Quantum Algorithms for Unate and Binate Covering Problems with Application to Finite State Machine Minimization

Covering problems find applications in many areas of computer science and engineering, such that numerous combinatorial problems can be formulated as covering problems. Combinatorial optimization problems are generally NPhard problems that require an extensive search to find the optimal solution. Exploiting the benefits of quantum computing, we present a quantum oracle design for covering problems, taking advantage of Grover’s search algorithm to achieve quadratic speedup. This paper also discusses applications of the quantum counter in unate covering problems and binate covering problems with some important practical applications, such as finding prime implicants of a Boolean function, implication graphs, and minimization of incompletely specified Finite State Machines

A Novel SAT-Based Approach to the Task Graph Cost-Optimal Scheduling Problem

The Task Graph Cost-Optimal Scheduling Problem consists in scheduling a certain number of interdependent tasks onto a set of heterogeneous processors (characterized by idle and running rates per time unit), minimizing the cost of the entire process. This paper provides a novel formulation for this scheduling puzzle, in which an optimal solution is computed through a sequence of Binate Covering Problems, hinged within a Bounded Model Checking paradigm. In this approach, each covering instance, providing a min-cost trace for a given schedule depth, can be solved with several strategies, resorting to Minimum-Cost Satisfiability solvers or Pseudo-Boolean Optimization tools. Unfortunately, all direct resolution methods show very low efficiency and scalability. As a consequence, we introduce a specialized method to solve the same sequence of problems, based on a traditional all-solution SAT solver. This approach follows the "circuit cofactoring" strategy, as it exploits a powerful technique to capture a large set of solutions for any new SAT counter-example. The overall method is completed with a branch-and-bound heuristic which evaluates lower and upper bounds of the schedule length, to reduce the state space that has to be visited. Our results show that the proposed strategy significantly improves the blind binate covering schema, and it outperforms general purpose state-of-the-art tool

Quantum Search Algorithms for Constraint Satisfaction and Optimization Problems Using Grover\u27s Search and Quantum Walk Algorithms with Advanced Oracle Design

The field of quantum computing has emerged as a powerful tool for solving and optimizing combinatorial optimization problems. To solve many real-world problems with many variables and possible solutions for constraint satisfaction and optimization problems, the required number of qubits of scalable hardware for quantum computing is the bottleneck in the current generation of quantum computers. In this dissertation, we will demonstrate advanced, scalable building blocks for the quantum search algorithms that have been implemented in Grover\u27s search algorithm and the quantum walk algorithm. The scalable building blocks are used to reduce the required number of qubits in the design. The proposed architecture effectively scales and optimizes the number of qubits needed to solve large problems with a limited number of qubits. Thus, scaling and optimizing the number of qubits that can be accommodated in quantum algorithm design directly reflect on performance. Also, accuracy is a key performance metric related to how accurately one can measure quantum states. The search space of quantum search algorithms is traditionally created by using the Hadamard operator to create superposition. However, creating superpositions for problems that do not need all superposition states decreases the accuracy of the measured states. We present an efficient quantum circuit design that the user has control over to create the subspace superposition states for the search space as needed. Using only the subspace states as superposition states of the search space will increase the rate of correct solutions. In this dissertation, we will present the implementation of practical problems for Grover\u27s search algorithm and quantum walk algorithm in logic design, logic puzzles, and machine learning problems such as SAT, MAX-SAT, XOR-SAT, and like SAT problems in EDA, and mining frequent patterns for association rule mining

ASAM : Automatic Architecture Synthesis and Application Mapping; dl. 3.2: Instruction set synthesis

No abstract

Optimization Algorithms For The Multiple Constant Multiplications Problem

(Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2009(PhD) -- İstanbul Technical University, Institute of Science and Technology, 2009Bu tezde, birden fazla katsayının çarpımı (MCM) problemi, bir başka deyişle, bir değişkenin birden fazla katsayı ile çarpımının minimum sayıda toplama/çıkarma işlemi kullanılarak gerçeklenmesi için tasarlanmış kesin ve yaklaşık algoritmalar sunulmaktadır. Bir kesin alt ifade eliminasyonu (CSE) algoritmasının tasarımında, MCM problemini bir 0-1 tamsayı lineer programlama problemi olarak modelleyen daha önceden önerilmiş bir algoritma temel alınmıştır. Kesin CSE algoritması içinde, alan ve gecikme ölçütlerini ele alabilmek için yeni bir kesin model önerilmektedir. Kesin CSE algoritması tarafından taranacak arama uzayını küçültmek için problem indirgeme ve model basitleştirme teknikleri sunulmaktadır. Bu tekniklerin kullanımının kesin CSE algoritmasının daha büyük örnekler üzerinde uygulanmasına olanak sağladığı gösterilmektedir. Ayrıca, bu teknikler ile donatılmış kesin CSE algoritması, katsayıları genel sayı gösteriminde ele alacak ve kesin CSE algoritmasından daha iyi sonuçlar elde edecek şekilde genişletilmektedir. Bunların yanında, gerçek boyutlu örnekler üzerinde uygulanabilen bir kesin graf tabanlı algoritma sunulmaktadır. Bu kesin algoritmalara ek olarak, minimum sonuçlara oldukça yakın çözümler bulabilen ve kesin algoritmaların ele almakta zorlandığı örneklere uygulanabilen yaklaşık CSE ve graf tabanlı algoritmalar verilmektedir. Bu tezde önerilen kesin ve yaklaşık algoritmaların daha önceden önerilmiş sezgisel yöntemlerden daha iyi sonuçlar verdiği gösterilmektedir. Bunların yanısıra, bu tezde, kesin CSE algoritması gecikme kısıtı altında alanın minimize edilmesi, kapı seviyesinde alanın minimize edilmesi ve yüksek hızlı sayısal sonlu impuls cevaplı filtrelerin tasarımında alanın optimize edilmesi problemlerine uygulanmaktadır.In this thesis, exact and approximate algorithms designed for the multiple constant multiplications (MCM) problem, i.e., the implementation of the multiplication of a variable with multiple constants using minimum number of addition/subtraction operations, are introduced. In the design of an exact common subexpression elimination (CSE) algorithm, we relied on the previously proposed algorithm that models the MCM problem as a 0-1 integer linear programming problem. To handle the area and delay parameters in the exact CSE algorithm, a new exact model is proposed. To reduce the search space to be explored by the exact algorithm, problem reduction and model simplification techniques are introduced. It is shown that the use of these techniques enable the exact CSE algorithm to be applied on larger size instances. Also, the exact CSE algorithm equipped with these techniques is extended to handle the constants under general number representation yielding better solutions than those of the exact CSE algorithm. Besides, an exact graph-based algorithm that can be applied on real size instances is introduced. In addition to the exact algorithms, approximate CSE and graph-based algorithms that find similar results with the minimum solutions and can be applied on instances that the exact algorithms cannot deal with are presented. It is shown that the exact and approximate algorithms proposed in this thesis give better solutions than those of the previously proposed heuristic algorithms. Furthermore, in this thesis, the exact CSE algorithm is applied on the minimization of area under a delay constraint, the minimization of area at gate-level, and the optimization of area in high-speed digital finite impulse response filters synthesis problems.DoktoraPh

Computer Aided Verification

This open access two-volume set LNCS 10980 and 10981 constitutes the refereed proceedings of the 30th International Conference on Computer Aided Verification, CAV 2018, held in Oxford, UK, in July 2018. The 52 full and 13 tool papers presented together with 3 invited papers and 2 tutorials were carefully reviewed and selected from 215 submissions. The papers cover a wide range of topics and techniques, from algorithmic and logical foundations of verification to practical applications in distributed, networked, cyber-physical, and autonomous systems. They are organized in topical sections on model checking, program analysis using polyhedra, synthesis, learning, runtime verification, hybrid and timed systems, tools, probabilistic systems, static analysis, theory and security, SAT, SMT and decisions procedures, concurrency, and CPS, hardware, industrial applications