THE DESIGN OF AN IC HALF PRECISION FLOATING POINT ARITHMETIC LOGIC UNIT

A 16 bit floating point (FP) Arithmetic Logic Unit (ALU) was designed and implemented in 0.35µm CMOS technology. Typical uses of the 16 bit FP ALU include graphics processors and embedded multimedia applications. The ALU of the modern microprocessors use a fused multiply add (FMA) design technique. An advantage of the FMA is to remove the need for a comparator which is required for a normal FP adder. The FMA consists of a multiplier, shifters, adders and rounding circuit. A fast multiplier based on the Wallace tree configuration was designed. The number of partial products was greatly reduced by the use of the modified booth encoder. The Wallace tree was chosen to reduce the number of reduction layers of partial products. The multiplier also involved the design of a pass transistor based 4:2 compressor. The average delay of the pass transistor based compressor was 55ps and was found to be 7 times faster than the full adder based 4:2 compressor. The shifters consist of separate left and right shifters using multiplexers. The shift amount is calculated using the exponents of the three operands. The addition operation is implemented using a carry skip adder (CSK). The average delay of the CSK was 1.05ns and was slower than the carry look ahead adder by about 400ps. The advantages of the CSK are reduced power, gate count and area when compared to the similar sized carry look ahead adder. The adder computes the addition of the multiplier result and the shifted value of the addend. In most modern computers, division is performed using software thereby eliminating the need for a separate hardware unit. FMA hardware unit was utilized to perform FP division. The FP divider uses the Newton Raphson algorithm to solve division by iteration. The initial approximated value with five bit accuracy was assumed to be pre-stored in cache memory and a separate clock cycle for cache read was assumed before the start of the FP division operation. In order to significantly reduce the area of the design, only one multiplier was used. Rounding to nearest technique was implemented using an 11 bit variable CSK adder. This is the best rounding technique when compared to other rounding techniques. In both the FMA and division, rounding was performed after the computation of the final result during the last clock cycle of operation. Testability analysis is performed for the multiplier which is the most complex and critical part of the FP ALU. The specific aim of testability was to ensure the correct operation of the multiplier and thus guarantee the correctness of the FMA circuit at the layout stage. The multiplier\u27s output was tested by identifying the minimal number of input vectors which toggle the inputs of the 4:2 compressors of the multiplier. The test vectors were identified in a semi automated manner using Perl scripting language. The multiplier was tested with a test set of thirty one vectors. The fault coverage of the multiplier was found to be 90.09%. The layout was implemented using IC station of Mentor Graphics CAD tool and resulted in a chip area of 1.96mm2. The specifications for basic arithmetic operations were met successfully. FP Division operation was completed within six clock cycles. The other arithmetic operations like FMA, FP addition, FP subtraction and FP multiplication were completed within three clock cycles

Dedicated Hardware for Complex Mathematical Operations

New hardware FPGA implementations for the efficient computations of division, natural logarithm and exponential function are proposed. The proposed implementations use generic floating-point adder and multiplier with small additional resources that are shared to compute more frequently used multiply and accumulate operations. Hardware sharing improved the resource utilization. The time of the computation has been reduced to only 6 clock cycles when the natural logarithm and exponential function are calculated. The division is calculated in 5 clock cycles. They are designed as technology independent high throughput computing cores with minimized memory requirements which can be used in higher numbers to significantly increased calculation speed in spectral processing. A new universal arithmetic floating-point unit is also proposed

Series Expansion based Efficient Architectures for Double Precision Floating Point Division

postprin

RISC-V Core Instruction Extension Sets M and F

This thesis project presents the hardware design of the components capable of implementing a 5-stages core RV32I, RV32IM with integer multiplication and division expansion, and RV32IMF with partial single-precision floating-point support. These have been developed using Verilog HDL and based on the RISC-V ISA. Furthermore, these designs have been verified and synthesised on "bare-metal" using the FPGA platform from the DE0 development board. In addition, a custom variety of division modules have been produced to offer performance diversity on frequency of operation, resource allocation and number of clock cycles per division operations. The selection of these modules provides implementation options that allow to personalize the product to the customer needs

Software floating-point computation on parallel mahcines

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (p. 71).by Michael Ruogu Zhang.M.Eng

IEEE Compliant Double-Precision FPU and 64-bit ALU with Variable Latency Integer Divider

Together the arithmetic logic unit (ALU) and floating-point unit (FPU) perform all of the mathematical and logic operations of computer processors. Because they are used so prominently, they fall in the critical path of the central processing unit - often becoming the bottleneck, or limiting factor for performance. As such, the design of a high-speed ALU and FPU is vital to creating a processor capable of performing up to the demanding standards of today\u27s computer users. In this paper, both a 64-bit ALU and a 64-bit FPU are designed based on the reduced instruction set computer architecture. The ALU performs the four basic mathematical operations - addition, subtraction, multiplication and division - in both unsigned and two\u27s complement format, basic logic operations and shifting. The division algorithm is a novel approach, using a comparison multiples based SRT divider to create a variable latency integer divider. The floating-point unit performs the double-precision floating-point operations add, subtract, multiply and divide, in accordance with the IEEE 754 standard for number representation and rounding. The ALU and FPU were implemented in VHDL, simulated in ModelSim, and constrained and synthesized using Synopsys Design Compiler (2006.06). They were synthesized using TSMC 0.1 3nm CMOS technology. The timing, power and area synthesis results were recorded, and, where applicable, compared to those of the corresponding DesignWare components.The ALU synthesis reported an area of 122,215 gates, a power of 384 mW, and a delay of 2.89 ns - a frequency of 346 MHz. The FPU synthesis reported an area 84,440 gates, a delay of 2.82 ns and an operating frequency of 355 MHz. It has a maximum dynamic power of 153.9 mW

Customizing floating-point units for FPGAs: Area-performance-standard trade-offs

The high integration density of current nanometer technologies allows the implementation of complex floating-point applications in a single FPGA. In this work the intrinsic complexity of floating-point operators is addressed targeting configurable devices and making design decisions providing the most suitable performance-standard compliance trade-offs. A set of floating-point libraries composed of adder/subtracter, multiplier, divisor, square root, exponential, logarithm and power function are presented. Each library has been designed taking into account special characteristics of current FPGAs, and with this purpose we have adapted the IEEE floating-point standard (software-oriented) to a custom FPGA-oriented format. Extended experimental results validate the design decisions made and prove the usefulness of reducing the format complexit

High-Speed Function Approximation using a Minimax Quadratic Interpolator

A table-based method for high-speed function approximation in single-precision floating-point format is presented in this paper. Our focus is the approximation of reciprocal, square root, square root reciprocal, exponentials, logarithms, trigonometric functions, powering (with a fixed exponent p), or special functions. The algorithm presented here combines table look-up, an enhanced minimax quadratic approximation, and an efficient evaluation of the second-degree polynomial (using a specialized squaring unit, redundant arithmetic, and multioperand addition). The execution times and area costs of an architecture implementing our method are estimated, showing the achievement of the fast execution times of linear approximation methods and the reduced area requirements of other second-degree interpolation algorithms. Moreover, the use of an enhanced minimax approximation which, through an iterative process, takes into account the effect of rounding the polynomial coefficients to a finite size allows for a further reduction in the size of the look-up tables to be used, making our method very suitable for the implementation of an elementary function generator in state-of-the-art DSPs or graphics processing units (GPUs)

Algorithms and architectures for decimal transcendental function computation

Nowadays, there are many commercial demands for decimal floating-point (DFP) arithmetic operations such as financial analysis, tax calculation, currency conversion, Internet based applications, and e-commerce. This trend gives rise to further development on DFP arithmetic units which can perform accurate computations with exact decimal operands. Due to the significance of DFP arithmetic, the IEEE 754-2008 standard for floating-point arithmetic includes it in its specifications. The basic decimal arithmetic unit, such as decimal adder, subtracter, multiplier, divider or square-root unit, as a main part of a decimal microprocessor, is attracting more and more researchers' attentions. Recently, the decimal-encoded formats and DFP arithmetic units have been implemented in IBM's system z900, POWER6, and z10 microprocessors. Increasing chip densities and transistor count provide more room for designers to add more essential functions on application domains into upcoming microprocessors. Decimal transcendental functions, such as DFP logarithm, antilogarithm, exponential, reciprocal and trigonometric, etc, as useful arithmetic operations in many areas of science and engineering, has been specified as the recommended arithmetic in the IEEE 754-2008 standard. Thus, virtually all the computing systems that are compliant with the IEEE 754-2008 standard could include a DFP mathematical library providing transcendental function computation. Based on the development of basic decimal arithmetic units, more complex DFP transcendental arithmetic will be the next building blocks in microprocessors. In this dissertation, we researched and developed several new decimal algorithms and architectures for the DFP transcendental function computation. These designs are composed of several different methods: 1) the decimal transcendental function computation based on the table-based first-order polynomial approximation method; 2) DFP logarithmic and antilogarithmic converters based on the decimal digit-recurrence algorithm with selection by rounding; 3) a decimal reciprocal unit using the efficient table look-up based on Newton-Raphson iterations; and 4) a first radix-100 division unit based on the non-restoring algorithm with pre-scaling method. Most decimal algorithms and architectures for the DFP transcendental function computation developed in this dissertation have been the first attempt to analyze and implement the DFP transcendental arithmetic in order to achieve faithful results of DFP operands, specified in IEEE 754-2008. To help researchers evaluate the hardware performance of DFP transcendental arithmetic units, the proposed architectures based on the different methods are modeled, verified and synthesized using FPGAs or with CMOS standard cells libraries in ASIC. Some of implementation results are compared with those of the binary radix-16 logarithmic and exponential converters; recent developed high performance decimal CORDIC based architecture; and Intel's DFP transcendental function computation software library. The comparison results show that the proposed architectures have significant speed-up in contrast to the above designs in terms of the latency. The algorithms and architectures developed in this dissertation provide a useful starting point for future hardware-oriented DFP transcendental function computation researches

An Architecture for Improving Variable Radix Real and Complex Division Using Recurrence Division

International audienceThis paper shows the details of an implementation of variable radix floating-point complex division based on previous implementations of the algorithm. This implementation takes advantage of the easier prescaling offered by low-radix division and recodes it as necessary for higher radix iterations throughout the design. This, along with proper use of redundant digit sets, allows us to significantly altar performance characteristics relative to exclusively high-radix division implementations. Comparisons to existing architectures are shown, as well as common implementation optimizations for future iterations. Results are given in cmos32soi 32nm MTCMOS technology using ARMbased standard-cells and commercial EDA toolsets