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

Characterization and Implementation of a Real-World Target Tracking Algorithm on Field Programmable Gate Arrays with Kalman Filter Test Case

A one dimensional Kalman Filter algorithm provided in Matlab is used as the basis for a Very High Speed Integrated Circuit Hardware Description Language (VHDL) model. The JAVA programming language is used to create the VHDL code that describes the Kalman filter in hardware which allows for maximum flexibility. A one-dimensional behavioral model of the Kalman Filter is described, as well as a one-dimensional and synthesizable register transfer level (RTL) model with optimizations for speed, area, and power. These optimizations are achieved by a focus on parallelization as well as careful Kalman filter sub-module algorithm selection. Newton-Raphson reciprocal is the chosen algorithm for a fundamental aspect of the Kalman filter, which allows efficient high-speed computation of reciprocals within the overall system. The Newton-Raphson method is also expanded for use in calculating square-roots in an optimized and synthesizable two-dimensional VHDL implementation of the Kalman filter. The two-dimensional Kalman filter expands on the one-dimensional implementation allowing for the tracking of targets on a real-world Cartesian coordinate system

Implementation of a Real-Time Beamforming System on Field Programmable Gate Array

Beamforming is an important technique in array signal processing and wireless communication systems. In this project, we investigate the Minimum Variance Distortionless Response (MVDR) beamforming technique and its implementation. The QR-RLS algorithm is chosen because of its advantages of numerical stability and systolic array architecture. The team successfully implemented the real-time beamforming of a linear array with 3 receiving antennas on a Xilinx Virtex-5 FPGA platform. Both the simulation and hardware implementation results are presented in this report

Design of ALU and Cache Memory for an 8 bit ALU

The design of an ALU and a Cache memory for use in a high performance processor was examined in this thesis. Advanced architectures employing increased parallelism were analyzed to minimize the number of execution cycles needed for 8 bit integer arithmetic operations. In addition to the arithmetic unit, an optimized SRAM memory cell was designed to be used as cache memory and as fast Look Up Table. The ALU consists of stand alone units for bit parallel computation of basic integer arithmetic operations. Addition and subtraction were performed using Kogge Stone parallel prefix hardware operating at 330MHz. A high performance multiplier was built using Radix 4 Modified Booth Encoder (MBE) and a Wallace Tree summation array. The multiplier requires single clock cycle for 8 bit integer multiplication and operates at a maximum frequency of 100MHz. Multiplicative division hardware was built for executing both integer division and square root. The division hardware computes 8-bit division and square root in 4 clock cycles. Multiplier forms the basic building block of all these functional units, making high level of resource sharing feasible with this architecture. The optimal operating frequency for the arithmetic unit is 70MHz. A 6T CMOS SRAM cell measuring 90 µm2 was designed using minimum size transistors. The layout allows for horizontal overlap resulting in effective area of 76 µm2 for an 8x8 array. By substituting equivalent bit line capacitance of P4 L1 Cache, the memory was simulated to have a read time of 3.27ns. An optimized set of test vectors were identified to enable high fault coverage without the need for any additional test circuitry. Sixteen test cases were identified that would toggle all the nodes and provide all possible inputs to the sub units of the multiplier. A correlation based semi automatic method was investigated to facilitate test case identification for large multipliers. This method of testability eliminates performance and area overhead associated with conventional testability hardware. Bottom up design methodology was employed for the design. The performance and area metrics are presented along with estimated power consumption. A set of Monte Carlo analysis was carried out to ensure the dependability of the design under process variations as well as fluctuations in operating conditions. The arithmetic unit was found to require a total die area of 2mm2 (approx.) in 0.35 micron process

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

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

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