scholarly journals Towards multi-threaded local tabling using a common table space

2012 ◽  
Vol 12 (4-5) ◽  
pp. 427-443 ◽  
Author(s):  
MIGUEL AREIAS ◽  
RICARDO ROCHA
Keyword(s):  
Experimental Results ◽  
Alternative View ◽  
Memory Usage ◽  
Running Time ◽  
Evaluation Strategy ◽  
Procedural Control ◽  
Declarative Semantics ◽  
Space Approach

AbstractMulti-threading is currently supported by several well-known Prolog systems providing a highly portable solution for applications that can benefit from concurrency. When multi-threading is combined with tabling, we can exploit the power of higher procedural control and declarative semantics. However, despite the availability of both threads and tabling in some Prolog systems, the implementation of these two features implies complex ties to each other and to the underlying engine. Until now, XSB was the only Prolog system combining multi-threading with tabling. In XSB, tables may be either private or shared between threads. While thread-private tables are easier to implement, shared tables have all the associated issues of locking, synchronization and potential deadlocks. In this paper, we propose an alternative view to XSB's approach. In our proposal, each thread views its tables as private but, at the engine level, we use a common table space where tables are shared among all threads. We present three designs for our common table space approach: No-Sharing (NS) (similar to XSB's private tables), Subgoal-Sharing (SS) and Full-Sharing (FS). The primary goal of this work was to reduce the memory usage for the table space but, our experimental results, using the YapTab tabling system with a local evaluation strategy, show that we can also achieve significant reductions on running time.

scholarly journals Max-Min Processors Scheduling

2021 ◽  
Vol 50 (1) ◽  
pp. 5-12
Author(s):  
Hani Alquhayz ◽  
Mahdi Jemmali
Keyword(s):  
Literature Review ◽  
Knapsack Problem ◽  
Completion Time ◽  
Research Work ◽  
Parallel Processors ◽  
Experimental Results ◽  
Running Time ◽  
Similar Performance ◽  
Minimum Completion Time ◽  
Randomization Method

This paper focuses on the maximization of the minimum completion time on identical parallel processors. The objective of this maximization is to ensure fair distribution. Let a set of jobs to be assigned to several identical parallel processors. This problem is shown as NP-hard. The research work of this paper is based essentially on the comparison of the proposed heuristics with others cited in the literature review. Our heuristics are developed using essentially the randomization method and the iterative utilization of the knapsack problem to solve the studied problem. Heuristics are assessed by several instances represented in the experimental results. The results show that the knapsack based heuristic gives almost a similar performance than heuristic in a literature review but in better running time.  

Mining of top-k high utility itemsets with negative utility

2020 ◽  
pp. 1-16
Author(s):  
Rui Sun ◽  
Meng Han ◽  
Chunyan Zhang ◽  
Mingyao Shen ◽  
Shiyu Du
Keyword(s):  
Data Mining ◽  
Search Space ◽  
Experimental Results ◽  
Effective Algorithm ◽  
Memory Usage ◽  
Utility Value ◽  
Itemset Mining ◽  
High Utility ◽  
High Utility Itemsets

High utility itemset mining(HUIM) with negative utility is an emerging data mining task. However, the setting of the minimum utility threshold is always a challenge when mining high utility itemsets(HUIs) with negative items. Although the top-k HUIM method is very common, this method can only mine itemsets with positive items, and the problem of missing itemsets occurs when mining itemsets with negative items. To solve this problem, we first propose an effective algorithm called THN (Top-k High Utility Itemset Mining with Negative Utility). It proposes a strategy for automatically increasing the minimum utility threshold. In order to solve the problem of multiple scans of the database, it uses transaction merging and dataset projection technology. It uses a redefined sub-tree utility value and a redefined local utility value to prune the search space. Experimental results on real datasets show that THN is efficient in terms of runtime and memory usage, and has excellent scalability. Moreover, experiments show that THN performs particularly well on dense datasets.

scholarly journals RDFuzz: Accelerating Directed Fuzzing with Intertwined Schedule and Optimized Mutation

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Jiaxi Ye ◽  
Ruilin Li ◽  
Bin Zhang
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
The State ◽  
Experimental Results ◽  
Exploration And Exploitation ◽  
Balance Problem ◽  
Evaluation Strategy ◽  
Testing Schedule ◽  
Available Resources

Directed fuzzing is a practical technique, which concentrates its testing energy on the process toward the target code areas, while costing little on other unconcerned components. It is a promising way to make better use of available resources, especially in testing large-scale programs. However, by observing the state-of-the-art-directed fuzzing engine (AFLGo), we argue that there are two universal limitations, the balance problem between the exploration and the exploitation and the blindness in mutation toward the target code areas. In this paper, we present a new prototype RDFuzz to address these two limitations. In RDFuzz, we first introduce the frequency-guided strategy in the exploration and improve its accuracy by adopting the branch-level instead of the path-level frequency. Then, we introduce the input-distance-based evaluation strategy in the exploitation stage and present an optimized mutation to distinguish and protect the distance sensitive input content. Moreover, an intertwined testing schedule is leveraged to perform the exploration and exploitation in turn. We test RDFuzz on 7 benchmarks, and the experimental results demonstrate that RDFuzz is skilled at driving the program toward the target code areas, and it is not easily stuck by the balance problem of the exploration and the exploitation.

A Hyper-Heuristic Using GRASP with Path-Relinking

2011 ◽  
Vol 4 (2) ◽  
pp. 31-42 ◽  
Author(s):  
He Jiang ◽  
Junying Qiu ◽  
Jifeng Xuan
Keyword(s):  
Simulated Annealing ◽  
Local Search ◽  
Iterative Procedure ◽  
Experimental Results ◽  
Path Relinking ◽  
Nurse Rostering ◽  
Primary Motivation ◽  
Running Time ◽  
Nurse Rostering Problem

The goal of hyper-heuristics is to design and choose heuristics to solve complex problems. The primary motivation behind the hyper-heuristics is to generalize the solving ability of the heuristics. In this paper, the authors propose a Hyper-heuristic using GRASP with Path-Relinking (HyGrasPr). HyGrasPr generates heuristic sequences to produce solutions within an iterative procedure. The procedure of HyGrasPr consists of three phases, namely the construction phase, the local search phase, and the path-relinking phase. To show the performance of the HyGrasPr, the authors use the nurse rostering problem as a case study. The authors use an existing simulated annealing based hyper-heuristic as a baseline. The experimental results indicate that HyGrasPr can achieve better solutions than SAHH within the same running time and the path-relinking phase is effective for the framework of HyGrasPr.

scholarly journals Hybrid Grammars for Parsing of Discontinuous Phrase Structures and Non-Projective Dependency Structures

2017 ◽  
Vol 43 (3) ◽  
pp. 465-520 ◽  
Author(s):  
Kilian Gebhardt ◽  
Mark-Jan Nederhof ◽  
Heiko Vogler
Keyword(s):  
Time Complexity ◽  
Hierarchical Structures ◽  
Experimental Results ◽  
Grammar Induction ◽  
Linear Structures ◽  
Syntactic Structures ◽  
Running Time ◽  
Dependency Structures ◽  
Time Accuracy

We explore the concept of hybrid grammars, which formalize and generalize a range of existing frameworks for dealing with discontinuous syntactic structures. Covered are both discontinuous phrase structures and non-projective dependency structures. Technically, hybrid grammars are related to synchronous grammars, where one grammar component generates linear structures and another generates hierarchical structures. By coupling lexical elements of both components together, discontinuous structures result. Several types of hybrid grammars are characterized. We also discuss grammar induction from treebanks. The main advantage over existing frameworks is the ability of hybrid grammars to separate discontinuity of the desired structures from time complexity of parsing. This permits exploration of a large variety of parsing algorithms for discontinuous structures, with different properties. This is confirmed by the reported experimental results, which show a wide variety of running time, accuracy, and frequency of parse failures.

scholarly journals Liver Segmentation Based on Snakes Model and Improved GrowCut Algorithm in Abdominal CT Image

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Huiyan Jiang ◽  
Baochun He ◽  
Zhiyuan Ma ◽  
Mao Zong ◽  
Xiangrong Zhou ◽  
...  
Keyword(s):  
Ct Images ◽  
Experimental Results ◽  
Initial Contour ◽  
Segmentation Result ◽  
Ct Image ◽  
Liver Segmentation ◽  
Abdominal Ct ◽  
Running Time ◽  
Novel Method ◽  
Liver Region

A novel method based on Snakes Model and GrowCut algorithm is proposed to segment liver region in abdominal CT images. First, according to the traditional GrowCut method, a pretreatment process using K-means algorithm is conducted to reduce the running time. Then, the segmentation result of our improved GrowCut approach is used as an initial contour for the future precise segmentation based on Snakes model. At last, several experiments are carried out to demonstrate the performance of our proposed approach and some comparisons are conducted between the traditional GrowCut algorithm. Experimental results show that the improved approach not only has a better robustness and precision but also is more efficient than the traditional GrowCut method.

scholarly journals Management and Plan of Undergraduates’ Mental Health Based on Keyword Extraction

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Weifeng Zhang
Keyword(s):  
Mental Health ◽  
Recall Rate ◽  
Social Attention ◽  
Experimental Results ◽  
Keyword Extraction ◽  
Health Issues ◽  
Running Time ◽  
Upper Approximation ◽  
Mental Health Issues ◽  
The Social

Mental health issues are alarmingly on the rise among undergraduates, which have gradually become the focus of social attention. With the emergence of some abnormal events such as more and more undergraduates’ suspension, and even suicide due to mental health issues, the social attention to undergraduates’ mental health has reached a climax. According to the questionnaire of undergraduates’ mental health issues, this paper uses keyword extraction to analyze the management and plan of undergraduates’ mental health. Based on the classical TextRank algorithm, this paper proposes an improved TextRank algorithm based on upper approximation rough data-deduction. The experimental results show that the accurate rate, recall rate, and F1 of proposed algorithm have been significantly improved, and the experimental results also demonstrate that the proposed algorithm has good performance in running time and physical memory occupation.

scholarly journals IMAGE FAST DEHAZING ALGORITHM BASED ON DARK CHANNEL PRIOR IMPROVEMENT

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 585-589
Author(s):  
J. W. Li ◽  
L. Liu ◽  
J. W. Jiang ◽  
Y. Hu ◽  
X. Q. Han ◽  
...  
Keyword(s):  
Gamma Function ◽  
Information Entropy ◽  
Experimental Results ◽  
Guided Filter ◽  
Dark Channel Prior ◽  
Two Dimensional ◽  
Image Dehazing ◽  
Running Time ◽  
Dark Channel ◽  
Intensity Image

Abstract. Aiming at the long-running time and the defogging image darkening problem in the dark channel prior algorithm, a fast deaeration algorithm based on the guided filter and improved two-dimensional gamma function for dark channel prior image is proposed. The algorithm uses the guided filter instead of the soft matting to obtain the image transmittance. The summation operation in the window replaces the quadrature operation in the window to reduce the complexity of the algorithm, and the image is processed by the two-dimensional gamma function. The brightness is adjusted to increase the brightness of the dark areas of the image, improve the contrast of the image, and enhance the image's performance in detail. The experimental results show that compared with the dark channel prior defogging algorithm and other image dehazing algorithms, the image fast dehazing algorithm based on dark channel prior improvement has high effective detail intensity, image information entropy and average gradient. The running time of the dark channel prior defogging algorithm is reduced, which effectively solves the long running time and the defogging image darkness problem of the dark channel prior defogging algorithm and has good robustness, and improves the quality and display effects of defogging image.

scholarly journals Dynamic Programming Algorithms for Computing Optimal Knockout Tournaments

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2480
Author(s):  
Amelia Bădică ◽  
Costin Bădică ◽  
Ion Buligiu ◽  
Liviu Ion Ciora ◽  
Doina Logofătu
Keyword(s):  
Dynamic Programming ◽  
Complexity Analysis ◽  
Dynamic Programming Algorithm ◽  
Experimental Results ◽  
Programming Algorithm ◽  
Programming Approach ◽  
Optimal Algorithms ◽  
Running Time ◽  
Dynamic Programming Approach ◽  
Programming Algorithms

We study competitions structured as hierarchically shaped single-elimination tournaments. We define optimal tournaments by maximizing attractiveness such that the topmost players will have the chance to meet in higher stages of the tournament. We propose a dynamic programming algorithm for computing optimal tournaments and we provide its sound complexity analysis. Based on the idea of the dynamic programming approach, we also develop more efficient deterministic and stochastic sub-optimal algorithms. We present experimental results obtained with the Python implementation of all the proposed algorithms regarding the optimality of solutions and the efficiency of the running time.

Alleviating the Thrashing by Adding Medium- Term Scheduler

2010 ◽  
pp. 118-136
Author(s):  
Moses Reuven ◽  
Yair Wiseman
Keyword(s):  
Operating System ◽  
Approximation Algorithms ◽  
Shared Memory ◽  
Bin Packing ◽  
Memory Capacity ◽  
Substantial Improvement ◽  
Experimental Results ◽  
Memory Usage ◽  
Medium Term ◽  
Short Term

A technique for minimizing the paging on a system with a very heavy memory usage is proposed. When there are processes with active memory allocations that should be in the physical memory, but their accumulated size exceeds the physical memory capacity. In such cases, the operating system begins swapping pages in and out the memory on every context switch. The authors lessen this thrashing by placing the processes into several bins, using Bin Packing approximation algorithms. They amend the scheduler to maintain two levels of scheduling - medium-term scheduling and short-term scheduling. The mediumterm scheduler switches the bins in a Round-Robin manner, whereas the short-term scheduler uses the standard Linux scheduler to schedule the processes in each bin. The authors prove that this feature does not necessitate adjustments in the shared memory maintenance. In addition, they explain how to modify the new scheduler to be compatible with some elements of the original scheduler like priority and realtime privileges. Experimental results show substantial improvement on very loaded memories.

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