Space-Constrained Scheduling Optimization Method for Minimizing the Effects of Stacking of Trades

Existing SCS (space-constrained scheduling) studies fall short of minimizing the effect of the stacking of trades that decline productivity due to an increase in resources within a physically limited work area. This article presents a space-constrained scheduling optimization (i.e., SSO) method for minimizing the stacking of trades. It imports schedule information from the project database, extracts IFC files of construction site area from the BIM model, defines the occupation density function of each activity to track the level of stacking of trades, and identifies the optimal solution (i.e., the optimal set of pairs of execution pattern alternatives and start times of activities) by implementing genetic algorithm (GA) optimization analysis. The study is of value to practitioners because SSO provides an easy-to-use computerized tool that reduces the lengthy computations relative to data processing and GAs. Test cases verify the validity of the computational method.

A Depth-First Iterative Algorithm for the Conjugate Pair Fast Fourier Transform

The Split-Radix Fast Fourier Transform has the same low arithmetic complexity as the related Conjugate Pair Fast Fourier Transform. Both transforms have an irregular datapath structure which is straightforwardly expressed only in recursive forms. Furthermore, the conjugate pair variant has a complicated input indexing pattern which requires existing iterative implementations to rely on precomputed tables. It however allows optimization of the memory bandwidth as it requires a single twiddle factor load per radix-4 butterfly. In existing algorithms, this comes at the cost of using additional precomputed tables or performing recursive function calls. In this paper we present two novel approaches that handle both the butterfly scheduling and the input index generation of the Conjugate Pair Fast Fourier Transform. The proposed algorithm is cache-friendly because it is depth-first, non-recursive and does not rely on precomputed index tables. In order to achieve this, we relate the butterfly execution pattern of the Split-Radix and Conjugate Pair FFTs to the binary carry sequence. Based on this finding, we describe how common integer arithmetic and bitwise operations can be used to perform input reordering and depth-first traversal of the transform datapath with O(1) space complexity.<br>

A Depth-First Iterative Algorithm for the Conjugate Pair Fast Fourier Transform

The Split-Radix Fast Fourier Transform has the same low arithmetic complexity as the related Conjugate Pair Fast Fourier Transform. Both transforms have an irregular datapath structure which is straightforwardly expressed only in recursive forms. Furthermore, the conjugate pair variant has a complicated input indexing pattern which requires existing iterative implementations to rely on precomputed tables. It however allows optimization of the memory bandwidth as it requires a single twiddle factor load per radix-4 butterfly. In existing algorithms, this comes at the cost of using additional precomputed tables or performing recursive function calls. In this paper we present two novel approaches that handle both the butterfly scheduling and the input index generation of the Conjugate Pair Fast Fourier Transform. The proposed algorithm is cache-friendly because it is depth-first, non-recursive and does not rely on precomputed index tables. In order to achieve this, we relate the butterfly execution pattern of the Split-Radix and Conjugate Pair FFTs to the binary carry sequence. Based on this finding, we describe how common integer arithmetic and bitwise operations can be used to perform input reordering and depth-first traversal of the transform datapath with O(1) space complexity.<br>

Scheduling Randomization Protocol to Improve Schedule Entropy for Multiprocessor Real-Time Systems

Because most tasks on real-time systems are conducted periodically, its execution pattern is highly predictable. While such a property of real-time systems allows developing the strong schedulability analysis tools providing high analytical capability, it also leads that security attackers could analyze the predictable execution patterns of real-time systems and use them as attack surfaces. Among the few approaches to foil such a timing-inference security attack, TaskShuffler as a schedule randomization protocol received considerable attention owing to its simplicity and applicability. However, the existing TaskShuffler is only applicable to uniprocessor platforms, where the task execution pattern is quite simple to analyze when compared to multiprocessor platforms. In this study, we propose a new schedule randomization protocol for real-time systems on symmetry multiprocessor platforms where all processors are composed of the same architecture, which extends the existing TaskShuffler initially designed for uniprocessor platforms.

Comparison and Evaluation of Organizational Transactions for Continuous Auditing and Business Compliance

This article presents a comparator module which aims to compare, in real time, executions of organizational transactions with patterns of behaviors of these transaction executions, allowing the determination of which execution pattern is being followed by running each transaction. This is according to information received by the internal control mechanisms, which continuously monitors the transaction executions. A possible application using this module was deployed and results were obtained from a case study. The results prove effectiveness of the module, mainly because it is able to assess business compliance and the qualitative risk associated to each transaction execution while it is running, enabling an efficient continuous auditing application. The innovation of this article is ensured by the use of an ontological model to represent organizational transactions, which can be applicable to any type of transaction in any business area in order to audit transactions at a very low level, contrary to what happens in traditional auditing, which occurs at a high level (e.g. compare whether a completed transaction has followed a set of procedures). Besides the conceptualization, this work presents some technical details of development and discussion of results from the case study.

Test Case Selection Using Feature Extraction and Clustering

This article explains the selection of important parameters from an execution pattern which brings out the details of the application of test cases. Hence, execution profiles are captured and a new execution profile-based clustering approach is chosen for test case selection, which uses three new features. These are Function frequency, Branches taken and Block percentage. The test cases are clustered using the extracted features. The experiments show that the proposed FBB selects smaller size of more relevant test cases which are more fault revealing compared to the existing Function Call Profile approach.

HIGH-PERFORMANCE MATHEMATICAL FUNCTIONS FOR SINGLE-CORE ARCHITECTURES

Nowadays high-performance computing (HPC) architectures are designed to resolve assorted sophisticated scientific as well as engineering problems across an ever intensifying number of HPC and professional workloads. Application and computation of key trigonometric functions sine and cosine are in all spheres of our daily life, yet fairly time consuming task in high-performance numerical simulations. In this paper, we have delivered a detailed deliberation of how the micro-architecture of single-core Itanium® and Alpha 21264/21364 processors as well as the manual optimization techniques improve the computing performance of several mathematical functions. On describing the detailed algorithm and its execution pattern on the processor, we have confirmed that the processor micro-architecture side by side manual optimization techniques ameliorate computing performance significantly as compared to not only the standard math library's built-in functions with compiler optimizing options but also Intel® Itanium® library's highly optimized mathematical functions.