Thermal-Aware Task Mapping on Dynamically Reconfigurable Network-on-Chip Based Multiprocessor System-on-Chip

Liu, Weichen; Yang, Lei; Jiang, Weiwen; Li, Feng; Guan, Nan; Zhang, Wei; Dutt, Nikil

doi:10.1109/tc.2018.2844365

Cited by 37 publications

(35 citation statements)

References 46 publications

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“…Failing to take advantage of the availability of dark cores might lead to suboptimal performance, as the cases of [16] [17]. To efficiently exploit dark cores, many dark-core-aware approaches have been considered [4]- [8]. The mapping approaches in [5] [6] assume that the system has a fixed number of dark cores, but in reality, the number of dark cores can vary significantly even in a short period of time [10].…”

Section: A Dynamic Mapping Without Task Migrationmentioning

confidence: 99%

“…Thermal-aware migration approaches (e.g., [22] [23]) move tasks from overheated cores to cooler ones to reduce hotspots. However, the above mapping approaches still do not exploit dark cores for better performance [8]. Although an early study in [9] presents a dark-core-aware migration algorithm to produce better computation performance, it does not address the changing computation demands of applications.…”

Section: B Dynamic Mapping With Task Migrationmentioning

confidence: 99%

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Dynamic Allocation/Reallocation of Dark Cores in Many-Core Systems for Improved System Performance

et al. 2020

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A significant number of processing cores in any many-core systems nowadays and likely in the future have to be switched off or forced to be idle to become dark cores, in light of ever increasing power density and chip temperature. Although these dark cores cannot make direct contributions to the chip's throughput, they can still be allocated to applications currently running in the system for the sole purpose of heat dissipation enabled by the temperature gradient between the active and dark cores. However, allocating dark cores to applications tends to add extra waiting time to applications yet to be launched, which in return can have adverse implications on the overall system performance. Another big issue related to dark core allocation stems from the fact that application characteristics are prone to undergo rapid changes at runtime, making a fixed dark core allocation scheme less desirable. In this paper, a runtime dark core allocation and dynamic adjustment scheme is thus proposed. Built upon a dynamic programming network (DPN) framework, the proposed scheme attempts to optimize the performance of currently running applications and simultaneously reduce waiting times of incoming applications by taking into account both thermal issues and geometric shapes of regions formed by the active/dark cores. The experimental results show that the proposed approach achieves an average of 61% higher throughput than the two state-of-the-art thermal-aware runtime task mapping approaches, making it the runtime resource management of choice in many-core systems. INDEX TERMS Dark core, many-core, dynamic resource allocation, throughput optimization.

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Section: A Dynamic Mapping Without Task Migrationmentioning

confidence: 99%

Section: B Dynamic Mapping With Task Migrationmentioning

confidence: 99%

Dynamic Allocation/Reallocation of Dark Cores in Many-Core Systems for Improved System Performance

et al. 2020

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“…Consequently, this can cause performance degradation. 15 Therefore, a balance between these two approaches is required for an optimised distribution. Additionally, exiting work do not consider the lifetime of nodes as one of the main factors; Hence, our proposed method.…”

Section: Introductionmentioning

confidence: 99%

ABENA: An Ageing before Temperature Electromigration-Aware Neighbour Allocation for Many-Core Architectures

Ofori-Attah

Agyeman

2021

2021 4th International Conference on Data Storage and Data Engineering

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The percentage of inactive nodes or dark nodes (we refer to dark nodes as dumso) in many-core systems increases because of power dissipation caused by continuous scaling in technology. To address this challenge, existing work employ several techniques. Some techniques place the dumso nodes strategically between active nodes to alleviate the temperature by choosing the nodes which are far away from each other. However, this increases the latency between nodes which require inter communication leading to performance degradation. Others employ Dynamic Thermal Management (DTM) to vary the Voltage Frequency (V/F) Scaling of the nodes whilst Task migration is used to migrate tasks. In this paper, an Ageing Before Temperature Eletromigration-Aware Neighbour Allocation (ABENA) is proposed to alleviate the temperature of the nodes by using the Lifetime of nodes as the main parameter. Experiments show that our approach improves the lifetime of nodes.

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“…As parallelism is the best way to utilize multi-cores, parallel workloads are now commonplace on such systems. In such a setting, the NoC is often a performance bottleneck of a multi-core system and responsible for performance slowdown of parallel workloads [1]. The NoC is also a major energy consumer of modern multi-core systems.…”

Section: Introductionmentioning

confidence: 99%

Network-on-Chip Aware Task Mappings

Sun

Dong

Chen

et al. 2020

Communications in Computer and Information Science

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Energy and power density have forced the industry to introduce many-cores where a large number of processor cores are integrated into a single chip. In such settings, the communication latency of the network on chip (NoC) could be performance bottleneck of a multi-core and many-core processor. Unfortunately, existing approaches for mapping the running tasks to the underlying hardware resources often ignore the impact of the NoC, leading to sub-optimal performance and energy efficiency. This paper presents a novel approach to allocating NoC resource among running tasks. Our approach is based on the topology partitioning of the shared routers of the NoC. We evaluate our approach by comparing it against two state-of-the-art methods using simulation. Experimental results show that our approach reduces the NoC communication latency by 5.19% and 2.99%, and the energy consumption by 17.94% and 12.68% over two competitive approaches.

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Thermal-Aware Task Mapping on Dynamically Reconfigurable Network-on-Chip Based Multiprocessor System-on-Chip

Abstract: Thermal-aware task mapping on dynamically reconfigurable network-on-chip based multiprocessor system-on-chip

Cited by 37 publications

References 46 publications

Dynamic Allocation/Reallocation of Dark Cores in Many-Core Systems for Improved System Performance

Dynamic Allocation/Reallocation of Dark Cores in Many-Core Systems for Improved System Performance

ABENA: An Ageing before Temperature Electromigration-Aware Neighbour Allocation for Many-Core Architectures

Network-on-Chip Aware Task Mappings

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