scholarly journals Methodologies for the WCET Analysis of Parallel Applications on Many-Core Architectures

2015 ◽  
Author(s):  
Vincent Nelis ◽  
Patrick Meumeu Yomsi ◽  
Luis Miguel Pinho
Keyword(s):  
Parallel Applications ◽  
Wcet Analysis ◽  
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 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

Enhancing the Performance of Multiple Parallel Applications using Heterogeneous Memory on the Intel"s Next-Generation Many-core Processor

2017 ◽  
Vol 44 (9) ◽  
pp. 878-886 ◽  
Author(s):  
Seungwoo Rho ◽  
Seoyoung Kim ◽  
Dukyun Nam ◽  
Geunchul Park ◽  
Jik-Soo Kim
Keyword(s):  
Parallel Applications ◽  
Next Generation ◽  
Many Core

scholarly journals The Maximum Common Subgraph Problem: A Parallel and Multi-Engine Approach

Computation ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 48 ◽  
Author(s):  
Stefano Quer ◽  
Andrea Marcelli ◽  
Giovanni Squillero
Keyword(s):  
Divide And Conquer ◽  
Parallel Applications ◽  
Practical Applications ◽  
Original Algorithm ◽  
Maximum Common Subgraph ◽  
Thread Pool ◽  
Cuda Programming ◽  
On Line ◽  
Gpu Architectures ◽  
Many Core

The maximum common subgraph of two graphs is the largest possible common subgraph, i.e., the common subgraph with as many vertices as possible. Even if this problem is very challenging, as it has been long proven NP-hard, its countless practical applications still motivates searching for exact solutions. This work discusses the possibility to extend an existing, very effective branch-and-bound procedure on parallel multi-core and many-core architectures. We analyze a parallel multi-core implementation that exploits a divide-and-conquer approach based on a thread pool, which does not deteriorate the original algorithmic efficiency and it minimizes data structure repetitions. We also extend the original algorithm to parallel many-core GPU architectures adopting the CUDA programming framework, and we show how to handle the heavily workload-unbalance and the massive data dependency. Then, we suggest new heuristics to reorder the adjacency matrix, to deal with “dead-ends”, and to randomize the search with automatic restarts. These heuristics can achieve significant speed-ups on specific instances, even if they may not be competitive with the original strategy on average. Finally, we propose a portfolio approach, which integrates all the different local search algorithms as component tools; such portfolio, rather than choosing the best tool for a given instance up-front, takes the decision on-line. The proposed approach drastically limits memory bandwidth constraints and avoids other typical portfolio fragility as CPU and GPU versions often show a complementary efficiency and run on separated platforms. Experimental results support the claims and motivate further research to better exploit GPUs in embedded task-intensive and multi-engine parallel applications.

Methodology of exploring ESL/RTL many-core platforms for developing embedded parallel applications

2014 ◽  
Author(s):  
Jyu-Yuan Lai ◽  
Chih-Tsun Huang ◽  
Ting-Shuo Hsu ◽  
Jing-Jia Liou ◽  
Tung-Hua Yeh ◽  
...  
Keyword(s):  
Parallel Applications ◽  
Many Core
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