A Minimum Cut Based Re-synthesis Approach

A new re-synthesis approach that benefits from min-cut based partitioning is proposed. This divide and conquer approach is shown to improve the performance of existing synthesis tools on a variety of benchmarks

Approximate logic circuits: Theory and applications

CMOS technology scaling, the process of shrinking transistor dimensions based on Moore's law, has been the thrust behind increasingly powerful integrated circuits for over half a century. As dimensions are scaled to few tens of nanometers, process and environmental variations can significantly alter transistor characteristics, thus degrading reliability and reducing performance gains in CMOS designs with technology scaling. Although design solutions proposed in recent years to improve reliability of CMOS designs are power-efficient, the performance penalty associated with these solutions further reduces performance gains with technology scaling, and hence these solutions are not well-suited for high-performance designs. This thesis proposes approximate logic circuits as a new logic synthesis paradigm for reliable, high-performance computing systems. Given a specification, an approximate logic circuit is functionally equivalent to the given specification for a "significant" portion of the input space, but has a smaller delay and power as compared to a circuit implementation of the original specification. This contributions of this thesis include (i) a general theory of approximation and efficient algorithms for automated synthesis of approximations for unrestricted random logic circuits, (ii) logic design solutions based on approximate circuits to improve reliability of designs with negligible performance penalty, and (iii) efficient decomposition algorithms based on approxiiii mate circuits to improve performance of designs during logic synthesis. This thesis concludes with other potential applications of approximate circuits and identifies. open problems in logic decomposition and approximate circuit synthesis

Efficient alternative wiring techniques and applications.

Sze, Chin Ngai.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 80-84) and index.Abstracts in English and Chinese.Abstract --- p.iAcknowledgments --- p.iiiCurriculum Vitae --- p.ivList of Figures --- p.ixList of Tables --- p.xiiChapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation and Aims --- p.1Chapter 1.2 --- Contribution --- p.8Chapter 1.3 --- Organization of Dissertation --- p.10Chapter 2 --- Definitions and Notations --- p.11Chapter 3 --- Literature Review --- p.15Chapter 3.1 --- Logic Reconstruction --- p.15Chapter 3.1.1 --- SIS: A System for Sequential and Combinational Logic Synthesis --- p.16Chapter 3.2 --- ATPG-based Alternative Wiring --- p.17Chapter 3.2.1 --- Redundancy Addition and Removal for Logic Optimization --- p.18Chapter 3.2.2 --- Perturb and Simplify Logic Optimization --- p.18Chapter 3.2.3 --- REWIRE --- p.21Chapter 3.2.4 --- Implication-tree Based Alternative Wiring Logic Trans- formation --- p.22Chapter 3.3 --- Graph-based Alternative Wiring --- p.24Chapter 4 --- Implication Based Alternative Wiring Logic Transformation --- p.25Chapter 4.1 --- Source Node Implication --- p.25Chapter 4.1.1 --- Introduction --- p.25Chapter 4.1.2 --- Implication Relationship and Implication-tree --- p.25Chapter 4.1.3 --- Selection of Alternative Wire Based on Implication-tree --- p.29Chapter 4.1.4 --- Implication-tree Based Logic Transformation --- p.32Chapter 4.2 --- Destination Node Implication --- p.35Chapter 4.2.1 --- Introduction --- p.35Chapter 4.2.2 --- Destination Node Relationship --- p.35Chapter 4.2.3 --- Destination Node Implication-tree --- p.39Chapter 4.2.4 --- Selection of Alternative Wire --- p.41Chapter 4.3 --- The Algorithm --- p.43Chapter 4.3.1 --- IB AW Implementation --- p.43Chapter 4.3.2 --- Experimental Results --- p.43Chapter 4.4 --- Conclusion --- p.45Chapter 5 --- Graph Based Alternative Wiring Logic Transformation --- p.47Chapter 5.1 --- Introduction --- p.47Chapter 5.2 --- Notations and Definitions --- p.48Chapter 5.3 --- Alternative Wire Patterns --- p.50Chapter 5.4 --- Construction of Minimal Patterns --- p.54Chapter 5.4.1 --- Minimality of Patterns --- p.54Chapter 5.4.2 --- Minimal Pattern Formation --- p.56Chapter 5.4.3 --- Pattern Extraction --- p.61Chapter 5.5 --- Experimental Results --- p.63Chapter 5.6 --- Conclusion --- p.63Chapter 6 --- Logic Optimization by GBAW --- p.66Chapter 6.1 --- Introduction --- p.66Chapter 6.2 --- Logic Simplification --- p.67Chapter 6.2.1 --- Single-Addition-Multiple-Removal by Pattern Feature . . --- p.67Chapter 6.2.2 --- Single-Addition-Multiple-Removal by Combination of Pat- terns --- p.68Chapter 6.2.3 --- Single-Addition-Single-Removal --- p.70Chapter 6.3 --- Incremental Perturbation Heuristic --- p.71Chapter 6.4 --- GBAW Optimization Algorithm --- p.73Chapter 6.5 --- Experimental Results --- p.73Chapter 6.6 --- Conclusion --- p.76Chapter 7 --- Conclusion --- p.78Bibliography --- p.80Chapter A --- VLSI Design Cycle --- p.85Chapter B --- Alternative Wire Patterns in [WLFOO] --- p.87Chapter B.1 --- 0-local Pattern --- p.87Chapter B.2 --- 1-local Pattern --- p.88Chapter B.3 --- 2-local Pattern --- p.89Chapter B.4 --- Fanout-reconvergent Pattern --- p.90Chapter C --- New Alternative Wire Patterns --- p.91Chapter C.1 --- Pattern Cluster C1 --- p.91Chapter C.1.1 --- NAND-NAND-AND/NAND;AND/NAND --- p.91Chapter C.1.2 --- NOR-NOR-OR/NOR;AND/NAND --- p.92Chapter C.1.3 --- AND-NOR-OR/NOR;OR/NOR --- p.95Chapter C.1.4 --- OR-NAND-AND/NAND;AND/NAND --- p.95Chapter C.2 --- Pattern Cluster C2 --- p.98Chapter C.3 --- Pattern Cluster C3 --- p.99Chapter C.4 --- Pattern Cluster C4 --- p.104Chapter C.5 --- Pattern Cluster C5 --- p.105Glossary --- p.106Index --- p.10

A parallel algorithm for multi-level logic synthesis using the transduction method

The Transduction Method has been shown to be a powerful tool in the optimization of multilevel networks. Many tools such as the SYLON synthesis system (X90), (CM89), (LM90) have been developed based on this method. A parallel implementation is presented of SYLON-XTRANS (XM89) on an eight processor Encore Multimax shared memory multiprocessor. It minimizes multilevel networks consisting of simple gates through parallel pruning, gate substitution, gate merging, generalized gate substitution, and gate input reduction. This implementation, called Parallel TRANSduction (PTRANS), also uses partitioning to break large circuits up and performs inter- and intra-partition dynamic load balancing. With this, good speedups and high processor efficiencies are achievable without sacrificing the resulting circuit quality

Automated synthesis and optimization of multilevel logic circuits.

With the increased complexity of Very Large Scaled Integrated (VLSI) circuits, multilevellogic synthesis plays an even more important role due to its flexibility and compactness.The history of symbolic logic and some typical techniques for multilevel logic synthesisare reviewed. These methods include algorithmic approach; Rule-Based approach; BinaryDecision Diagram (BDD) approach; Field Programmable Gate Array(FPGA) approachand several perturbation applications.One new kind of don't cares (DCs), called functional DCs has been proposed for multilevellogic synthesis. The conventional two-level cubes are generalized to multilevel cubes.Then functional DCs are generated based on the properties of containment. The conceptof containment is more general than unateness which leads to the generation of newDCs. A separate C program has been developed to utilize the functional DCs generatedas a Boolean function is decomposed for both single output and multiple output functions.The program can produce better results than script.rugged of SIS, developed by UC Berkeley,both in area and speed in less CPU time for a number of testcases from MCNC andIWLS'93 benchmarks.In certain applications ANDjXOR (Reed-Muller) logic has shown some attractive advantagesover the standard Boolean logic based on AND JOR operations. A bidirectionalconversion algorithm between these two paradigms is presented based on the concept of polarityfor sum-of-products (SOP) Boolean functions, multiple segment and multiple pointerfacilities. Experimental results show that the algorithm is much faster than the previouslypublished programs for any fixed polarity. Based on this algorithm, a new technique calledredundancy-removal is applied to generalize the idea to very large multiple output Booleanfunctions. Results for benchmarks with up to 199 inputs and 99 outputs are presented.Applying the preceding conversion program, any Boolean functions can be expressedby fixed polarity Reed-Muller forms. There are 2n polarities for an n-variable function andthe number of product terms depends on these polarities. The problem of exact polarityminimization is computationally extensive and current programs are only suitable whenn :::; 15. Based on the comparison of the concepts of polarity in the standard Boolean logicand Reed-Muller logic, a fast algorithm is developed and implemented in C language whichcan find the best polarity for multiple output functions. Benchmark examples of up to 25inputs and 29 outputs run on a personal computer are given.After the best polarity for a Boolean function is calculated, this function can be furthersimplified using mixed polarity methods by combining the adjacent product terms. Hence,an efficient program is developed based on decomposition strategy to implement mixedpolarity minimization for both single output and very large multiple output Boolean functions.Experimental results show that the numbers of product terms are much less thanthe results produced by ESPRESSO for some categories of functions