Name
Abstract | ||
|---|---|---|
Management of shared resources in emerging multicores for achieving predictable performance has received considerable attention in recent times. In general, almost all these approaches attempt to guarantee a certain level of performance QoS (weighted IPC, harmonic speedup, etc) by managing a single shared resource or at most a couple of interacting resources. A fundamental shortcoming of these approaches is the lack of coordination between these shared resources to satisfy a system level QoS. This is undesirable because providing end-to-end QoS in future multicores is essential for supporting wide-spread adoption of these architectures in virtualized servers and cloud computing systems. An initial step towards such an end-to-end QoS support in multicores is to ensure that at least the major computational and memory resources on-chip are managed efficiently in a coordinated fashion. In this paper, we propose METE, a platform for end-to-end on-chip resource management in multicore processors. Assuming that each application specifies a performance target/SLA, the main objective of METE is to dynamically provision sufficient on-chip resources to applications for achieving the specified targets. METE employs a feedback based system, designed as a Single-Input, Multiple-Output (SIMO) controller with an Auto-Regressive-Moving-Average (ARMA) model, to capture the behaviors of different applications. We evaluate a specific implementation of METE that manages cores, shared caches and off-chip bandwidth in an integrated manner on 8 and 16 core systems using a detailed full system simulator and workloads derived from the SPECOMP and SPECJBB multithreaded benchmarks. The collected results indicate that our proposed scheme is able to provision shared resources among co-runner applications dynamically over the course of execution, to provide end-to-end QoS and satisfy specified performance targets. Furthermore, the elegance of the control theory based multi-layer resource provisioning is in assuring QoS guarantees. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/1993744.1993747 | SIGMETRICS |
Keywords | Field | DocType |
qos guarantee,system-wide resource management,performance qos,meeting end-to-end qos,end-to-end qos,shared cache,system level qos,single shared resource,performance target,end-to-end on-chip resource management,end-to-end qos support,shared resource,control theory,chip,resource manager,multicore processors,arma model,satisfiability,system design,resource management,cloud computing | Resource management,Computer science,Server,Quality of service,Computer network,Real-time computing,Provisioning,Bandwidth (signal processing),Shared resource,Multi-core processor,Speedup,Distributed computing | Conference |
Volume | Issue | Citations |
39 | 1 | 38 |
PageRank | References | Authors |
1.02 | 28 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Akbar Sharifi | 1 | 123 | 5.99 |
| Shekhar Srikantaiah | 2 | 215 | 10.47 |
| Asit K. Mishra | 3 | 1216 | 46.21 |
| Mahmut T. Kandemir | 4 | 7371 | 568.54 |
| Chita R. Das | 5 | 1038 | 59.34 |