Name
Abstract | ||
|---|---|---|
In the last decades, the increasing amount of resources in embedded systems has been leading them to the point where an efficient management of these resources is mandatory, especially for the memory subsystem. Current MPSoCs have more than one application running concurrently. Hence, it is important to identify the memory needs of these applications and provide them accordingly. In this work we propose the use of a cluster-based, resource-aware approach to provide this efficient environment. The solution proposed here improves the overall performance of these systems by aggregating memory resources in clusters and redistributing these resources among applications based on a fairness criterion. For this memory clustering proposal, we use the information of external memory access-es as an estimate of the amount of memory required by each application. T Experimental results show that, depending on how the redistribution of memory resources among application occurs, the overall system can improve performance up to 18% and the energy savings can reach up to 20%. |
Year | Venue | Field |
|---|---|---|
2015 | IESS | Resource management,CPU cache,Computer science,Network on a chip,Redistribution (cultural anthropology),Cluster analysis,Auxiliary memory,Distributed computing |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gustavo Girão | 1 | 26 | 4.10 |
| Flávio Rech Wagner | 2 | 380 | 59.82 |