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Título:
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Write-aware replacement policies for PCM-based systems
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Autores:
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Rodríguez, Rodríguez ;
Castro Rodríguez, Fernando ;
Chaver, D. ;
González Alberquilla, R. ;
Piñuel Moreno, Luis ;
Tirado Fernández, Francisco
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Tipo de documento:
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texto impreso
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Editorial:
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Oxford Univ Press, 2015-09
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Dimensiones:
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application/pdf
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Nota general:
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info:eu-repo/semantics/openAccess
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Idiomas:
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Palabras clave:
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Estado = Publicado
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Materia = Ciencias: Informática: Programación de ordenadores
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Tipo = Artículo
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Resumen:
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The gap between processor and memory speeds is one of the greatest challenges that current designers face in order to develop more powerful computer systems. In addition, the scalability of the Dynamic Random Access Memory (DRAM) technology is very limited nowadays, leading one to consider new memory technologies as candidates for the replacement of conventional DRAM. Phase-Change Memory (PCM) is currently postulated as the prime contender due to its higher scalability and lower leakage. However, compared with DRAM, PCM also exhibits some drawbacks, like lower endurance or higher dynamic energy consumption and write latency, that need to be mitigated before it can be used as the main memory technology for the next generation of computers. This work addresses the PCM endurance constraint. For this purpose, we present an analysis of conventional cache replacement policies in terms of the amount of writebacks to main memory that they imply and we also propose some new replacement algorithms for the last-level cache (LLC) with the goal of cutting down the write traffic to memory and consequently, to increase PCM lifetime without degrading system performance. In this paper, we target general purpose processors provided with this kind of non-volatile main memory and we exhaustively evaluate our proposed policies in both single- and multi-core environments. Experimental results show that, on average, compared with a conventional Least Recently Used (LRU) algorithm, some of our proposals manage to reduce the amount of writes to main memory up to 20-30% depending on the scenario evaluated, which leads to memory endurance extensions of up to 20-45%, also reducing the energy consumption in the memory hierarchy by up to 9% and hardly degrading performance.
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En línea:
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https://eprints.ucm.es/34375/1/castrorodriguez10postpr.pdf
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