Revisiting the Sequential Programming Model for the Multicore Era

IEEE Micro ◽  
2008 ◽  
Vol 28 (1) ◽  
pp. 12-20 ◽  
Author(s):  
Matthew J. Bridges ◽  
Neil Vachharajani ◽  
Yun Zhang ◽  
Thomas Jablin ◽  
David I. August
Keyword(s):  
Programming Model ◽  
Sequential Programming

Revisiting the Sequential Programming Model for Multi-Core

2007 ◽  
Author(s):  
Matthew Bridges ◽  
Neil Vachharajani ◽  
Yun Zhang ◽  
Thomas Jablin ◽  
David August
Keyword(s):  
Programming Model ◽  
Sequential Programming

Simultaneous MultiThreading Microarchitecture

2010 ◽  
pp. 552-582
Author(s):  
Chen Liu ◽  
Xiaobin Li ◽  
Shaoshan Liu ◽  
Jean-Luc Gaudiot
Keyword(s):  
Resource Sharing ◽  
High Performance ◽  
Programming Model ◽  
Clock Cycle ◽  
Vital Role ◽  
Simultaneous Multithreading ◽  
Sequential Programming ◽  
Parallel Programming Model ◽  
Key Aspects ◽  
Level Parallelism

Due to the conventional sequential programming model, the Instruction-Level Parallelism (ILP) that modern superscalar processors can explore is inherently limited. Hence, multithreading architectures have been proposed to exploit Thread-Level Parallelism (TLP) in addition to conventional ILP. By issuing and executing instructions from multiple threads at each clock cycle, Simultaneous MultiThreading (SMT) achieves some of the best possible system resource utilization and accordingly higher instruction throughput. In this chapter, the authors describe the origin of SMT microarchitecture, comparing it with other multithreading microarchitectures. They identify several key aspects for high-performance SMT design: fetch policy, handling long-latency instructions, resource sharing control, synchronization and communication. They also describe some potential benefits of SMT microarchitecture: SMT for faulttolerance and SMT for secure communications. Given the need to support sequential legacy code and emerge of new parallel programming model, we believe SMT microarchitecture will play a vital role as we enter the multi-thread multi/many-core processor design era.

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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