Workload-aware placement strategies to leverage disaggregated resources in the datacenter
| Autor: | David Carrera, Aaron Call, Jordà Polo |
|---|---|
| Přispěvatelé: | Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Process management
Computer Networks and Communications Computer science Scheduling (computing) Model-aware Leverage (negotiation) Composability Workload placement Orchestration (computing) Electrical and Electronic Engineering Informàtica::Arquitectura de computadors [Àrees temàtiques de la UPC] Resource disaggregation Hardware_MEMORYSTRUCTURES Scheduling NVM Express Quality of service (Computer networks) Orchestration Workload Gestió de memòria (Informàtica) Computer Science Applications Work (electrical) Memory management (Computer science) Control and Systems Engineering IO pooling Christian ministry Software-defined infrastructures Centres informàtics Data processing service centers Information Systems NVMe |
| Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| Popis: | Disaggregation of resources is a datacenter strategy that aims to decouple the physical location of resources from the place where they are accessed, as opposed to physically attached devices connected to the Peripheral Component Interconnect Express (PCIe) bus. By attaching and detaching resources through a fast interconnection network, it is possible to increase the flexibility to manage datacenter infrastructures while keeping the performance of the pooled and disaggregated devices. This article introduces workload scheduling and placement policies for environments with disaggregated memories. These policies are driven by accurate prebuilt performance degradation models. We focus on the use of nonvolatile memory to store data and/or to provide memory extensions. Following a software-defined approach, persistent memories are combined to provide higher capacity and/or bandwidth devices, or used by multiple workloads to increase the number of running workloads. Different combinations of workloads and associated soft deadlines are used to evaluate the placement policies using a system simulator. When using the first-fit policy, results show that a disaggregated system can reduce missed deadlines up to 49% when compared to a physically attached system. When our proposed policy with workload awareness is enabled in a disaggregated system, missed deadlines can be reduced up to 100% (no deadlines missed). This work was supported in part by the Ministry of Economy of Spain under Contract TIN2015-65316-P, in part by the Ministry of Science under Contract PID2019-107255GBC21/AEI/10.13039/501100011033, and in part by the Generalitat de Catalunya under Contract 2014SGR1051. |
| Databáze: | OpenAIRE |
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