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English
Optimization methods for the memory allocation problems in embedded systems
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Memory allocation in embedded systems is one of the main challenges that electronic designers have to face. This part, rather difficult
to handle is often left to the compiler with which automatic rules are applied. Nevertheless, a carefully tailored allocation of data to memory banks may lead to great savings in terms of running time and energy consumption. This thesis addresses various versions of the memory allocation problem. At each version the problem’s difficulty increases, i.e., the number of constraints increases. The number of memory banks, bank capacities, sizes and number of accesses of data structures, and the conflicting data structures at each time interval are the main constrains handled in the memory allocation
problems. In this work we present an ILP formulation and some metaheuristics implemented for each problem version. We also assess our metaheuristics with the exact methods and other literature metaheuristics with the aim of highlighting what makes the success of metaheuristics for these problems.
- What
- Meeting
- When
-
23.11.2011
from
14:00
to
15:35
- Where
- ENSSAT- 036C
- Name
- Sébastien Pillement
- Contact Email
- pillemen@irisa.fr
Gecos: a source-to-source compiler for high-level synthesis