An Efficient Query Optimizer with Materialized Intermediate Views in Distributed and Cloud Environment

In cloud computing environment hardware resources required for the execution of query using distributed relational database system are scaled up or scaled down according to the query workload performance. Complex queries require large scale of resources in order to complete their execution efficiently. The large scale of resource requirements can be reduced by minimizing query execution time that maximizes resource utilization and decreases payment overhead of customers. Complex queries or batch queries contain some common subexpressions. If these common subexpressions evaluated once and their results are cached, they can be used for execution of further queries. In this research, we have come up with an algorithm for query optimization, which aims at storing intermediate results of the queries and use these by-products for execution of future queries. Extensive experiments have been carried out with the help of simulation model to test the algorithm efficiency

Optimization of Area and Delay for Implementation of the Composite Field Advanced Encryption Standard S-Box

Among different implementations of the Advanced Encryption Standard (AES) S-box, the implementation based on composite field arithmetic (CFA) has the smallest size. In this study, to eliminate the redundant gates in the implementation of CFA-based S-box, a new optimization algorithm named common subexpression elimination (CSE)–shortest critical path constructing (SCPC) algorithm is proposed. The CSE–SCPC algorithm combines an efficient CSE technology with the SCPC method, therefore not only area cost but also the delays are taken into account in the optimization process. For facilitating the search of common subexpressions (CSs), the main operation of CFA-based S-box — the multiplicative inverses (MI) over galois field (GF)((2[Formula: see text] — is divided into six parts and each part is expressed by logical expressions directly. Furthermore, the parts with same input are classified into the same group, as there are CSs among them. Each part of the S-box is optimized by the CSE–SCPC algorithm. For the MI over GF((2[Formula: see text], both the CSs in each part and the CSs among the parts are eliminated by the CSE–SCPC algorithm. Compared to the previous works, our design has not only the minimal area cost but also the shorter critical path in both theoretical computing evaluation and experimental evaluation.

Minimizing Design Costs of an FIR Filter Using a Novel Coefficient Optimization Algorithm

This work presents a novel coefficient optimization algorithm to reduce the area and improve the performance of finite impulse response (FIR) filter designs. Two basic architectures are commonly used in filters—direct and transposed. The coefficients of a filter can be encoded in the fewest possible nonzero bits using canonic signed digit (CSD) expressions. The proposed optimization algorithm can share common subexpressions (CS) and reduce the number of replicate operations that involve the CSD coefficients of filters with a transposed architecture. The effectiveness of the algorithm is confirmed by using filters with the collision detection multiple access (CDMA) standard, the 121-tap high-pass band, and 105- and 325-tap low-pass bands as benchmarks. For example, the proposed algorithm used in the optimization of 105-tap filter has a 30.44% smaller combinational logic area and a 16.69% better throughput/area than those of the best design that has been developed to date. Experimental results reveal that the proposed algorithm outperforms earlier designs.

Comparison of Computer Algebra Systems for Closed Form Stiffness Matrix Generation

Computer algebra systems (CAS) have been advantageously employed to generate closed form expressions for finite elements. The advantages relate to the time improvements or savings realized by employing closed form generated expressions as compared to numerical integration. However as the element order increases, the size of the closed form generated expressions become unmanageable causing the source code files to possibly become unusable due to their size. One approach to reducing the size of the source files is to take advantage of the utilities found in CAS to identify common expressions or sub-expressions. In this manuscript we present on-going research by comparing two widely used CAS, Mathematica and Maple, as they relate to identifying common expressions in low order tetrahedral finite element stiffness matrices generated in symbolic form, associated time savings and possible issues. The results indicate that the use of CAS could be advantageously employed to identify common subexpressions through pattern matching to further reduce the size of the generated source files and realize time improvements during execution of the source codes. In addition, the developed procedures could be easily applied to higher order elements with much larger number of entries of closed form expressions where even more savings could be realized.