Energy-aware fully-adaptive resource provisioning in collaborative CPU-FPGA cloud environments

Jordan, Michael Guilherme; Korol, Guilherme; Knorst, Tiago; Rutzig, Mateus Beck; Beck, Antonio Carlos Schneider

doi:10.1016/j.jpdc.2023.02.009

Cited by 6 publications

(4 citation statements)

References 32 publications

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“…The total power consumption consists of two main elements, namely dynamic and static (leakage) power. The total power consumed by the CMOS-based circuit [27] is determined as…”

Section: Power Estimationmentioning

confidence: 99%

Efficient Power Estimation Using DSENT for 3D-Mesh on Chip Optic Communication Network

Ahmed,

Ambudka,

Yadav

2024

ISI

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The Network-on-Chip (NoC) stands as a potent solution for achieving heightened performance, efficient communication, and dependability in the migration of Very-Large Scale Integration (VLSI) architecture toward deep submicron technology, when contrasted with conventional connectivity networks. Considerable research endeavours have been allocated to diverse facets of NoCs, encompassing topology, routing algorithms, traffic behaviours, power management, and fundamental mapping. This paper explores the power consumption efficiency of Parameterized Path-Based, Randomized, Oblivious, Minimal for 3D Mesh (PROM3D) routing and ZXY routing algorithms for various traffic patterns like transpose, bit shuffle, and random traffic with the help of the integrated DSENT network model. The PROM3D routing algorithm selects a path randomly from all possible minimal pathways between the source and destination, whereas ZXY is a layer-based routing method. The Design Space Exploration of Network (DSENT) tool is used with the NoC Interconnect Routing and Applications Modeling (NIRGAM) simulator in experiments to measure the power consumption. The findings indicate that, within the 3D-Mesh environment, the ZXY routing algorithm exhibits a 0.02% of variation in power consumption while in saturation on varying loads for various traffic patterns in comparison to the PROM3D algorithm.

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“…The total power consumption consists of two main elements, namely dynamic and static (leakage) power. The total power consumed by the CMOS-based circuit [27] is determined as…”

Section: Power Estimationmentioning

confidence: 99%

Efficient Power Estimation Using DSENT for 3D-Mesh on Chip Optic Communication Network

Ahmed,

Ambudka,

Yadav

2024

ISI

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“…In recent years, applications have employed FPGA to create the best strategy to optimize resource allocation, allowing clients to share the same infrastructure in order to maximize scalability and resource utilization. [8] (3) Optimal path planning. Optimal route planning refers to the optimal route obtained by the system based on the stored route information, considering the distance, road conditions, and other human beings that cannot be predicted and are constrained by a large amount of data.…”

Section: Intelligent System Fieldmentioning

confidence: 99%

FPGA: The super chip in the age of artificial intelligence

2023

J. Phys.: Conf. Ser.

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In modern society, artificial intelligence (AI) is developing more rapidly. And the Field Programmable Gate Array (FPGA) has always been the focus of research as a driving platform. This paper studies in detail the theoretical basis, applications, defects, and future development directions of FPGAs. It is concluded that FPGA has three characteristics: gate array, programmable, and scene, and the detailed positioning of FPGA, the structure, principle, tools, process, and description language of FPGA design. And the unique advantages of FPGA in the field of artificial intelligence: flexible and configurable, special optimizations for convolutional neural networks, and deterministic low latency. Several typical applications of FPGA in the field of artificial intelligence, deficiencies and solutions, and two future development directions. This article will make a great contribution to the development of FPGA in the field of artificial intelligence in the future.

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“…To address these challenges, resource provisioning algorithms need to strike a balance between meeting real-time execution requirements and optimizing energy consumption. This requires sophisticated optimization techniques, such as dynamic voltage and frequency scaling (DVFS) [15], task consolidation [16], and load balancing [17], to achieve efficient resource allocation. Furthermore, considering energy-aware scheduling policies and incorporating energy models for IoT devices can help guide resource provisioning decisions that minimize energy consumption while meeting realistic workload demands.…”

Section: Issn: 2502-4752 mentioning

confidence: 99%

“…The task 𝐾 𝑞 𝑟 which needs to be executed might have various data-dependency. Hence, the datadependency for each task can be expressed as (15);…”

Section: Optimization Model For Task Scheduling In Heterogenous Iot E...mentioning

confidence: 99%

Resource provisioning model for executing realistic workload in heterogenous internet of things environment

Chowdaiah,

Dammur

2023

IJEECS

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Resource provisioning considering scientific or realistic workload in a heterogeneous internet of things (IoT) environment presents significant challenges in terms of execution time and energy consumption. These challenges arise due to the dynamic nature of scientific or realistic-time workloads and the diverse characteristics of IoT devices. In this study, we propose a resource provisioning model that takes into account the dynamic and real-time nature of IoT workloads in a heterogeneous environment. <br /> The model aims to allocate computational resources effectively, considering the real-time demands of IoT applications while optimizing execution time and energy consumption. Three scientific workloads have been used to evaluate the proposed model. The results have been compared with the existing models. The results show that the proposed model attains better performance in terms of reducing time and energy consumption for the execution of workload tasks.

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Energy-aware fully-adaptive resource provisioning in collaborative CPU-FPGA cloud environments

Cited by 6 publications

References 32 publications

Efficient Power Estimation Using DSENT for 3D-Mesh on Chip Optic Communication Network

Efficient Power Estimation Using DSENT for 3D-Mesh on Chip Optic Communication Network

FPGA: The super chip in the age of artificial intelligence

Resource provisioning model for executing realistic workload in heterogenous internet of things environment

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