An Elitist Non-Dominated Multi-Objective Genetic Algorithm Based Temperature Aware Circuit Synthesis

At sub-nanometre technology, temperature is one of the important design parameters to be taken care of during the target implementation for the circuit for its long term and reliable operation. High device package density leads to high power density that generates high temperatures. The temperature of a chip is directly proportional to the power density of the chip. So, the power density of a chip can be minimized to reduce the possibility of the high temperature generation. Temperature minimization approaches are generally addressed at the physical design level but it incurs high cooling cost. To reduce the cooling cost, the temperature minimization approaches can be addressed at the logic level. In this work, the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) based multi-objective heuristic approach is proposed to select the efficient input variable polarity of Mixed Polarity Reed-Muller (MPRM) expansion for simultaneous optimization of area, power, and temperature. A Pareto optimal solution set is obtained from the vast solution set of 3n (‘n’ is the number of input variables) different polarities of MPRM. Tabular technique is used for input polarity conversion from Sum-of-Product (SOP) form to MPRM form. Finally, using CADENCE and HotSpot tool absolute temperature, silicon area and power consumption of the synthesized circuits are calculated and are reported. The proposed algorithm saves around 76.20% silicon area, 29.09% power dissipation and reduces 17.06% peak temperature in comparison with the reported values in the literature

Low Power Design Techniques for Digital Logic Circuits.

With the rapid increase in the density and the size of chips and systems, area and power dissipationbecome critical concern in Very Large Scale Integrated (VLSI) circuit design. Low powerdesign techniques are essential for today's VLSI industry. The history of symbolic logic and sometypical techniques for finite state machine (FSM) logic synthesis are reviewed.The state assignment is used to optimize area and power dissipation for FSMs. Two costfunctions, targeting area and power, are presented. The Genetic Algorithm (GA) is used to searchfor a good state assignment to minimize the cost functions. The algorithm has been implementedin C. The program can produce better results than NOVA, which is integrated into SIS by DCBerkeley, and other publications both in area and power tested by MCNC benchmarks.Flip-flops are the core components of FSMs. The reduction of power dissipation from flip-flopscan save power for digital systems significantly. Three new kinds of flip-flops, called differentialCMOS single edge-triggered flip-flop with clock gating, double edge-triggered and multiple valuedflip-flops employing multiple valued clocks, are proposed. All circuits are simulated using PSpice.Most researchers have focused on developing low-power techniques in AND/OR or NAND& NOR based circuits. The low power techniques for AND /XOR based circuits are still intheir early stage of development. To implement a complex function involving many inputs,a form of decomposition into smaller subfunctions is required such that the subfunctions fitinto the primitive elements to be used in the implementation. Best polarity based XOR gatedecomposition technique has been developed, which targets low power using Huffman algorithm.Compared to the published results, the proposed method shows considerable improvement inpower dissipation. Further, Boolean functions can be expressed by Fixed Polarity Reed-Muller(FPRM) forms. Based on polarity transformation, an algorithm is developed and implementedin C language which can find the best polarity for power and area optimization. Benchmarkexamples of up to 21 inputs run on a personal computer are given

A Novel Reconfiguration Scheme in Quantum-Dot Cellular Automata for Energy Efficient Nanocomputing

Quantum-Dot Cellular Automata (QCA) is currently being investigated as an alternative to CMOS technology. There has been extensive study on a wide range of circuits from simple logical circuits such as adders to complex circuits such as 4-bit processors. At the same time, little if any work has been done in considering the possibility of reconfiguration to reduce power in QCA devices. This work presents one of the first such efforts when considering reconfigurable QCA architectures which are expected to be both robust and power efficient. We present a new reconfiguration scheme which is highly robust and is expected to dissipate less power with respect to conventional designs. An adder design based on the reconfiguration scheme will be presented in this thesis, with a detailed power analysis and comparison with existing designs. In order to overcome the problems of routing which comes with reconfigurability, a new wire crossing mechanism is also presented as part of this thesis

Detecting facial features automatically

Text in English; Abstract: English and TurkishIncludes bibliographical references (leaves 57-58)xii, 59 leavesThere are many algorithms and approaches in object detection world. Many of them are based on Viola Jones algorithm. According to our observations, the features which help to detect an object are very critical for the success of this algorithm. These features are usually created manually. In this thesis we explore automatic extraction of Haar-like features. We describe the design and construction of a completely automated face detector for gray scale images. Finally, we illustrate the performance of our algorithm on various databases.Obje tespit etmek icin bir çok algoritma ve yaklaşım vardır. Bunların çoğu Viola Jones algoritmasına dayanır. Bizim edindiğimiz tecrübelere göre, obje tespitinde temel konu o objeye ait özniteliklerdir. Bu öznitelikler genellikle manuel olarak oluşturulur. Bu tezde biz Haar-like özniteliklerin otomatik çıkarımları üzerine araştırma yaptık. Gri tonlamalı resimler için tamamıyla otomatikleştirilmiş bir yüz algılayıcısı tasarlayıp bunu uyguladık. Nihayetinde, tasarladığımız algoritmanın farklı veribankaları üzerindeki performansını gösterdik

MIXSyn: An Efficient Logic Synthesis Methodology for Mixed XOR-AND/OR Dominated Circuits

We present a new logic synthesis methodology, called MIXSyn, that produces area-efficient results for mixed XOR-AND/OR dominated logic functions. MIXSyn is a two step synthesis process. The first step is a hybrid logic optimization that enables selective and distinct optimization of AND/OR and XOR-intensive portions of the logic circuit. The second step is a library-free technology mapping that enhances design flexibility with a tractable computational cost. MIXSyn has been tested on a set of large MCNC benchmarks. Experimental results indicate that MIXSyn produces CMOS circuits with 18.0% and 9.2% fewer devices, on the average, with respect to state-of-art academic and commercial synthesis tools, respectively. MIXSyn is also capable to exploit the opportunity of novel XOR implementations offered by the use of double-gate ambipolar devices. Experimental results show that MIXSyn can reduce the number of ambipolar transistors by 20.9% and 15.3%, on the average, with respect to state-of-art academic and commercial synthesis tools, respectively

Support-reducing decomposition for FPGA mapping

Decomposition is a technology-independent process, in which a large complex function is broken into smaller, less complex functions. The costs of two-level or factored-form representations (cubes and literals) are used in most decomposition methods, as they have a high correlation with the area of cell-based designs. However, this correlation is weaker for field-programmable gate arrays (FPGAs) based on look-up tables. Furthermore, local optimizations have limited power due to the structural bias of the circuit descriptions. This paper tries to reduce the structural biasing by remapping the LUT network and decomposing the derived functions using the support as cost function. The proposed method improves the FPGA mapping results of a commercial tool for the 20 largest MCNC benchmarks, with gains of 28% in delay plus 18% in area when targeting delay, and a reduction of 28% in area plus 14% in delay with area as cost function. Results with 23% less area and 6% less delay are obtained after physical synthesis (post place-and-route). Moreover, 12 of the best known results for delay (and 3 for area) of the EPFL benchmarks are improved.Peer ReviewedPostprint (author's final draft