scholarly journals Static Mapping of Multiple Data-Parallel Applications on Embedded Many-Core SoCs

2013 ◽  
Vol E96.D (10) ◽  
pp. 2268-2271
Author(s):  
Junya KAIDA ◽  
Yuko HARA-AZUMI ◽  
Takuji HIEDA ◽  
Ittetsu TANIGUCHI ◽  
Hiroyuki TOMIYAMA ◽  
...  
Keyword(s):  
Parallel Applications ◽  
Data Parallel ◽  
Multiple Data ◽  
Many Core

scholarly journals Static Mapping with Dynamic Switching of Multiple Data-Parallel Applications on Embedded Many-Core SoCs

2014 ◽  
Vol E97.D (11) ◽  
pp. 2827-2834 ◽  
Author(s):  
Ittetsu TANIGUCHI ◽  
Junya KAIDA ◽  
Takuji HIEDA ◽  
Yuko HARA-AZUMI ◽  
Hiroyuki TOMIYAMA
Keyword(s):  
Parallel Applications ◽  
Data Parallel ◽  
Dynamic Switching ◽  
Multiple Data ◽  
Many Core

scholarly journals Many-Core Scheduling of Data Parallel Applications Using SMT Solvers

2014 ◽  
Author(s):  
Pranav Tendulkar ◽  
Peter Poplavko ◽  
Ioannis Galanommatis ◽  
Oded Maler
Keyword(s):  
Parallel Applications ◽  
Data Parallel ◽  
Smt Solvers ◽  
Many Core

scholarly journals Resource-Aware Device Allocation of Data-Parallel Applications on Heterogeneous Systems

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1825
Author(s):  
Donghyeon Kim ◽  
Seokwon Kang ◽  
Junsu Lim ◽  
Sunwook Jung ◽  
Woosung Kim ◽  
...  
Keyword(s):  
Heterogeneous Systems ◽  
Parallel Applications ◽  
Small Data ◽  
Data Set ◽  
Computing Device ◽  
Parallel Application ◽  
Multiple Gpus ◽  
Data Parallel ◽  
Multiple Data ◽  
Resource Aware

As recent heterogeneous systems comprise multi-core CPUs and multiple GPUs, efficient allocation of multiple data-parallel applications has become a primary goal to achieve both maximum total performance and efficiency. However, the efficient orchestration of multiple applications is highly challenging because a detailed runtime status such as expected remaining time and available memory size of each computing device is hidden. To solve these problems, we propose a dynamic data-parallel application allocation framework called ADAMS. Evaluations show that our framework improves the average total execution device time by 1.85× over the round-robin policy in the non-shared-memory system with small data set.

Data Parallel Application Adaptivity and System-Wide Resource Management in Many-Core Architectures

2014 ◽  
pp. 345-352
Author(s):  
Giuseppe Massari ◽  
Edoardo Paone ◽  
Michele Scandale ◽  
Patrick Bellasi ◽  
Gianluca Palermo ◽  
...  
Keyword(s):  
Resource Management ◽  
Parallel Application ◽  
Data Parallel ◽  
Many Core

VLADYMIR—a C++ matrix library for data-parallel applications

2004 ◽  
Vol 20 (6) ◽  
pp. 1023-1039 ◽  
Author(s):  
Jonas Lätt ◽  
Bastien Chopard
Keyword(s):  
Parallel Applications ◽  
Data Parallel
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