multipliers reduce the area and performance gap to binary multipliers and are smaller for 32 digit operands.

Hardware–Software Co-Design for Decimal Multiplication

Decimal arithmetic using software is slow for very large-scale applications. On the other hand, when hardware is employed, extra area overhead is required. A balanced strategy can overcome both issues. Our proposed methods are compliant with the IEEE 754-2008 standard for decimal floating-point arithmetic and combinations of software and hardware. In our methods, software with some area-efficient decimal component (hardware) is used to design the multiplication process. Analysis in a RISC-V-based integrated co-design evaluation framework reveals that the proposed methods provide several Pareto points for decimal multiplication solutions. The total execution process is sped up by 1.43× to 2.37× compared with a full software solution. In addition, 7–97% less hardware is required compared with an area-efficient full hardware solution.

Radix-10 Fixed Point Division Hardware

Standardization of decimal floating-point formats by IEEE in IEEE 754-2008 Standards fuelled the interest on decimal floating-point architectures among the global research community. Although decimal arithmetic architecture research attracted computer scientists for the last two decades, the major thrust was observed past the year 2008. Multiple proposals have been witnessed for decimal arithmetic units, mostly adders/subtractors, and multipliers. Very few designs have been proposed in the division domain. This article proposes decimal division hardware based on sutras from Vedic Mathematics, the ancient mathematics system. We present a Reduced Magnitude Divisor Generator which converts each digit of the actual divisor into a reduced digit set [-5, 5] using a unique combination/modification of the Vedic Sutras. The divisor digit magnitude reduction also minimizes the product set of multiplication as the single-digit multiplier belongs to the reduced digit set [0, 5] barring the sign. The sign of the dividend or the divisor is not attended during division as a simple XOR operation on the two signs provides the sign of the quotient. Peer comparison has exhibited better results for our design in terms of space and time.

Decimal Hardware Multiplier

IEEE-754 2008 has extended the standard with decimal floating-point arithmetic. Human-centric applications, like financial and commercial, depend on decimal arithmetic since the results must match exactly those obtained by human calculations without being subject to errors caused by decimal to binary conversions. Decimal multiplication is a fundamental operation utilized in many algorithms, and it is referred in the standard IEEE-754 2008. Decimal multiplication has an inherent difficulty associated with the representation of decimal numbers using a binary number system. Both bit and digit carries, as well as invalid results, must be considered in decimal multiplication in order to produce the correct result. This chapter focuses on algorithms for hardware implementation of decimal multiplication. Both decimal fixed-point and floating-point multiplication are described, including iterative and parallel solutions.

Decimal Hardware Multiplier

IEEE-754 2008 has extended the standard with decimal floating point arithmetic. Human-centric applications, like financial and commercial, depend on decimal arithmetic since the results must match exactly those obtained by human calculations without being subject to errors caused by decimal to binary conversions. Decimal Multiplication is a fundamental operation utilized in many algorithms and it is referred in the standard IEEE-754 2008. Decimal multiplication has an inherent difficulty associated with the representation of decimal numbers using a binary number system. Both bit and digit carries, as well as invalid results, must be considered in decimal multiplication in order to produce the correct result. This article focuses on algorithms for hardware implementation of decimal multiplication. Both decimal fixed-point and floating-point multiplication are described, including iterative and parallel solutions.