Evaluation and analysis of a dynamic allocation scheme on a C++-based parallel programming library

2000 ◽  
Author(s):  
T. Tezuka ◽  
B.O. Apduhan ◽  
T. Sueyoshi ◽  
I. Arita
Keyword(s):  
Parallel Programming ◽  
Allocation Scheme ◽  
Dynamic Allocation ◽  
Programming Library

A three-dimensional dynamic allocation scheme for WDM-OFDM-PON

2015 ◽  
pp. 133-136
Author(s):  
Jun Jiang ◽  
Min Zhang ◽  
Yang Yang ◽  
Zhuo Liu ◽  
Xue Chen
Keyword(s):  
Three Dimensional ◽  
Allocation Scheme ◽  
Dynamic Allocation

scholarly journals A Dynamic Allocation Scheme for Resource Blocks Using ARQ Status Reports in LTE Networks

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Sacrifice Nana-Kyere ◽  
Francis Agyei Boateng ◽  
Glory Kofi Hoggar ◽  
Paddy Jonathan
Keyword(s):  
Allocation Scheme ◽  
Dynamic Allocation ◽  
Lte Networks

scholarly journals THE INTEGRATION OF TASK AND DATA PARALLEL SKELETONS

2002 ◽  
Vol 12 (02) ◽  
pp. 141-155 ◽  
Author(s):  
HERBERT KUCHEN ◽  
MURRAY COLE
Keyword(s):  
Parallel Programming ◽  
Travelling Salesman Problem ◽  
Travelling Salesman ◽  
Data Parallel ◽  
Programming Library ◽  
Parallel Skeletons

We describe a skeletal parallel programming library which integrates task and data parallel constructs within an API for C++. Traditional skeletal requirements for higher orderness and polymorphism are achieved through exploitation of operator overloading and templates, while the underlying parallelism is provided by MPI. We present a case study describing two algorithms for the travelling salesman problem.

scholarly journals Calcul parallèle appliqué aux écoulements de fluides complexes

2007 ◽  
pp. 703-722
Author(s):  
Hugues Digonnet ◽  
Olivier Basset ◽  
Luisa Silva ◽  
Thierry Coupez
Keyword(s):  
Numerical Simulations ◽  
Parallel Programming ◽  
Linear Systems ◽  
Fluid Flows ◽  
Computational Results ◽  
Specific Language ◽  
Pc Cluster ◽  
Programming Library ◽  
Parallelization Strategy ◽  
Complex Fluid

In this paper we present numerical simulations of complex fluid flows performed on a PC cluster. These simulations were possible thanks to a parallelization strategy that is transparent and efficient: each developer does not need to know a parallel programming library and its specific language. Instead, he uses purely SPMD tools to build their applications. Two examples are shown, as well as the computational results obtained for problems that need the resolution of linear Systems of over 7 million of unknowns.

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