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On improving application utility prediction
2010
Proceedings of the 28th of the international conference extended abstracts on Human factors in computing systems - CHI EA '10
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In this paper, we present an objective utility function that accurately predicts the user's subjective impressions of application importance. ...
Identifying these high-utility applications is critical to the fields of Task Analysis, User Interruptions, Workflow Analysis, and Goal Prediction. ...
The most accurate model created improved upon existing techniques by 53% resulting in a Decision Tree with a 66% accuracy for predicting actual high-utility applications as high-utility, and a "good" kappa ...
doi:10.1145/1753846.1753995
dblp:conf/chi/HailpernJSK10
fatcat:lhnyaqc6gzh6lf2mqioox5k6du
IoNCloud: Exploring application affinity to improve utilization and predictability in datacenters
2015
2015 IEEE International Conference on Communications (ICC)
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The intra-cloud network is typically oversubscribed and shared in a best-effort manner, relying on TCP to achieve high network utilization and scalability. ...
In doing so, we explore the trade-off between high resource utilization (which is desired by providers to achieve economies of scale) and strict network guarantees (necessary for tenants to run jobs predictably ...
It improves network predictability by grouping tenant applications into virtual networks according to their temporal bandwidth demands. ...
doi:10.1109/icc.2015.7249198
dblp:conf/icc/MarconNOBBGB15
fatcat:bjftgowyqvg4fm2eurfhspohyq
Effect of the Digital Transformation of Power System on Renewable Energy Utilization in China
2021
IEEE Access
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In the early stage of digital development, the improvement of SE of business application of power digitalization has a significant impact on the utilization rate of renewable energy. ...
Based on the operation requirements of renewable energy power stations and the functions of business application of power digitalization, the short-term prediction of renewable energy output application ...
doi:10.1109/access.2021.3094317
fatcat:kep4v5zcwrhmtod6ykyd4xip3i
Power-aware predictive models of hybrid (MPI/OpenMP) scientific applications on multicore systems
2011
Computer Science - Research and Development
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Predictive models enable a better understanding of the performance characteristics of applications on multicore systems. ...
Our models show that cache utilization (L1/L2), branch instructions, TLB data misses, and system resource stalls affect the performance of each application and performance component differently. ...
Improving the L1 cache utilization of the application on SystemG has the potential to reduce the runtime of the application. ...
doi:10.1007/s00450-011-0190-0
fatcat:o22il4jehva5ti4sr6wnoubmzy
SMiTe: Precise QoS Prediction on Real-System SMT Processors to Improve Utilization in Warehouse Scale Computers
2014
2014 47th Annual IEEE/ACM International Symposium on Microarchitecture
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One of the key challenges for improving efficiency in warehouse scale computers (WSCs) is to improve server utilization while guaranteeing the quality of service (QoS) of latency-sensitive applications ...
Our evaluation shows that SMiTe allows us to improve the utilization of WSCs by up to 42.57% while enforcing an application's QoS requirements. ...
Scale-out Study: Improving Utilization while Guaranteeing QoS With SMiTe's precise prediction, we can enable 'safe' co-locations in order to improve utilization without violating the QoS requirement. ...
doi:10.1109/micro.2014.53
dblp:conf/micro/ZhangLMT14
fatcat:fyx7gxw7jfcxjktrm7q3rjn7me
Bubble-flux
2013
Proceedings of the 40th Annual International Symposium on Computer Architecture - ISCA '13
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Ensuring the quality of service (QoS) for latency-sensitive applications while allowing co-locations of multiple applications on servers is critical for improving server utilization and reducing cost in ...
Batch applications remain in a state of flux throughout execution. Our results show that the utilization improvement achieved by Bubble-Flux is up to 2.2x better than the prior static approach. ...
The cluster manager consolidates multiple disparate applications on a single server to improve the machine utilization. ...
doi:10.1145/2485922.2485974
dblp:conf/isca/YangBMT13
fatcat:x3p7zjawyzfjjl4pm4jyhv2ktu
Bubble-flux
2013
SIGARCH Computer Architecture News
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Ensuring the quality of service (QoS) for latency-sensitive applications while allowing co-locations of multiple applications on servers is critical for improving server utilization and reducing cost in ...
Batch applications remain in a state of flux throughout execution. Our results show that the utilization improvement achieved by Bubble-Flux is up to 2.2x better than the prior static approach. ...
The cluster manager consolidates multiple disparate applications on a single server to improve the machine utilization. ...
doi:10.1145/2508148.2485974
fatcat:3lywpawkevf3hpglugufiozizm
The CLOTHO project
2010
Proceedings of the 8th ACM Conference on Designing Interactive Systems - DIS '10
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In this paper, we present an objective utility function that accurately predicts the user's subjective impressions of application importance, improving existing techniques by 53%. ...
We term this subset of applications that the user values as high-utility applications. ...
We utilized a large real-world data set (22 users and 321 real-world hours of data) and constructed a set of models for predicting application utility with direct applications to HCI in Task Analysis, ...
doi:10.1145/1858171.1858230
dblp:conf/ACMdis/HailpernJSK10
fatcat:gi5iecvuxzallaj3nlvpyjfo4u
HSM
2020
Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems
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One solution is to use the GPU in a multitasking fashion to improve utilization. ...
HSM accurately predicts application slowdown with an average error of 6.8%, a significant improvement over the current state-of-the-art. ...
For memory-bound workloads, BW-App improves fairness by 18.1% on average compared to even partitioning. This improvement is not as high as for HSM-Fair, which improves fairness by 75% on average. ...
doi:10.1145/3373376.3378457
dblp:conf/asplos/0004JE20
fatcat:ecovkbgevzghzbil6rzxik2wfu
Baymax
2016
ACM SIGOPS Operating Systems Review
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Using DjiNN, a deep neural network service, Sirius, an end-to-end IPA workload, and traditional applications on a Nvidia K40 GPU, our evaluation shows that Baymax improves the accelerator utilization by ...
applications and increase the accelerator utilization. ...
Improving CPU Utilization There has been a large amount of prior work focusing on improving application QoS and hardware utilization [18, 20, 21, 23, 46] . ...
doi:10.1145/2954680.2872368
fatcat:ydy2iuyb3bd3lpfioog5sug6lu
G2LC: Resources Autoscaling for Real Time Bioinformatics Applications in IaaS
2015
Computational and Mathematical Methods in Medicine
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Its main purpose is to guarantee applications performance, while improving resource utilization. Real sequence searching data of BLAST is used to evaluate the effectiveness of G2LC. ...
This paper proposes an automated resource provisioning method, G2LC, for bioinformatics applications in IaaS. It enables application to output the results in a real time manner. ...
A key factor for improving utilization efficiency is resource provisioning. ...
doi:10.1155/2015/549026
pmid:26504488
pmcid:PMC4609414
fatcat:s2egonaej5bfxl3w7elqdqbbba
Leveraging Resource Prediction for Anticipatory Dynamic Configuration
2007
First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007)
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while improving utility to the user. ...
Self-adapting systems based on multiple concurrent applications must decide how to allocate scarce resources to applications and how to set the quality parameters of each application to best satisfy the ...
Second part of the challenge is to aggregate predictions from multiple sources. R3. Design efficient on-line algorithms for anticipatory configuration that improve expected utility for the user. ...
doi:10.1109/saso.2007.35
dblp:conf/saso/PoladianGSSSS07
fatcat:db5javtrpfeyddda4rzuq5iavq
Bubble-Up
2011
Proceedings of the 44th Annual IEEE/ACM International Symposium on Microarchitecture - MICRO-44 '11
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Using this methodology to arrive at "sensible" co-locations in Google's production datacenters with real-world large-scale applications, we can improve the utilization of a 500-machine cluster by 50% to ...
By using a bubble to apply a tunable amount of "pressure" to the memory subsystem on processors in production datacenters, our methodology can predict the performance interference between co-locate applications ...
We would also like to thank Neil Vachharajani for his healthy skepticism and keeping us on our toes. Finally, we would like to thank the reviewers for there feedback and suggestions. ...
doi:10.1145/2155620.2155650
dblp:conf/micro/MarsTHSS11
fatcat:kvjhak47jngglex5hswtwehhcq
A Data-Driven Approach to Dynamically Adjust Resource Allocation for Compute Clusters
[article]
2018
arXiv
pre-print
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In this work, we propose a mechanism that improves cluster utilization, thus decreasing the average turnaround time, while preventing application failures due to contention in accessing finite resources ...
Nowadays, data-centers are largely under-utilized because resource allocation is based on reservation mechanisms which ignore actual resource utilization. ...
are limited to improve system efficiency from the perspective of CPU utilization. ...
arXiv:1807.00368v1
fatcat:7byxnyhnkjatvnx4hio5qvg2e4
A Resource Utilization Prediction Model for Cloud Data Centers Using Evolutionary Algorithms and Machine Learning Techniques
2022
Applied Sciences
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Most of the existing mechanisms focus on single resource utilization prediction, such as memory, CPU, storage, network, or servers allocated to cloud applications but overlook the correlation among resources ...
This research focuses on multi-resource utilization prediction using Functional Link Neural Network (FLNN) with hybrid Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). ...
In the case of memory utilization prediction, the percentage improvement gain over the compared models is 25.0, 14. ...
doi:10.3390/app12042160
fatcat:zjsi7dcqfbfhlo3t7o6abik7iu
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