Foundations for multifile design by application partitioning

1982 ◽  
Author(s):  
Doron Rotem ◽  
Frank Wm. Tompa ◽  
David Kirkpatrick
Keyword(s):  
Application Partitioning

scholarly journals A framework for application partitioning using trusted execution environments

2017 ◽  
Vol 29 (23) ◽  
pp. e4130 ◽  
Author(s):  
Ahmad Atamli-Reineh ◽  
Andrew Paverd ◽  
Giuseppe Petracca ◽  
Andrew Martin
Keyword(s):  
Application Partitioning

CIGAR: Application Partitioning for a CPU/Coprocessor Architecture

2007 ◽  
Author(s):  
John H. Kelm ◽  
Isaac Gelado ◽  
Mark J. Murphy ◽  
Nacho Navarro ◽  
Steve Lumetta ◽  
...  
Keyword(s):  
Application Partitioning

scholarly journals Performance and energy optimization of heterogeneous CPU-GPU systems for embedded applications

2021 ◽  
Author(s):  
Abdullah Siddiqui
Keyword(s):  
Embedded Systems ◽  
Power Consumption ◽  
Optimization Algorithm ◽  
Heterogeneous Computing ◽  
Energy Optimization ◽  
Systems Design ◽  
Application Partitioning ◽  
Computing Platforms ◽  
Embedded Applications ◽  
Software Partitioning

One of the most critical steps of embedded systems design is Hardware-Software partitioning. It is characterized by distributing the components of an application between hardware and software such that the user defined system constraints are satisfied. Heterogeneous computing platforms consisting of CPUs and GPUs have tremendous potential for enhancing the performance of embedded applications. The challenge of application partitioning for CPU-GPU mapping is much greater on such platforms due to their unique and diverse characteristics. In this thesis, an optimization algorithm is devised and presented for partitioning and mapping computational tasks on CPU-GPU platforms while keeping a check on the power consumption. Our methodology also uses parallelism in applications and their tasks by utilizing the architectural capabilities of the GPU. The optimization algorithm was tested with a MJPEG decoder, several benchmarks and synthetic graphs.

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