B
Back-face culling test, programmable graphics pipeline
428
Background modeling, real-time stereo
475–478
Background subtraction algorithm, image/video processing
548–550 , 552–554
Backprojection
CT projection filtering
669–672
image reconstruction method
686
list-mode image reconstruction
679
list-mode OSEM
681
Backward mapping, CT projection filtering
669
Backward operator, MRI reconstruction
715–717
Backward propagation, FFT
638
Baker-Campbell-Hausdorf (BCH) expansion, MD calculations
61 , 70–71
Barnes-Hut multiple acceptance criteria, fast N -body simulations
121–122
Barnes-Hut n -body algorithm, CUDA implementation
algorithm overview
76–77
basic problem
75–76
evaluation methodology
88–89
global optimizations
78–79
kernel 1 optimization
79–80
kernel 2 optimization
80–81
kernel 3 optimization
81–83
kernel 4 optimization
83
kernel 5 optimization
84–86
kernel 6 optimization
86
limitations
91
optimizations overview
86–88
results
89–90
Base pairs (BPs)
genome-matching acceleration
174 , 178–179
RNA folding problem
199–200
Basis functions
B-spline registration
752–753 , 755–758 , 766
electronic structure
60 , 65 , 69
fine-scale facial deformation
419–420
high-resolution facial details
420–421
large-scale deformation
416–417
MO computations
8–11
MRI
712
multiclass SVM
307
Basis sets
basic concept
8
DFT calculations
133 , 137
MO algorithms
10–14 , 16–18
Bayer pattern color filter array (CFA)
583–584
BDP2, programmable graphics pipeline in CUDA
434
Becke kernels
comparison
40–41
serial triple loop pseudo-code
38
Becke weight, quadrature grid DFT calculations
core method
36–37
implementation
37–39
kernel comparison
40
Belief propagation
LDPC
620 , 627
real-time stereo
487
BFGS algorithm, GSO calculations
23 , 25–27
Bidirectional reflectance distribution function (BRDF), random walks in path tracing
409–410
Bidirectional scattering distribution function (BSDF), random walks in path tracing
402–403 , 406
BigDFT code
benefits and limitations
144–145
BLAS routines
140–143
code structure
138
convolutions
138–139
core method
135–138
CPU code
145
Daubechies wavelets
134
definition
133–134
efficiency developments
149
hybrid code performance
145–147
implementation
140
kinetic convolution and preconditioner
139
kinetic operator
136
local potential
136
magic filters
136
molecule simulation domain example
135
multiple core calculations
148
operations
136–137
overview
134
parallel distribution
147
performance evaluation
140 , 150
3D operators
140–143
Bijection, MaxEnt with
284–285
Bilateral filter (BF), CT reconstruction
696 , 702–703
Bilinear interpolation, de-mosaicing
algorithms
586–593
filtering enhancements
593–597
performance
597–598
Binary black hole (BBH) systems
103
Binary support vector machine
294–295
Biomolecular systems, electrostatics algorithms
core method
45
direct Coulomb summation
47–51 , 56–57
MDH method
45 , 54–56
overview
43–44
short-range cutoff
50–55 , 57–58
Bit error rate (BER), LDPC
619 , 626
Bit nodes (BN), LDPC
620 , 622–623
Biweight Tuckey test, visual saliency motion estimator kernel
460
Black hole (BH) simulations
GPU implementation
106–107
GPU supercomputing clusters
107–109
numerical algorithm
105
overview
103–104
performance results
107–108
PN approximation
104–105
statistical results
109
BLAS routines
atlas construction
778
BigDFT code
138 , 140–145 , 147
MaxEnt model
287–290
MD calculations
67–68
BLAST, pattern matching acceleration
192
Block-based data structures, brain connectivity reconstruction
795
Block compressed Sparse Row (BSR), MRI reconstruction
717
Block-per-point method, quadrature grid DFT calculations
38
Born-Oppenheimer approximation
basic approach
59
direct MD
60
MD calculations
72
Bottom-up visual saliency model
definition
451
schematic
452
Boundary condition (BC)
atlas construction
780–781 , 786
BigDFT code
137 , 139–140 , 149
brain connectivity reconstruction
801
DBT
652
real-time speed-limit-sign recognition
506
Boundary element methods (BEM), and FMM
114
Bounding box kernel, Barnes Hut n -body algorithm
76–77
Box-Muller transform, random number generator performance
243
BPTI, quadrature grid calculations
41–42
Brain connectivity reconstruction, in EM
axon surface visualization
795–797
core methods
793–797
future work
811–812
GPU active ribbon segmentation
797–802
GPU axon segmentation
809
GPU-based volume brick filtering
802–803
GPU implicit surface ray casting
797
GPU volume brick boundary detection
803–809
histogram-based boundary detection
810–811
HistogramVoxelDirect algorithm
805 , 807–809
HistogramVoxelSweep algorithm
804–805
implementation
797–809
level set re-distancing
801–802
level set updating
797–800
on-demand volume filtering
796
overview
793
performance analysis
809–811
semiautomatic axon segmentation
793–795
3D axon tracking
802
3D volume visualization
795–797
Breadth-first search (BFS), Graph Cuts for computer vision
446–447
Breast cancer screening, overview
647–649
Bricking, brain connectivity reconstruction
796
Brute-force message group loading, ABM communication
319
B-splines, deformable registration algorithm
coefficient optimization
754–756
cost function
753–755
cost function with deformation field
759–762
cost function gradient
762–766
deformation field
752–753
implementation
756–766
initialization
757–758
input, output, state
756
overview
751–752
performance analysis
767–769
process flowchart
757
tile symmetry
756–757
Butterfly reduction, MaxEnt model
283–285
BX cells, RNA folding algorithm
204
..................Content has been hidden....................

You can't read the all page of ebook, please click here login for view all page.
Reset
18.188.178.181