scholarly journals Java Script Data Transformation Library using Fork Join Pool and Web Workers Technology

2019 ◽  
Vol 9 (2) ◽  
pp. 1609-1614
Keyword(s):  
Parallel Processing ◽  
Parallel Programming ◽  
Programming Language ◽  
Processing Time ◽  
Optimization Technique ◽  
Data Transformation ◽  
Testing Phase ◽  
Use Of Data ◽  
Multi Core Processor

Transforming large amounts of data takes a lot of processing time so that the optimization technique is required. One way that can be used to perform optimization is multithreading. Nowadays, processor is proliferating. The average processor in community is multi-core processor that can do parallel processing. Prior to the emergence of Web Workers, JavaScript is a poor programming language for parallel programming. The emergence of Web Workers allows JavaScript to do a better job in parallel programming. Fork Join Pool is a method that implements the Divide and Conquers algorithm, so it is suitable for the use in multithreading. This data transformation library was created by implementing the ForkJoinPool method using Web Workers technology in JavaScript. This program is written in JavaScript and HTML language. Based on results of testing phase that has been done, it is proven that ForkJoinPool method can be implemented using Web Workers technology in JavaScript as a data transformation library. In addition, it can be concluded that the data transformation library usage affects the speed of data transformation which depends on the data transformation complexity. The higher the complexity of data transformation performed, the effectiveness in the use of data transformation libraries will increase.

A Multitask Parallel Algorithm Based on Multi-Core Processor

2013 ◽  
Vol 765-767 ◽  
pp. 2590-2594
Author(s):  
Qian Jin Wang
Keyword(s):  
Parallel Processing ◽  
Parallel Algorithm ◽  
Data Handling ◽  
Process Data ◽  
Operation Speed ◽  
Processing Data ◽  
Parallel Data ◽  
Hardware Resource ◽  
Parallel Speedup ◽  
Multi Core Processor

Multi-core processor has been a hot topic since it improves operation speed. It is not easy to get efficient parallel processing data algorithms because of waste of hardware resources. In this paper, a novel multitask parallel algorithm based on getting common substring of two strings is described in order to improve the data-handling capacity of the multi-processor. Firstly, this algorithm performs Task Parallel Library (TPL) in VS.NET, and then schedule the algorithm proposed in this paper to process data. This algorithm is tested by actual parallel data. The results demonstrate that this algorithm overcomes the problem of waste of hardware resource, can take full advantage of the features of multi-core parallel processing data thereby enhancing the parallel speedup, greatly improving the efficiency of data processing.

Parallel Programming Language Adetran

1995 ◽  
pp. 429-465
Author(s):  
Koji Zaiki ◽  
Akiyoshi Wakatani ◽  
Tadashi Okamoto ◽  
Katsuyuki Kaneko ◽  
Tatsuo Nogi
Keyword(s):  
Parallel Programming ◽  
Programming Language ◽  
Parallel Programming Language

scholarly journals Parallel programming technologies on computer complexes

2020 ◽  
Vol 30 (3) ◽  
pp. 28-33 ◽  
Author(s):  
S. A. Pryadko ◽  
A. Yu. Troshin ◽  
V. D. Kozlov ◽  
A. E. Ivanov
Keyword(s):  
Parallel Programming ◽  
Shared Memory ◽  
Programming Language ◽  
Operating Systems ◽  
Distributed Memory ◽  
Programming Models ◽  
Writing Programs ◽  
Advantages And Disadvantages ◽  
C Programming Language ◽  
C Programming

The article describes various options for speeding up calculations on computer systems. These features are closely related to the architecture of these complexes. The objective of this paper is to provide necessary information when selecting the capability for the speeding process of solving the computation problem. The main features implemented using the following models are described: programming in systems with shared memory, programming in systems with distributed memory, and programming on graphics accelerators (video cards). The basic concept, principles, advantages, and disadvantages of each of the considered programming models are described. All standards for writing programs described in the article can be used both on Linux and Windows operating systems. The required libraries are available and compatible with the C/C++ programming language. The article concludes with recommendations on the use of a particular technology, depending on the type of task to be solved.

scholarly journals Implementasi Pengisian Register Data dan Oprasi Aritmatika Menggunakan Program Cammand Prompt, Bahasa assembler

JURTEKSI ◽  
2017 ◽  
Vol 4 (1) ◽  
pp. 51-56
Author(s):  
Hambali Hambali
Keyword(s):  
Programming Language ◽  
Input Data ◽  
Register Data ◽  
Application Program ◽  
Assembler Language ◽  
Use Of Data ◽  
Application Data ◽  
Data Register

Abstract: Based on the type of information stored microprocessors can be divided into data registers, address registers, register flags and instruction registers. The filling of the application data register can be done by filling the register data AX, BX, CX, DX with the integration of 8 bit and 16 bit microprocessors with register AH, AL, BH, BL to DH register, DL using some programming language command assembler and application program run, cmd and commanprompt. Input data register on the use of data filling in data registers and address registers can be seen from some initial input registers are desired. Keywords: data registers, assembler language Abstrak: Berdasarkan jenis informasi yang disimpan mikroprosesor dapat dibagi menjadi register data, register alamat, register flag dan register instruksi. Pengisian register data penerapannya dapat dilakukan dengan dengan pengisian data register AX,BX,CX,DX dengan penggabungan mikrprosesor 8 bit dan 16 bit dengan register AH,AL,BH,BL sampai dengan register DH, DL menggunakan beberapa perintah bahasa pemograman assembler dan aplikasi program run, cmd dan commandprompt. Inputan data register pada penggunaan pengisian data pada register data dan register alamat dapat dilihat dari beberapa inputan register awal yang diinginkan. Kata kunci: register data, bahasa assembler

Scheduling and stability aspects of a general class of parallel processing systems

1993 ◽  
Vol 25 (1) ◽  
pp. 176-202 ◽  
Author(s):  
Nicholas Bambos ◽  
Jean Walrand
Keyword(s):  
Asymptotic Behavior ◽  
Parallel Processing ◽  
General Class ◽  
Processing Time ◽  
Arrival Time ◽  
System Designer ◽  
Scheduling Policy ◽  
Concurrent Processing ◽  
Random Flow ◽  
Random Amount

In this paper we study the following general class of concurrent processing systems. There are several different classes of processors (servers) and many identical processors within each class. There is also a continuous random flow of jobs, arriving for processing at the system. Each job needs to engage concurrently several processors from various classes in order to be processed. After acquiring the needed processors the job begins to be executed. Processing is done non-preemptively, lasts for a random amount of time, and then all the processors are released simultaneously. Each job is specified by its arrival time, its processing time, and the list of processors that it needs to access simultaneously. The random flow (sequence) of jobs has a stationary and ergodic structure. There are several possible policies for scheduling the jobs on the processors for execution; it is up to the system designer to choose the scheduling policy to achieve certain objectives.We focus on the effect that the choice of scheduling policy has on the asymptotic behavior of the system at large times and especially on its stability, under general stationary and ergocic input flows.

Analysis of Segmentation Parameters Effect towards Parallel Processing Time on Fuzzy C Means Algorithm

2018 ◽  
Vol 1 (4) ◽  
pp. 99
Author(s):  
Cepi Ramdani ◽  
Indah Soesanti ◽  
Sunu Wibirama
Keyword(s):  
Parallel Processing ◽  
Processing Time ◽  
Color Image ◽  
Clustering Algorithms ◽  
Fuzzy C Means ◽  
Sequential Processing ◽  
Processing Times ◽  
Parameter Values ◽  
Fuzzy C Means Algorithm ◽  
Segmentation Parameters

Fuzzy C Means algorithm or FCM is one of many clustering algorithms that has better accuracy to solve problems related to segmentation. Its application is almost in every aspects of life and many disciplines of science. However, this algorithm has some shortcomings, one of them is the large amount of processing time consumption. This research conducted mainly to do an analysis about the effect of segmentation parameters towards processing time in sequential and parallel. The other goal is to reduce the processing time of segmentation process using parallel approach. Parallel processing applied on Nvidia GeForce GT540M GPU using CUDA v8.0 framework. The experiment conducted on natural RGB color image sized 256x256 and 512x512. The settings of segmentation parameter values were done as follows, weight in range (2-3), number of iteration (50-150), number of cluster (2-8), and error tolerance or epsilon (0.1 – 1e-06). The results obtained by this research as follows, parallel processing time is faster 4.5 times than sequential time with similarity level of image segmentations generated both of processing types is 100%. The influence of segmentation parameter values towards processing times in sequential and parallel can be concluded as follows, the greater value of weight parameter then the sequential processing time becomes short, however it has no effects on parallel processing time. For iteration and cluster parameters, the greater their values will make processing time consuming in sequential and parallel become large. Meanwhile the epsilon parameter has no effect or has an unpredictable tendency on both of processing time.

SC-EXPRESSIONS IN OBJECT-ORIENTED LANGUAGES

2007 ◽  
Vol 18 (06) ◽  
pp. 1441-1452
Author(s):  
SHENG YU ◽  
QING ZHAO
Keyword(s):  
Parallel Programming ◽  
Programming Language ◽  
Object Oriented ◽  
Automata Theory ◽  
Basic Ideas ◽  
Basic Features ◽  
Synchronization Constraints ◽  
Object Oriented Languages ◽  
Parallel Programming Language

In this paper, SC-expressions are developed, based on automata theory, for specifying synchronization constraints in parallel object-oriented languages. The predecessor of SC-expressions, the synchronization expressions, was introduced in the ParC parallel programming language in the early nineties [19]. However, ParC is not an object-oriented language and also a number of basic features of synchronization expressions are inadequate for object-oriented languages. SC-expressions are developed for object-oriented environment. They are different from synchronization expressions in basic ideas and assumptions. Here we describe the basic ideas of SC-expressions and their applications in object-oriented languages. We also study the problem of inheritance of the SC-expressions.

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