Evolutionary Design of the Memory Subsystem
| Autor: | J. Manuel Colmenar, Josefa Díaz Álvarez, José L. Risco-Martín |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: |
FOS: Computer and information sciences
Flat memory model Cache coloring CPU cache Computer science Computer Science - Artificial Intelligence Real-time computing 0211 other engineering and technologies Register file 02 engineering and technology Overlay law.invention law Hardware Architecture (cs.AR) 0202 electrical engineering electronic engineering information engineering Computing with Memory Neural and Evolutionary Computing (cs.NE) Computer Science - Hardware Architecture 021106 design practice & management Dynamic random-access memory Memory hierarchy business.industry Uniform memory access Computer Science - Neural and Evolutionary Computing 020202 computer hardware & architecture Physical address Memory management Artificial Intelligence (cs.AI) Shared memory Embedded system Distributed memory Cache business Software |
| Popis: | The memory hierarchy has a high impact on the performance and power consumption in the system. Moreover, current embedded systems, included in mobile devices, are specifically designed to run multimedia applications, which are memory intensive. This increases the pressure on the memory subsystem and affects the performance and energy consumption. In this regard, the thermal problems, performance degradation and high energy consumption, can cause irreversible damage to the devices. We address the optimization of the whole memory subsystem with three approaches integrated as a single methodology. Firstly, the thermal impact of register file is analyzed and optimized. Secondly, the cache memory is addressed by optimizing cache configuration according to running applications and improving both performance and power consumption. Finally, we simplify the design and evaluation process of general-purpose and customized dynamic memory manager, in the main memory. To this aim, we apply different evolutionary algorithms in combination with memory simulators and profiling tools. This way, we are able to evaluate the quality of each candidate solution and take advantage of the exploration of solutions given by the optimization algorithm. We also provide an experimental experience where our proposal is assessed using well-known benchmark applications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|