gpu based parallel implementation Search Results


gpu cuda-based implementation of the method – pedsy-mc  (Simphotek Inc)
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Gpu Cuda Based Implementation Of The Method – Pedsy Mc, supplied by Simphotek Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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gpu-based implementation rayconstruct r⃝–ir  (RayConStruct GmbH)
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RayConStruct GmbH gpu-based implementation rayconstruct r⃝–ir
Gpu Based Implementation Rayconstruct R⃝–Ir, supplied by RayConStruct GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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gpu-based implementation of the fdk  (RayConStruct GmbH)
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RayConStruct GmbH gpu-based implementation of the fdk
Gpu Based Implementation Of The Fdk, supplied by RayConStruct GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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gpu-based implementation of the rocs algorithm fastrocs  (Pfizer Inc)
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Pfizer Inc gpu-based implementation of the rocs algorithm fastrocs
Gpu Based Implementation Of The Rocs Algorithm Fastrocs, supplied by Pfizer Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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gpu-based implementation of infomax ica  (InfoMax Inc)
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InfoMax Inc gpu-based implementation of infomax ica
Scalp maps and respective equivalent dipole locations of eight reliable independent components identified <t>using</t> <t>RELICA</t> in the data of a representative participant. Each IC is connected by an arrow to its relative cluster. Each dot represents a particular IC of one (out of 150) <t>ICA</t> run. The more compact the cluster the higher the stability of a IC to small variations in the original data (bootstrapping). IC1 and IC2 account for vertical and lateral eye movement artifacts and IC7 and IC8 account for left and right neck muscle activity respectively. The high quality index (QIc) values for these ICs (respectively 92%, 89%, 93%, 91%) is consistent with the relative compactness of their RELICA IC clusters, and their high dopolarity is ascribed to the short electrode-source distance and power of such artifacts. Artifactual (non-brain) components with high dipolarity (Dip>90%) and replicability quality index (QIc>85%), and with equivalent dipole locations outside the brain volume such as these were removed from the data before proceeding with further analyses. IC4, IC5, IC15, and IC20, instead, represent meaningful, brain-based central, left, and right mu rhythm processes with high dipolarity and QIc. This 2D representation of the IC space enables also to detect possible ICA decomposition artifacts, i.e., components that might not have been successfully separated, by their “mustache”-like distribution (e.g. IC56).
Gpu Based Implementation Of Infomax Ica, supplied by InfoMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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computational software based on gpu implementations  (Biobeam Scientific)
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Biobeam Scientific computational software based on gpu implementations
Scalp maps and respective equivalent dipole locations of eight reliable independent components identified <t>using</t> <t>RELICA</t> in the data of a representative participant. Each IC is connected by an arrow to its relative cluster. Each dot represents a particular IC of one (out of 150) <t>ICA</t> run. The more compact the cluster the higher the stability of a IC to small variations in the original data (bootstrapping). IC1 and IC2 account for vertical and lateral eye movement artifacts and IC7 and IC8 account for left and right neck muscle activity respectively. The high quality index (QIc) values for these ICs (respectively 92%, 89%, 93%, 91%) is consistent with the relative compactness of their RELICA IC clusters, and their high dopolarity is ascribed to the short electrode-source distance and power of such artifacts. Artifactual (non-brain) components with high dipolarity (Dip>90%) and replicability quality index (QIc>85%), and with equivalent dipole locations outside the brain volume such as these were removed from the data before proceeding with further analyses. IC4, IC5, IC15, and IC20, instead, represent meaningful, brain-based central, left, and right mu rhythm processes with high dipolarity and QIc. This 2D representation of the IC space enables also to detect possible ICA decomposition artifacts, i.e., components that might not have been successfully separated, by their “mustache”-like distribution (e.g. IC56).
Computational Software Based On Gpu Implementations, supplied by Biobeam Scientific, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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gpu-based som implemented in cuda-som  (Rundo Cronova)
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Rundo Cronova gpu-based som implemented in cuda-som
Scalp maps and respective equivalent dipole locations of eight reliable independent components identified <t>using</t> <t>RELICA</t> in the data of a representative participant. Each IC is connected by an arrow to its relative cluster. Each dot represents a particular IC of one (out of 150) <t>ICA</t> run. The more compact the cluster the higher the stability of a IC to small variations in the original data (bootstrapping). IC1 and IC2 account for vertical and lateral eye movement artifacts and IC7 and IC8 account for left and right neck muscle activity respectively. The high quality index (QIc) values for these ICs (respectively 92%, 89%, 93%, 91%) is consistent with the relative compactness of their RELICA IC clusters, and their high dopolarity is ascribed to the short electrode-source distance and power of such artifacts. Artifactual (non-brain) components with high dipolarity (Dip>90%) and replicability quality index (QIc>85%), and with equivalent dipole locations outside the brain volume such as these were removed from the data before proceeding with further analyses. IC4, IC5, IC15, and IC20, instead, represent meaningful, brain-based central, left, and right mu rhythm processes with high dipolarity and QIc. This 2D representation of the IC space enables also to detect possible ICA decomposition artifacts, i.e., components that might not have been successfully separated, by their “mustache”-like distribution (e.g. IC56).
Gpu Based Som Implemented In Cuda Som, supplied by Rundo Cronova, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Scalp maps and respective equivalent dipole locations of eight reliable independent components identified using RELICA in the data of a representative participant. Each IC is connected by an arrow to its relative cluster. Each dot represents a particular IC of one (out of 150) ICA run. The more compact the cluster the higher the stability of a IC to small variations in the original data (bootstrapping). IC1 and IC2 account for vertical and lateral eye movement artifacts and IC7 and IC8 account for left and right neck muscle activity respectively. The high quality index (QIc) values for these ICs (respectively 92%, 89%, 93%, 91%) is consistent with the relative compactness of their RELICA IC clusters, and their high dopolarity is ascribed to the short electrode-source distance and power of such artifacts. Artifactual (non-brain) components with high dipolarity (Dip>90%) and replicability quality index (QIc>85%), and with equivalent dipole locations outside the brain volume such as these were removed from the data before proceeding with further analyses. IC4, IC5, IC15, and IC20, instead, represent meaningful, brain-based central, left, and right mu rhythm processes with high dipolarity and QIc. This 2D representation of the IC space enables also to detect possible ICA decomposition artifacts, i.e., components that might not have been successfully separated, by their “mustache”-like distribution (e.g. IC56).

Journal: NeuroImage

Article Title: Unidirectional brain to muscle connectivity reveals motor cortex control of leg muscles during stereotyped walking

doi: 10.1016/j.neuroimage.2017.07.013

Figure Lengend Snippet: Scalp maps and respective equivalent dipole locations of eight reliable independent components identified using RELICA in the data of a representative participant. Each IC is connected by an arrow to its relative cluster. Each dot represents a particular IC of one (out of 150) ICA run. The more compact the cluster the higher the stability of a IC to small variations in the original data (bootstrapping). IC1 and IC2 account for vertical and lateral eye movement artifacts and IC7 and IC8 account for left and right neck muscle activity respectively. The high quality index (QIc) values for these ICs (respectively 92%, 89%, 93%, 91%) is consistent with the relative compactness of their RELICA IC clusters, and their high dopolarity is ascribed to the short electrode-source distance and power of such artifacts. Artifactual (non-brain) components with high dipolarity (Dip>90%) and replicability quality index (QIc>85%), and with equivalent dipole locations outside the brain volume such as these were removed from the data before proceeding with further analyses. IC4, IC5, IC15, and IC20, instead, represent meaningful, brain-based central, left, and right mu rhythm processes with high dipolarity and QIc. This 2D representation of the IC space enables also to detect possible ICA decomposition artifacts, i.e., components that might not have been successfully separated, by their “mustache”-like distribution (e.g. IC56).

Article Snippet: Within RELICA, ICs were extracted using a GPU-based implementation of Infomax ICA , CUDAICA , whose relative speed on CUDA-enabled workstations made 150 bootstrap repetitions feasible.

Techniques: Activity Assay