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EVALUATING COMPUTATIONAL COSTS WHILE HANDLING DATA AND CONTROL PARALLELISM
2008
Parallel Processing Letters
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The aim of this work is to introduce a computational costs system associated to a semantic framework for orthogonal data and control parallelism handling. ...
In such a framework a parallel application is described by a semantic expression involving in an orthogonal manner both data access and control parallelism abstractions. ...
On the other hand, a parallel application have also to deal with data access concerns that can heavily influence both the programming phase and the final computational costs. ...
doi:10.1142/s0129626408003296
fatcat:uacb3s5udjftpdx7vvzgf5hiu4
A COMPARATIVE EVALUATION OF THE GPU VS. THE CPU FOR PARALLELIZATION OF EVOLUTIONARY ALGORITHMS THROUGH MULTIPLE INDEPENDENT RUNS
2019
Zenodo
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This means that a GPU is not the universally best option for parallelizing multiple independent runs and that the choice of computation platform therefore should be an informed decision. ...
This is done through a number of experiments that evaluate the efficiency of the GPU versus the CPU in various scenarios. ...
Computational cost in relation to the amount of data handled To evaluate how the computational cost grows with the amount of data handled, the CPU and GPU implementations were tested withgenome sizes rangingfrom ...
doi:10.5281/zenodo.3253437
fatcat:4j4uwoxo4bem3puafuepzzzpiy
A Comparative Evaluation of the GPU vs The CPU for Parallelization of Evolutionary Algorithms Through Multiple Independent Runs
2017
International Journal of Computer Science & Information Technology (IJCSIT)
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This means that a GPU is not the universally best option for parallelizing multiple independent runs and that the choice of computation platform therefore should be an informed decision. ...
This is done through a number of experiments that evaluate the efficiency of the GPU versus the CPU in various scenarios. ...
Computational cost in relation to the amount of data handled To evaluate how the computational cost grows with the amount of data handled, the CPU and GPU implementations were tested with genome sizes ...
doi:10.5121/ijcsit.2017.9301
fatcat:bc4kn6a54ze2heifrj6iw4brda
Speculation with Little Wasting: Saving Cost in Software Speculation through Transparent Learning
2009
2009 15th International Conference on Parallel and Distributed Systems
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Evaluation Metric • Cost Efficiency Ratio = Speedup/ cost ratio • Speedup = T p /T s • Cost Ratio = sum(processors running times)/T s • The higher the better. ...
Challenges
• Input complexity
• Learning algorithms and overhead control
• Prediction errors
Input
Input
charact. ...
doi:10.1109/icpads.2009.130
dblp:conf/icpads/JiangMS09
fatcat:3o4iaahfujb47kuekr7elnul2a
FRIEDA: Flexible Robust Intelligent Elastic Data Management in Cloud Environments
2012
2012 SC Companion: High Performance Computing, Networking Storage and Analysis
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However, managing data effectively and efficiently over these cloud resources is challenging due to the myriad storage choices with different performance, cost trade-offs, complex application choices and ...
Additionally, we describe a range of data management strategies and show the benefit of flexible data management approaches in cloud environments. ...
FRIEDA provides more flexible controls on data partitioning, distribution, and computation while executing in a distributed parallel environment. ...
doi:10.1109/sc.companion.2012.132
dblp:conf/sc/GhoshalR12
fatcat:ukvd7gdv45gx5ousd6rjjmullm
Parallel Pipeline Volume Intersection for Real-Time 3D Shape Reconstruction on a PC Cluster
2006
Fourth IEEE International Conference on Computer Vision Systems (ICVS'06)
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To avoid the conflicts while keeping high percentage of CPU running time, we propose a tree structured thread control model. ...
By thus extension, the computation is accelerated greatly for arbitrary camera layouts. We also parallelized the 3-base-plane method and implemented it on a PC cluster. ...
Comparing with the plane based volume intersection, only the phase "VCC" is added and its computational cost is little. ...
doi:10.1109/icvs.2006.49
dblp:conf/icvs/WuTM06
fatcat:xdfzxamet5fevhurdbu3d26ohm
Evaluating the Impact of OpenMP 4.0 Extensions on Relevant Parallel Workloads
[chapter]
2015
Lecture Notes in Computer Science
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This paper also shows performance trade-offs between the OmpSs/OpenMP tasking and loop parallelism constructs and shows how a hybrid implementation that combines both approaches is sometimes the best option ...
In this paper we show the usefulness of three OmpSs features not currently handled by OpenMP 4.0 by deploying them over three applications of the PARSEC benchmark suite and showing the performance benefits ...
While the Pthreads version of Pgain makes use of a dynamically allocated array per thread to store the partial cost computations and performs a reduction of all these costs over a global array after the ...
doi:10.1007/978-3-319-24595-9_5
fatcat:73uijnkeyzbmvibunmpnceptju
clustermq enables efficient parallelization of genomic analyses
2019
Bioinformatics
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High performance computing (HPC) clusters play a pivotal role in large-scale bioinformatics analysis and modeling. ...
For the statistical computing language R, packages exist to enable a user to submit their analyses as jobs on HPC schedulers. ...
Supplementary Methods), we first tested the overhead cost for each of these tools by evaluating a function of negligible runtime and repeating this between 1000 and 10 9 times. ...
doi:10.1093/bioinformatics/btz284
pmid:31134271
pmcid:PMC6821287
fatcat:iur4u4tm3fdqrflyzc2buq7xe4
Elastic Stream Computing with Clouds
2011
2011 IEEE 4th International Conference on Cloud Computing
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We implemented a prototype system using Amazon EC2 and an IBM System S stream computing system to evaluate the effectiveness of our approach. ...
Our experimental results show that our approach reduces the costs by 80% while keeping the application's response latency low. ...
One is a "Data-Parallel Application" that distributes a data stream to multiple nodes and computes in parallel, and the other is a "Task-Parallel Application" that distributes a computation process to ...
doi:10.1109/cloud.2011.11
dblp:conf/IEEEcloud/IshiiS11
fatcat:dbsst4uegje6rfj6744lrbrzry
Potential of General Purpose Graphic Processing Unit for Energy Management System
2011
2011 Sixth International Symposium on Parallel Computing in Electrical Engineering
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The different performance evaluations show the high potential of GPGPU for the HMI part with a speedup factor up to 100 at the cost of acceptable approximations, while the benefit on the server side varies ...
The HMI investigation focuses on the applicability and performance improvement of GPGPU for scattered data interpolation algorithms typically used to visually represent the overall state of a power network ...
As more transistors are devoted to data processing rather than caching and flow control, the computation power offered by GPGPU is significantly larger than the one offered by the latest CPU. ...
doi:10.1109/parelec.2011.37
dblp:conf/parelec/TournierDL11
fatcat:ohpkge6z75b6nfkmq6uwwo2gmy
Reconfigurable FPGA architecture for computer vision applications in Smart Camera Networks
2013
2013 Seventh International Conference on Distributed Smart Cameras (ICDSC)
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Finally, performance evaluation results underline the potential of an hardware software codesign approach in reaching flexibility and reduced processing time. ...
In this vision, one of the biggest effort is in the definition of a flexible and reconfigurable SCN node architecture able to remotely update the application parameter and the performed computer vision ...
Then we will propose, implement and evaluate our parallel solution against the previously existent. ...
doi:10.1109/icdsc.2013.6778212
dblp:conf/icdsc/MaggianiSPPS13
fatcat:tq4fmtm4evhsfbwxsww7ct3nqa
Survey on improved Autoscaling in Hadoop into cloud environments
2013
The 5th Conference on Information and Knowledge Technology
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Based on the evaluation methods we understand that "The controller module and BEEMR" are best way to improve energy performance. ...
Nowadays technologies for analyzing big data are evolving rapidly. Because of that models and methods to design and analyze parallel processing of data is done automatically. ...
Further to this, we gratefully acknowledge those in the cloud computing team at the Department of Computer engineering and Information Technology, Amirkabir University, IRAN and Cloud Computing lab in ...
doi:10.1109/ikt.2013.6620031
fatcat:3ra3zakwgrd2zaeelc3h3jtrqe
CnC-Python
2012
Proceedings of the 3rd annual conference on Systems, programming, and applications: software for humanity - SPLASH '12
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CnC-Python, being implicitly parallel, avoids the use of these low-level constructs, thereby enabling Python programmers to achieve task, data and pipeline parallelism in a declarative fashion while only ...
Our implementation of CnC-Python uses the CnC Habanero-Java (HJ) runtime system, the Babel compiler to generate glue code while invoking Python from Java, and the multiprocessing module available in standard ...
This research is partially supported by the Center for Domain-Specific Computing (CDSC) funded by NSF Expeditions in Computing Award CCF-0926127. ...
doi:10.1145/2384716.2384763
dblp:conf/oopsla/Imam12
fatcat:pzkarsudkba55lzgdeyl4mehm4
Balanced MVC Architecture for High Efficiency Mobile Applications
2012
KSII Transactions on Internet and Information Systems
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And, we define a method to design a balanced MVC architecture which embodies functionality partitioning for high performance, and a simulation-based evaluation method of balanced MVC architectures. ...
Mobile devices such as Android devices are emerging as a convenient client computing device with mobility and context-sensing capability. ...
Pattern 1 consumes a large amount of network communication cost due to interaction between view and control layers while its computation cost is quite low. ...
doi:10.3837/tiis.2012.05.010
fatcat:7ko6kszqvbhdlebsrkg435xw2e
Performance Evaluation and Prediction of Parallel Big Data using MOA
2017
International Journal of Engineering and Technology
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These elements (nodes) are scalable but cost sensitive and well interconnected. They are precisely designed to handle massive applications on parallel fashion [7], [8] . ...
In addition, big data manipulation may exhibit volatile memory-paging, spatial locality and data flow control. ...
In the purchase of computer networks, for instance, network architecture is associated not only for computer costs, but also for factors such as their speedups, transaction processing rate, and bandwidth ...
doi:10.21817/ijet/2017/v9i2/170902200
fatcat:rxrktlntczdbzpooweg5kcq5ae
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