ADARE: Adaptive Resource Provisioning in Multi-FPGA Edge Environments

This paper introduces ADARE, a novel resource provisioning framework optimized for multi-FPGA environments. Unlike traditional edge scenarios, which may not fully account for the multitenancy of heterogeneous and dynamic demands, ADARE integrates a fully adaptive resource management and load-balancing system. This framework selects the most suitable FPGA configurations for varying task demands and adjusts resource allocation dynamically to optimize energy consumption and makespan. Configurable to a range of operational parameters, ADARE excels across various computational scenarios by effectively managing the balance between workload types and FPGA capabilities. Demonstrations in a heterogeneous workload environment show ADARE outperforming traditional homogeneous approaches. On average, ADARE achieves a 2.0x improvement in makespan and a 2.4x reduction in energy consumption. These results highlight its adaptability and efficiency in managing complex multi-tenant edge environments.

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Publication Details

Published
2024-09-02
DOI
https://doi.org/10.1109/sbcci62366.2024.10704009
Citations
3
Primary Topic
Embedded Systems Design Techniques
Type
article
Field-Weighted Citation Impact
1.47

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article

ADARE: Adaptive Resource Provisioning in Multi-FPGA Edge Environments

Michael Guilherme Jordan, Fernanda Lima Kastensmidt, José Rodrigo Azambuja, Antonio Carlos Schneider Beck et al.
3 citations
Embedded Systems Design Techniques
1.47
article

ADARE: Adaptive Resource Provisioning in Multi-FPGA Edge Environments

Michael Guilherme Jordan, Fernanda Lima Kastensmidt, José Rodrigo Azambuja, Antonio Carlos Schneider Beck, Ian Kersz, Henry Piceni
article en
3 citations

Abstract

This paper introduces ADARE, a novel resource provisioning framework optimized for multi-FPGA environments. Unlike traditional edge scenarios, which may not fully account for the multitenancy of heterogeneous and dynamic demands, ADARE integrates a fully adaptive resource management and load-balancing system. This framework selects the most suitable FPGA configurations for varying task demands and adjusts resource allocation dynamically to optimize energy consumption and makespan. Configurable to a range of operational parameters, ADARE excels across various computational scenarios by effectively managing the balance between workload types and FPGA capabilities. Demonstrations in a heterogeneous workload environment show ADARE outperforming traditional homogeneous approaches. On average, ADARE achieves a 2.0x improvement in makespan and a 2.4x reduction in energy consumption. These results highlight its adaptability and efficiency in managing complex multi-tenant edge environments.

Universidade Federal do Rio Grande do Sul (BR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Decent work and economic growth
Openalex Percentile: Top 17%
Embedded Systems Design Techniques
1.47
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