S
SA
SAD image, stereo matching
483
Scalability
atlas construction
789
CCL
580
CT image reconstruction
676
fast circuit optimization
375
MO computations
8
SVM
293
Scaling
black hole simulations
107–108
CT image reconstruction
674
fast circuit optimization
375
genome matching
182–183
MO computations
18
molecular electrostatics
50
pattern matching acceleration
194–195
SPIRiT MRI
734
VSM
458
Scaling coefficient, LB models
396–397
Scatter-gather iterations, Multi-GPU Cascade SVM
305
Scheduling kernel, macro-gate event-driven simulation
352
Scientific simulation, GPU computing status
2
Scratch memory model, atlas construction
786–787
Scripting, ABM transition function behavior
317–319
Secondary structure, RNA folding problem
199–200
Seed buffer, photon transport
256
Segmentation
atlas construction
771–772
DBT
651
medical imaging
737
radiographic image simulation
815–816
Semiautomatic axon segmentation, brain connectivity reconstruction
793–795
Sensitivity list, macro-gate event-driven simulation
352
Separability property, integral image calculation
527
Sequence database scanning, with SW algorithm
long sequences
168–169
overview
155–157
registers and loop unrolling
163–168
shared memory implementation
160–162
simple CUDA implementation
157–160
Sequential minimal optimization (SMO)
future work
310
map step
298
reduce step
299–302
SVM
296–297
testing phase
302–303
Serial input/output operations, image/video processing
558–560
Shooting function, photon transport
258
SHUTTLE dataset, SVM evaluation
308
Sierpinski triangle, IFS
264
Signal processing
ASR
602–603
GPU computing status
599–600
LDPC
619
real-time stereo
473–474
speed-limit-sign recognition
514
SPIRiT MRI
723
Similarity evaluation, chemical informatics
algorithmic transformation and memory optimization
27–30
core methods
22
data-parallel objective function
23–25
LINGO overview
21–22
overview
19–21
parallelization and arithmetic optimization
22–27
SIML
31–33
3D shape molecule overlay
21
Simulation phase, gate-level simulation
event-driven
352
oblivious simulation
352–354
overview
351–355
test benches
354–355
Simultaneous algebraic reconstruction techniques (SART)
iterative CT reconstruction algorithms
700–702
and OS-SIRT
695
Single instruction multiple data (SIMD)
CT image reconstruction
676
DBT GPU acceleration
650
fast circuit optimization
366–367
GPU-based parallelization
368
ITK-based medical imaging
738
and OS-SIRT
696
speech models
614
stereo matching
489
Single-instruction multiple-thread (SIMT)
DBT GPU acceleration
650
gate-level simulation
345–346
genome-matching acceleration
174
Single-photon emission computed tomography (SPECT), tomographic image reconstruction
685
Single-precision (SP)
ASR
613
black hole simulations
105–107
CT image reconstruction
663
dynamical quadrature grids
39
MD methods
69
MRI reconstruction
720
n
-body simulations
131
object detection
539–540
radiographic image simulation
828
Single resolution adaptive window, stereo matching
487–491
Sizing heuristics, macro-gates
355
Skip-ahead algorithm, Mersenne Twister MT19937
240–242
Slack allocation (SA), fast circuit optimization evaluation
374
Smith-Waterman (SW) algorithm
pattern matching
algorithms, implementations, evaluations
187–192
antidiagonal approach
188–189
basic problem
185–186
core method
186–187
data packing
192
future work
196
hash tables
192
overlapping search
191–192
overview
193–196
reduced dependency
187–188
row/column parallel approach
188–191
protein identification
long sequences
168–169
overview
156–157
registers and loop unrolling
163–168
shared memory implementation
160–162
simple CUDA implementation
157–160
sequence database scanning
155–156
SMs
SNR
SO
Sobol quasi-random generator
formulation
235
implementation
236
parallelization
235–236
performance evaluation
242–245
Solution construction phase, AntMinerGPU
329–330
Solution-evaluation kernel, AntMinerGPU
335–337
Source reading, de-mosaicing
588–589
Sparse-matrix vector multiplication (SpMV), MRI reconstruction
717
Sparse warps, random walks in path tracing
404
Sparsity, SPIRiT MRI
724
Speech feature extactor, speech recognition application
602
Speech recognition
Speed-limit-sign recognition
compute power adjustments
511–512
fast-radial symmetry
505–506
feature-based pipeline
499–501
FFT correlation with nonlinear filters
507
future work
513–514
implementation
505–507
methods
499–505
overview
497–498
pipeline scalability
512–513
recognition results
508
results
507–513
SIFT-based pipeline
505
template-based pipeline
500–505
Spin-orbit (SO) interactions, black hole simulations
109
Spring forces, and LB methods
395
SSD
State-based agent simulation, ABM with CUDA
314–315
Stellar spectral synthesis
basic problem
95
flux calculation/aggregation
95–96
GRASSY platform
division of labor
97–98
interpolation decomposition
97
overview
97
performance model
100
precision issues
98–99
pseudo-code
98–99
testing
100
texture packing
97
steps
94–95
Stereo matching
algorithms, implementations, evaluations
475–485
basic problem
473–474
core method
475
cross-checking
484–485
foreground
vs
. full image
490–493
Middlebury evaluation
486–487
multiresolution background modeling
475–478
multiresolution
vs
. single resolution
487–490
multiresolution stereo matching
478–479
performance evaluation
486–493
single CUDA kernel
479–485
Stream compaction, object detections
533–535
Streaming-multiprocessors (SMs)
DBT GPU acceleration
650–652
speed-limit-sign recognition
512–513
tomographic image reconstruction
684
Strong classifiers, object detection
521–522
Stump-based classifier, definition
521–522
Successive overview relaxation (SOR) method, atlas construction
778–780
Sum of squared differences (SSD), B-splines
754
Support vector machine (SVM)
algorithms, implementations, evaluations
296–306
basic problem
293
binary SVM
294–295
block/grid sizes
303–304
core method
294–295
future work
310
GPU performance
308–310
instance port
306
multiclass SVM
295
performance evaluation
306–310
SMO
296–297
SMO map step
298
SMO reduce step
299–302
testing phase
302–303
SVM
Synthesizable test benches, gate-level simulation
354–355
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