A Simple Study of Pleasing Parallelism on Multicore Computers

2020 ◽  
pp. 325-346
Author(s):  
Yanfei Ren ◽  
David F. Gleich
Keyword(s):  
Multicore Computers

scholarly journals Parallel Scheduling of Grid Jobs on Quadcore Systems using Grouping Methods

2021 ◽  
pp. 21-34
Author(s):  
Goodhead T. Abraham ◽  
Evans F. Osaisai ◽  
Nicholas S. Dienagha
Keyword(s):  
Scheduling Algorithm ◽  
Group Method ◽  
Sequential Method ◽  
System A ◽  
Processing Power ◽  
Significant Performance ◽  
Computing Platforms ◽  
Machine Groups ◽  
Multicore Computers ◽  
Single Processor

As Grid computing continues to make inroads into different spheres of our lives and multicore computers become ubiquitous, the need to leverage the gains of multicore computers for the scheduling of Grid jobs becomes a necessity. Most Grid schedulers remain sequential in nature and are inadequate in meeting up with the growing data and processing need of the Grid. Also, the leakage of Moore’s dividend continues as most computing platforms still depend on the underlying hardware for increased performance. Leveraging the Grid for the data challenge of the future requires a shift away from the traditional sequential method. This work extends the work of [1] on a quadcore system. A random method was used to group machines and the total processing power of machines in each group was computed, a size proportional to speed method is then used to estimates the size of jobs for allocation to machine groups. The MinMin scheduling algorithm was implemented within the groups to schedule a range of jobs while varying the number of groups and threads. The experiment was executed on a single processor system and on a quadcore system. Significant improvement was achieved using the group method on the quadcore system compared to the ordinary MinMin on the quadcore. We also find significant performance improvement with increasing groups. Thirdly, we find that the MinMin algorithm also gained marginally from the quadcore system meaning that it is also scalable.

NONLINEAR MODEL OF THE THREE-COMPONENTS COMPETITIVE ADSORPTION USING LANGMUIR EQUILIBRIUM

2021 ◽  
Vol 9 (1) ◽  
pp. 64-78
Author(s):  
I. Boyko ◽  
M. Petryk ◽  
M. Shynkaryk ◽  
O. Petryk
Keyword(s):  
High Speed ◽  
High Performance ◽  
Competitive Adsorption ◽  
Convergent Series ◽  
Temperature Phase ◽  
Adsorption Models ◽  
Temperature Phase Transition ◽  
Isothermal Gas ◽  
Multicore Computers ◽  
Operating Method

A basis for the mathematical modeling of non-isothermal gas competitive adsorption in a porous solid using Langmuir equilibrium is given. High-performance analytical solutions of considered adsorption models based on the Heaviside operating method and Landau’s decom- position and linearization approach of Langmuir equilibrium by expanding into a convergent series in the temperature phase transition point are proposed. Numerical experiments results based on high-speed computations on multicore computers are presented.

scholarly journals Developing Graph-Based Co-Scheduling Algorithms on Multicore Computers

2016 ◽  
Vol 27 (6) ◽  
pp. 1617-1632 ◽  
Author(s):  
Ligang He ◽  
Huanzhou Zhu ◽  
Stephen A. Jarvis
Keyword(s):  
Scheduling Algorithms ◽  
Multicore Computers

scholarly journals High-throughput Bayesian network learning using heterogeneous multicore computers

2010 ◽  
Author(s):  
Michael D. Linderman ◽  
Robert Bruggner ◽  
Vivek Athalye ◽  
Teresa H. Meng ◽  
Narges Bani Asadi ◽  
...  
Keyword(s):  
Bayesian Network ◽  
High Throughput ◽  
Heterogeneous Multicore ◽  
Network Learning ◽  
Multicore Computers

Programming multicore computers

2015 ◽  
Vol 58 (5) ◽  
pp. 76-76
Author(s):  
James Larus
Keyword(s):  
Multicore Computers
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