scholarly journals A Scenario-Aware Dataflow Programming Model

2015 ◽  
Author(s):  
Reinier Van Kampenhout ◽  
Sander Stuijk ◽  
Kees Goossens
Keyword(s):  
Programming Model ◽  
Dataflow Programming

Handling Iterations in Distributed Dataflow Systems

2022 ◽  
Vol 54 (9) ◽  
pp. 1-38
Author(s):  
Gábor E. Gévay ◽  
Juan Soto ◽  
Volker Markl
Keyword(s):  
Programming Model ◽  
Iterative Algorithms ◽  
Research Literature ◽  
Control Flow ◽  
Programming Models ◽  
Program Execution ◽  
The Past ◽  
Standard Technology ◽  
Dataflow Programming

Over the past decade, distributed dataflow systems (DDS) have become a standard technology. In these systems, users write programs in restricted dataflow programming models, such as MapReduce, which enable them to scale out program execution to a shared-nothing cluster of machines. Yet, there is no established consensus that prescribes how to extend these programming models to support iterative algorithms. In this survey, we review the research literature and identify how DDS handle control flow, such as iteration, from both the programming model and execution level perspectives. This survey will be of interest for both users and designers of DDS.

scholarly journals HitFlow: A Dataflow Programming Model for Hybrid Distributed- and Shared-Memory Systems

2018 ◽  
Vol 47 (1) ◽  
pp. 3-23
Author(s):  
Javier Fresno ◽  
Daniel Barba ◽  
Arturo Gonzalez-Escribano ◽  
Diego R. Llanos
Keyword(s):  
Shared Memory ◽  
Programming Model ◽  
Memory Systems ◽  
Dataflow Programming

scholarly journals A Power-Aware, Self-Adaptive Macro Data Flow Framework

2017 ◽  
Vol 27 (01) ◽  
pp. 1740004 ◽  
Author(s):  
Marco Danelutto ◽  
Daniele De Sensi ◽  
Massimo Torquati
Keyword(s):  
Parallel Programming ◽  
Shared Memory ◽  
Programming Model ◽  
Optimal Number ◽  
Parallel Applications ◽  
User Requirements ◽  
Effective Solution ◽  
Clock Frequency ◽  
Dataflow Programming ◽  
Application Execution

The dataflow programming model has been extensively used as an effective solution to implement efficient parallel programming frameworks. However, the amount of resources allocated to the runtime support is usually fixed once by the programmer or the runtime, and kept static during the entire execution. While there are cases where such a static choice may be appropriate, other scenarios may require to dynamically change the parallelism degree during the application execution. In this paper we propose an algorithm for multicore shared memory platforms, that dynamically selects the optimal number of cores to be used as well as their clock frequency according to either the workload pressure or to explicit user requirements. We implement the algorithm for both structured and unstructured parallel applications and we validate our proposal over three real applications, showing that it is able to save a significant amount of power, while not impairing the performance and not requiring additional effort from the application programmer.

A Linear Programming Model for Product Mix Profit Maximization in A Small Medium Enterprise Company

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
S Mohd Baki ◽  
Jack Kie Cheng
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Business Performance ◽  
Programming Model ◽  
Profit Maximization ◽  
Optimal Level ◽  
Linear Programming Model ◽  
Product Mix ◽  
Small Medium Enterprises ◽  
Medium Enterprises

Production planning is often challenging for small medium enterprises (SMEs) company. Most of the SMEs are having difficulty in determining the optimal level of the production output which can affect their business performance. Product mix optimization is one of the main key for production planning. Many company have used linear programming model in determining the optimal combination of various products that need to be produced in order to maximize profit. Thus, this study aims for profit maximization of a SME company in Malaysia by using linear programming model. The purposes of this study are to identify the current process in the production line and to formulate a linear programming model that would suggest a viable product mix to ensure optimum profitability for the company. ABC Sdn Bhd is selected as a case study company for product mix profit maximization study. Some conclusive observations have been drawn and recommendations have been suggested. This study will provide the company and other companies, particularly in Malaysia, an exposure of linear programming method in making decisions to determine the maximum profit for different product mix.

Power Generation for India with Higher Efficiency

2018 ◽  
Vol 6 (7) ◽  
pp. 267
Author(s):  
Umeshkannan P ◽  
Muthurajan KG
Keyword(s):  
Power Generation ◽  
Objective Function ◽  
Fossil Fuels ◽  
Programming Model ◽  
Developed Countries ◽  
Power Requirement ◽  
Average Efficiency ◽  
Potential Demand ◽  
The Developed Countries ◽  
Developed Nations

The developed countries are consuming more amount of energy in all forms including electricity continuously with advanced technologies.  Developing  nation’s  energy usage trend rises quickly but very less in comparison with their population and  their  method of generating power is not  seems  to  be  as  advanced  as  developed  nations. The   objective   function   of   this   linear   programming model is to maximize the average efficiency of power generation inIndia for 2020 by giving preference to energy efficient technologies. This model is subjected to various constraints like potential, demand, running cost and Hydrogen / Carbon ratio, isolated load, emission and already installed capacities. Tora package is used to solve this linear program. Coal,  Gas,  Hydro  and  Nuclear  sources can are  supply around 87 %  of  power  requirement .  It’s concluded that we can produce power  at  overall  efficiency  of  37%  while  meeting  a  huge demand  of  13,00,000  GWh  of  electricity.  The objective function shows the scenario of highaverage efficiency with presence of 9% renewables. Maximum value   is   restricted   by   low   renewable   source’s efficiencies, emission constraints on fossil fuels and cost restriction on some of efficient technologies. This    model    shows    that    maximum    18%    of    total requirement   can   be   met   by   renewable itself which reduces average efficiency to 35.8%.   Improving technologies  of  renewable  sources  and  necessary  capacity addition  to  them in  regular  interval  will  enhance  their  role and existence against fossil fuels in future. The work involves conceptualizing, modeling, gathering information for data’s to be used in model for problem solving and presenting different scenarios for same objective.

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