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Using Multi-Core HW/SW Co-design Architecture for Accelerating K-means Clustering Algorithm
[article]
2018
arXiv
pre-print
Preserved Fulltext
The empirical result on this two-level structure over multi-core FPGA-based architecture provides 330X speed-up compared to a conventional software-only solution. ...
K-mean clustering is an essential tool for many big data applications including data mining, predictive analysis, forecasting studies, and machine learning. ...
with the proposed architecture in [17] , which is a multi-core implementation of k-clustering. ...
arXiv:1807.09250v1
fatcat:wbvre7jsbbgxtjlcilfwfvpqv4
K-means Spectral Unmixing for Multi-channel Imaging and Image Analysis Platform at a Core Facility
2019
Journal of Biomolecular Techniques
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To help users solve channel bleed-through problem, the Multiphoton Imaging (MP) core at URMC developed a novel method by using K-means clustering to separate mixed channels and clear up images. ...
There is an increasing need of multi-channel fluorescent imaging to simultaneously visualize different biological structures and the dynamic interactions between them. ...
K-means Spectral Unmixing for Multi-channel Imaging and Image Analysis Platform at a Core Facility Yurong Gao 1 , Tristan McRae 1 1
University of Rochester Medical Center There is an increasing need ...
pmid:31892897
pmcid:PMC6936903
fatcat:uto3upuuyjaalfeym7uaykn7ya
A Critical Performance Study of Memory Mapping on Multi-Core Processors: An Experiment with k-means Algorithm with Large Data Mining Data Sets
2010
International Journal of Computer Applications
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Experiments are carried out with k-means algorithm, a popular Data mining (DM) clustering algorithm, to explore the potential of Multi-Core hardware under OpenMP API and POSIX threads. ...
This paper mainly focuses on performance of memory mapped files on Multi-Core processors. ...
The percentage of mmap() benefit is more in parallel k-means than serial k-means in selected Multi-Core machines. ...
doi:10.5120/211-358
fatcat:hfy3b56jqfaahazjvce2n4xo3a
Parallel Implementation of K-Means on Multi-Core Processors
2014
GESJ: Computer Science and Telecommunications
unpublished
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Nowadays, all most personal computers have multi-core processors. We try to exploit computational power from the multi-core architecture. We need a new design on existing algorithms and software. ...
The experimental results demonstrate considerable speedup rate of the proposed parallel k-means clustering method run on a multicore/multiprocessor machine, compared to the serial k-means approach. ...
This paper also focuses on parallelizing k-means algorithm, but we base our study on the multi-core architecture. ...
fatcat:asfre3te45ez3ngmh5ffs763le
Evaluating and modeling power consumption of multi-core processors
2012
Proceedings of the 3rd International Conference on Future Energy Systems Where Energy, Computing and Communication Meet - e-Energy '12
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Based on our analysis, we present a methodology for estimating the power consumption of multi-core processors. ...
With the advent of multi-core processors and their energy-saving mechanisms, there is a necessity to model their power consumption. ...
Four cores f=2.13 f=2.0 f=2.5 f=2.0 f=2.5 f=2.0 f=2.5 mean +/-ci mean +/-ci mean +/-ci mean +/-ci mean +/-ci mean +/-ci mean +/-ci 10 Figure 1 : 1 An abstract architecture of a multi-core processor ...
doi:10.1145/2208828.2208840
dblp:conf/eenergy/BasmadjianM12
fatcat:xbv263xswfe2bksvwzuemr2som
Efficient Multi-Core Computations in Computational Statistics and Econometrics
2012
2012 IEEE 15th International Conference on Computational Science and Engineering
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One way for accelerating these computations is to use the parallel computing with multi-core platforms. ...
The purpose of this paper is to present an extensive quantitative and qualitative study of the multi-core programming models for parallel statistical and econometric computations. ...
Figure 1 presents the mean execution times for all the statistical kernels using all reviewed multi-core programming models. ...
doi:10.1109/iccse.2012.44
dblp:conf/cse/MichailidisM12
fatcat:sxmrlzh34zggtokoygmefhmqku
Multi-Class Ubm-Based Mllr M-Vector System For Speaker Verification
2013
Zenodo
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K-means based multi-class MLLR m-vector system for speaker verification on NIST 2008 SRE core condition (det 7 task) 7.3. ...
−1 L (10) Step 4: Repeat Step 2 to 3 upto the number of classes
K-means based multi-class MLLR m-vector system The K-means based system is similar to statistical clustering based multi-class MLLR m-vector ...
doi:10.5281/zenodo.43355
fatcat:fmksrb7jxjhtdbg65rwff3kv7m
Image Restoration by DOG Multi-Scale Analysis
2011
Microscopy and Microanalysis
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This paper describes a newly developed image restoration method, which uses a multi-scale analysis of an image with wavelet-like sub-band decomposition. ...
On the contrary, we separate multi-scale operators and a signal completely in the decomposition procedure and generate optimum 2D filters for images with a wide range of frequencies, which allows a simple ...
Image J can be divided into a blurred image and its differentiation shown in eq. (1). . (1) means a Gaussian distribution with a standard deviation and k is a suffix on the condition: :(k=1,…,n). means ...
doi:10.1017/s1431927611006817
fatcat:457shdqp6zabvo5xz2ub2wzety
A Simple Baseline for Low-Budget Active Learning
[article]
2022
arXiv
pre-print
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We show that although the state-of-the-art active learning methods work well given a large labeling budget, a simple K-means clustering algorithm can outperform them on low budgets. ...
We call this variant of K-means sampling as multi K-means. ...
In both evaluation benchmarks, K-means is consistently better than multi K-means. ...
arXiv:2110.12033v2
fatcat:ga5qvvhpijffzjewm6axhtksc4
Large-Scale Hierarchical k-means for Heterogeneous Many-Core Supercomputers
2018
SC18: International Conference for High Performance Computing, Networking, Storage and Analysis
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) in parallel, making k-means a more feasible solution for complex scenarios. ...
This paper presents a novel design and implementation of k-means clustering algorithm targeting the Sunway TaihuLight supercomputer. ...
on Xilinx ZC706 FPGA [27] , and a multi-core processor based approach running a custom implementation of parallel k-means on 8-core Intel i7-3770k processor [13] . ...
doi:10.1109/sc.2018.00016
fatcat:trz6pjfk6bgmvcjxywbep5snbm
Accelerated dictionary learning with GPU/Multi-core CPU and its application to music classification
2012
2012 IEEE 11th International Conference on Signal Processing
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In this paper a new GPU and multi-core CPU accelerated k-means clustering and GMM training is proposed. ...
K-means clustering and GMM training, as dictionary learning procedures, lie at the heart of many signal processing applications. ...
From Table IV In this paper we have proposed to use GPU and multi-core CPU to accelerate bag-of-words method especially dictionary learning of k-means clustering and GMM training. ...
doi:10.1109/icosp.2012.6491789
fatcat:misxraykm5bihlwyr47u3pukki
Parallel Multigrid Solvers Using OpenMP/MPI Hybrid Programming Models on Multi-Core/Multi-Socket Clusters
[chapter]
2011
Lecture Notes in Computer Science
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-10G
T2K/Tokyo (2/2)
• AMD Quad-core Opteron
(Barcelona) 2.3GHz
• 4 "sockets" per node
-16 cores/node
• Multi-core，multi-socket
system
• cc-NUMA architecture
-careful configuration needed ...
$omp parallel do private (ii) do k= istart, iend ii = 3*EXPORT_ITEM(k) WS(3*k-2)= X(ii-2) WS(3*k-1)= X(ii-1) WS(3*k )= X(ii ) enddo ! ...
doi:10.1007/978-3-642-19328-6_19
fatcat:aji7of4wgveirdx2yenob4qiua
An Optimization Algorithm to Build Low Congestion Multi-Ring Topology for Optical Network-on-Chip
2018
IEICE transactions on information and systems
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An algorithm is developed to optimize the low congestion multi-ring topology. ...
In this paper, we proposed an algorithm to build a low congestion multi-ring architecture for optical network-on-chip without additional wavelength or scheduling overhead. ...
That means that the interface of this core has 3 micro-rings. The number of micro-rings of different cores can be calculated in this way. ...
doi:10.1587/transinf.2017edp7330
fatcat:57ujbqrfjrdh3hhkdcb4kzn3qa
A Fully Programmable Reed-Solomon Decoder on a Multi-Core Processor Platform
2012
IEICE transactions on information and systems
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The multi-core processor platform is a 2-Dimension mesh array of Single Instruction Multiple Data (SIMD) cores, and it is well suited for digital communication applications. ...
Unlike usual VLSI approaches, this paper presents a high throughput fully programmable Reed-Solomon decoder on a multi-core processor. ...
Overview of Reed-Solomon Codes The most common representation of RS codes is RS(n, k, t), which means a block of k symbols is encoded into n symbols by adding 2 × t parity symbols. ...
doi:10.1587/transinf.e95.d.2939
fatcat:wiin25zmdvflpnarhbip3b7itu
Thread-Based Modeling and Analysis in Multi-Core-Based V2X Communication Device
2022
Sustainability
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Furthermore, we analyze the performance of a multi-core-based vehicle service system utilizing the proposed method. ...
First, we propose a thread-level performance modeling and analysis method based on queuing theory in a multi-core-based vehicle service system. ...
a node is given by: ρ i = e i m i µi • G(K − 1) G(K) (13) The mean number of threads for a single server node can be calculated as follows: K i = K ∑ k=1 ( e i µ i ) k • G(K − k) G(K) (14) According to ...
doi:10.3390/su14148277
fatcat:hs7kzdv47fdzvg7ypposlcpqt4
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