Understanding Power Consumption Metric on Heterogeneous Memory Systems
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866929457474830336 |
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| author | Proaño, Andrès Rubio Sato, Kento |
| author_facet | Proaño, Andrès Rubio Sato, Kento |
| contents | Contemporary memory systems contain a variety of memory types, each possessing distinct characteristics. This trend empowers applications to opt for memory types aligning with developer's desired behavior. As a result, developers gain flexibility to tailor their applications to specific needs, factoring in attributes like latency, bandwidth, and power consumption. Our research centers on the aspect of power consumption within memory systems. We introduce an approach that equips developers with comprehensive insights into the power consumption of individual memory types. Additionally, we propose an ordered hierarchy of memory types. Through this methodology, developers can make informed decisions for efficient memory usage aligned with their unique requirements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_06579 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Understanding Power Consumption Metric on Heterogeneous Memory Systems Proaño, Andrès Rubio Sato, Kento Performance Distributed, Parallel, and Cluster Computing Contemporary memory systems contain a variety of memory types, each possessing distinct characteristics. This trend empowers applications to opt for memory types aligning with developer's desired behavior. As a result, developers gain flexibility to tailor their applications to specific needs, factoring in attributes like latency, bandwidth, and power consumption. Our research centers on the aspect of power consumption within memory systems. We introduce an approach that equips developers with comprehensive insights into the power consumption of individual memory types. Additionally, we propose an ordered hierarchy of memory types. Through this methodology, developers can make informed decisions for efficient memory usage aligned with their unique requirements. |
| title | Understanding Power Consumption Metric on Heterogeneous Memory Systems |
| topic | Performance Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2408.06579 |