Paper Info
Title
Hotspot-aware task-resource co-allocation for heterogeneous many-core networks-on-chip.
Abstract
To fully exploit the massive parallelism of many-core on a chip, this work tackles the problem of mapping large-scale applications onto heterogeneous networks-on-chip (NoCs) while minimizing hotspots. A task-resource co-optimization framework is proposed which configures the on-chip communication infrastructure and maps the applications simultaneously and coherently, aiming to minimize the peak energy under the constraints of computation power, communication capacity, and total cost budget of on-chip resources. The problem is first formulated into a linear programming model to search for optimal solution. A heuristic is further developed for fast design space exploration at design-time and run-time in large-scale NoCs. Extensive simulations are carried out under real-world benchmarks and randomly generated task graphs to demonstrate the effectiveness and efficiency of the proposed schemes. Real system simulations show the significant improvement (30–200%) in NoCs latency and throughput compared to the state-of-the-art minimum-path approach because of the diminishing hotspots and balanced load distribution.
Year
DOI
Venue
2018
10.1016/j.compeleceng.2018.04.019
Computers & Electrical Engineering
Keywords
Field
DocType
Task-resource co-allocation,Network-on-Chip (NoC),Many-Core NoC,Heterogeneous,Computation and communication,Peak load,Energy hotspots,Cost budget,Linear programming (LP),Heuristic
Heuristic,Computer science,Massively parallel,Chip,Real-time computing,Exploit,Linear programming,Throughput,Design space exploration,Hotspot (Wi-Fi),Distributed computing
Journal
Volume
ISSN
Citations 
68
0045-7906
1
PageRank 
References 
Authors
0.37
18
4
Name
Order
Citations
PageRank
Md Farhadur Reza181.89
Dan Zhao218815.29
Hongyi Wu384876.90
Magdy Bayoumi419036.91