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Optimizing Dynamic Resource Allocation
2014
Procedia Computer Science
We present a formulation, solution method, and program acceleration techniques for two dynamic control scenarios, both with the common goal of optimizing resource allocations. ...
A novel aspect is included in the second scenario: dynamically allocating the computational resources in an online fashion which is made possible through constant aspect ratio tiling (CART). ...
Through the non-myopic management of the computational resources, Section 4, energy and time expended for the tracking execution can be reduced in an optimal manner. ...
doi:10.1016/j.procs.2014.05.115
fatcat:xe42jy2q4jg5raeokutw75jhuq
Resource Taxonomy for a Fog System
2021
Zenodo
We consider this work as the first step towards the construction of an ontology that supports the strong variety of the involved nodes of the cloud, the fog and the IoT, which would contribute to the homogenization ...
Fog computing has emerged as a novel technology for solving the latency, network traffic management, and power consumption issues faced by Internet of Things ecosystems. ...
We consider this work as the first step towards the construction of an ontology in this context. The rest of this paper is organized as follows. ...
doi:10.5281/zenodo.4770822
fatcat:gysp5msipja5xjmu45lnwsijh4
Runtime Resource Management in Heterogeneous System Architectures: The SAVE Approach
2014
2014 IEEE International Symposium on Parallel and Distributed Processing with Applications
This paper presents a first implementation of a resource allocation policy that dynamically shares heterogeneous resources between multiple running applications. ...
This scenario has propelled an interest towards self-adaptive systems that dynamically reorganize the use of system resources to optimize for a given goal. ...
However, they still lack a comprehensive, autonomic OSes and runtimes, such as the K42 research OS [4] , which makes monitoring and adaptation first-class citizens. ...
doi:10.1109/ispa.2014.27
dblp:conf/ispa/DurelliPMPRSVB14
fatcat:ccsfd3f2tnhijged767ljiww2i
Implementing Agent-Based Resource Management in Tsunami Modeling – Preliminary Considerations
[chapter]
2014
Lecture Notes in Computer Science
Recently, work has started to apply the agent-semantic infrastructure, developed within the scope of the Agents in Grid project, to the resource management needed in tsunami modeling. ...
The original proposal was based on the perceived simplicity, versatility and exibility of the agent-based approach that makes it easier to deploy than the standard grid middlewares. ...
First, we have resigned from the notion of resource team, and placed a WorkerAgent (playing the role of the LMaster) on each computing node. ...
doi:10.1007/978-3-319-05693-7_6
fatcat:mymlqeaxlzhbzawprr4q62lwnu
HeteroCore GPU to Exploit TLP-Resource Diversity
2018
IEEE Transactions on Parallel and Distributed Systems
Sharing GPU resources in such environments requires effective multitasking support. ...
Graphics processing units (GPUs) are widely adopted as compute accelerators in cloud computing environments and supercomputers. ...
first initiate a spatial profiling phase in which we partition the HeteroCore GPU into two groups with 4 big-SMs and 4 small-SMs each. ...
doi:10.1109/tpds.2018.2854764
fatcat:vwpoqnb3uzgzpaaqziokk2nk74
Software Resource Disaggregation for HPC with Serverless Computing
[article]
2024
arXiv
pre-print
Consequently, HPC systems fail to efficiently use the large pools of unused memory and increase the utilization of idle computing resources. ...
We show how serverless functions provide fine-grained access to the resources of batch-managed cluster nodes. ...
This work was partially supported by the ETH Future Computing Laboratory (EFCL), financed by a donation from Huawei Technologies. ...
arXiv:2401.10852v4
fatcat:odagfgmekrbn7iy3jct7ogai2u
Application-Driven Requirements for Node Resource Management in Next-Generation Systems
2020
2020 IEEE/ACM International Workshop on Runtime and Operating Systems for Supercomputers (ROSS)
We then extract several themes from these applications that highlight next-generation requirements for node resource managers. ...
Finally, using these requirements, we propose a general, cross-stack coordination framework and outline its components and functionality. ...
Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, and the Exascale Computing Research laboratory with support of CEA, Intel, and UVSQ. LLNL-CONF-809181. ...
doi:10.1109/ross51935.2020.00006
fatcat:mp3krqiv55bgrhdtr5skurgg3u
A Holistic Resource Management for Graphics Processing Units in Cloud Computing
2018
Electronical Notes in Theoretical Computer Science
Moreover, we develop a Heterogeneous GPUs analyser as the first step in the implementation of the proposed architecture. ...
In this paper, we propose a systematic architecture to manage heterogeneous GPUs in a Cloud environment considering the performance and the energy consumption as key factors. ...
consumption and increasing GPU resources sharing. ...
doi:10.1016/j.entcs.2018.09.002
fatcat:kc5mrpllijfsxck2ejzwmgmwbi
Quality of Service Driven Runtime Resource Allocation in Reconfigurable HPC Architectures
2016
2016 IEEE Intl Conference on Computational Science and Engineering (CSE) and IEEE Intl Conference on Embedded and Ubiquitous Computing (EUC) and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES)
We implement the proposed resource manager in a commercial HPC system, evaluating its behavior with representative workloads. ...
We propose a novel resource manager able to dynamically vary the number of FPGAs allocated to each of the jobs running in a multi-accelerator system, with the goal of meeting a given Quality of Service ...
Resource management techniques are good enablers for resource sharing, even on devices conceived as singleapplication and single-user appliances: resource sharing can extend the suitability of HSAs to ...
doi:10.1109/cse-euc-dcabes.2016.156
dblp:conf/cse/PoglianiDMB16
fatcat:zox4kxyxhfa5dlaizatez3lzhq
Service Oriented Interactive Media (SOIM) Engines Enabled by Optimized Resource Sharing
2016
2016 IEEE Symposium on Service-Oriented System Engineering (SOSE)
In the same way as cloud computing, Software as a Service (SaaS) and Content Centric Networking (CCN) triggered a new class of software architectures fundamentally different from traditional desktop software ...
slot management. ...
The first approach applies a 1:1 mapping between GPU and OS. ...
doi:10.1109/sose.2016.47
dblp:conf/sose/AlyFKSS16
fatcat:runemwibdfh27guvwwqtucpf2y
Fluxion: A Scalable Graph-Based Resource Model for HPC Scheduling Challenges
2023
Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis
The current era of exascale supercomputing and the emergence of a computing continuum present several significant resource management challenges. ...
These include, but are not limited to, management of complex and high-throughput scientific workflows, diverse resources such as power and network bandwidth, extremely heterogenous and dynamic systems, ...
Authors also wish to thank James Corbett, Al Chu, Don Lipari, Christopher Moussa, Chris Morrone, and Becky Springmeyer from the Flux team at Lawrence Livermore National Laboratory. ...
doi:10.1145/3624062.3624286
fatcat:5smy3cjklrgcpgr3cmnewwfw54
MARVEL - D5.3: HPC infrastructure and resource management for audio-visual data analytics – initial version
2022
Zenodo
Computing resources for running applications come from domains like HPC and Cloud where virtual machines with framework services are set-up according to pilot demands. ...
The purpose of this deliverable is to present respective activities to analyse and establish properly the architecture for initial MARVEL services deployment. ...
HPC infrastructure' and 'Task 5.2. Resource management and optimised automatic usage of external computational and storage resources'. ...
doi:10.5281/zenodo.6821303
fatcat:i6jp42fubfelvl7ms5m76cmk5m
MARVEL - D5.3: HPC infrastructure and resource management for audio-visual data analytics – initial version
2022
Zenodo
Computing resources for running applications come from domains like HPC and Cloud where virtual machines with framework services are set-up according to pilot demands. ...
The purpose of this deliverable is to present respective activities to analyse and establish properly the architecture for initial MARVEL services deployment. ...
HPC infrastructure' and 'Task 5.2. Resource management and optimised automatic usage of external computational and storage resources'. ...
doi:10.5281/zenodo.7543694
fatcat:xdclluaj3rhefhv6guyxz3uol4
Hetero-DB: Next Generation High-Performance Database Systems by Best Utilizing Heterogeneous Computing and Storage Resources
2015
Journal of Computer Science and Technology
Hetero-DB develops a GPU-aware query execution engine with GPU device memory management and query scheduling mechanism to support concurrent query execution. ...
To best utilize the hybrid hardware devices, the semantic information that is critical for storage I/O is identified and passed to the storage manager, which has a great potential to improve the efficiency ...
PTask [37] adds abstractions of GPUs in the OS kernel to support managing GPUs as first-class computing resources. ...
doi:10.1007/s11390-015-1553-y
fatcat:tv5xc6p4avhebfkhmzj5emcl2y
Techniques for Shared Resource Management in Systems with Throughput Processors
[article]
2018
arXiv
pre-print
Our evaluations show that the GPU-aware cache and memory management techniques proposed in this dissertation are effective at mitigating the interference caused by GPUs on current and future GPU-based ...
The continued growth of the computational capability of throughput processors has made throughput processors the platform of choice for a wide variety of high performance computing applications. ...
Acknowledgements First and foremost, I would like to thank my parents, Khrieng and Ruchanee Ausavarungnirun for their endless encouragement, love, and support. ...
arXiv:1803.06958v1
fatcat:3mqbwegpkvdrpk6sqwb3ooyh7e
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