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John Owens's calculated h-index is 48. This page was automatically generated on 2018-06-13.

2089Owens:2007:ASOA Survey of General-Purpose Computation on Graphics Hardware
2001Owens:2008:GCGPU Computing
954Rixner:2000:MASMemory Access Scheduling
735Harris:2007:PPSParallel Prefix Sum (Scan) with CUDA
661Sengupta:2007:SPFScan Primitives for GPU Computing
507Owens:2007:RCFResearch Challenges for On-Chip Interconnection Networks
440Khailany:2001:IMPImagine: Media Processing with Streams
408Kapasi:2003:PSPProgrammable Stream Processors
361Rixner:2000:ROFRegister Organization for Media Processing
332Rixner:1998:ABAA Bandwidth-Efficient Architecture for Media Processing
308Kapasi:2002:TISThe Imagine Stream Processor
253Zhang:2011:AQPA Quantitative Performance Analysis Model for GPU Architectures
213Zhang:2010:FTSFast Tridiagonal Solvers on the GPU
202Lefohn:2006:GGEGlift: Generic, Efficient, Random-Access GPU Data Structures
199Stuart:2011:MMOMulti-GPU MapReduce on GPU Clusters
163Alcantara:2009:RPHReal-Time Parallel Hashing on the GPU
149Owens:2005:SAAStreaming Architectures and Technology Trends
144Silberstein:2008:ECOEfficient Computation of Sum-products on GPUs Through Software-Managed Cache
132Muyan-Ozcelik:2008:FDRFast Deformable Registration on the GPU: A CUDA Implementation of Demons
132Kapasi:2000:ECOEfficient Conditional Operations for Data-parallel Architectures
127Wang:2016:GAHGunrock: A High-Performance Graph Processing Library on the GPU
121Samant:2008:HPCHigh performance computing for deformable image registration: Towards a new paradigm in adaptive radiotherapy
119Tzeng:2010:TMFTask Management for Irregular-Parallel Workloads on the GPU
116Owens:2002:MPAMedia Processing Applications on the Imagine Stream Processor
115Gupta:2012:ASOA Study of Persistent Threads Style GPU Programming for GPGPU Workloads
100Kass:2006:IDOInteractive Depth of Field Using Simulated Diffusion on a GPU
95Davidson:2014:WPGWork-Efficient Parallel GPU Methods for Single Source Shortest Paths
91Park:2006:DSIDiscrete Sibson Interpolation
86Stuart:2009:MPOMessage Passing on Data-Parallel Architectures
86Ebeida:2011:EMPEfficient Maximal Poisson-Disk Sampling
84Sengupta:2006:AWSA Work-Efficient Step-Efficient Prefix Sum Algorithm
80Phillips:2009:RAPRapid Aerodynamic Performance Prediction on a Cluster of Graphics Processing Units
77Lefohn:2007:RSMResolution-Matched Shadow Maps
76Owens:2000:PROPolygon Rendering on a Stream Architecture
73Ebeida:2012:ASAA Simple Algorithm for Maximal Poisson-Disk Sampling in High Dimensions
68Khailany:2003:ETVExploring the VLSI Scalability of Stream Processors
68Patel:2012:PLDParallel Lossless Data Compression on the GPU
67Davidson:2011:AAMAn Auto-tuned Method for Solving Large Tridiagonal Systems on the GPU
63Kapasi:2001:SSStream Scheduling
63Patney:2008:RRAReal-Time Reyes-Style Adaptive Surface Subdivision
63Mattson:2000:CSCommunication Scheduling
61Stuart:2010:MVRMulti-GPU Volume Rendering using MapReduce
55Owens:2002:CGOComputer Graphics on a Stream Architecture
52Budge:2009:ODMOut-of-core Data Management for Path Tracing on Hybrid Resources
50Moerschell:2008:DTMDistributed Texture Memory in a Multi-GPU Environment
49Davidson:2012:EPMEfficient Parallel Merge Sort for Fixed and Variable Length Keys
48Szumel:2005:TAMTowards a Mobile Agent Framework for Sensor Networks
48Lefohn:2005:IEPImplementing Efficient Parallel Data Structures on GPUs

45Patney:2009:PVTParallel View-Dependent Tessellation of Catmull-Clark Subdivision Surfaces
44Davidson:2012:TTFToward Techniques for Auto-tuning GPU Algorithms
44Davidson:2010:TTFToward Techniques for Auto-Tuning GPU Algorithms
39Owens:2002:CRAComparing Reyes and OpenGL on a Stream Architecture
39Stuart:2011:ESPEfficient Synchronization Primitives for GPUs
36Sengupta:2011:EPSEfficient Parallel Scan Algorithms for many-core GPUs
35Ebeida:2011:EAGEfficient and Good Delaunay Meshes From Random Points
35Davidson:2011:RPFRegister Packing for Cyclic Reduction: A Case Study
34Lefohn:2005:DASDynamic Adaptive Shadow Maps on Graphics Hardware
32Jenkins:2011:LLFLessons Learned from Exploring the Backtracking Paradigm on the GPU
32Riffel:2004:MFMMio: Fast Multipass Partitioning via Priority-Based Instruction Scheduling
30Alcantara:2011:BAEBuilding an Efficient Hash Table on the GPU
29Owens:2005:AOGAssessment of Graphic Processing Units (GPUs) for Department of Defense (DoD) Digital Signal Processing (DSP) Applications
27Tzeng:2012:AGTA GPU Task-Parallel Model with Dependency Resolution
26Kepner:2016:MFOMathematical Foundations of the GraphBLAS
24Ebeida:2011:ICRIsotropic conforming refinement of quadrilateral and hexahedral meshes using two-refinement templates
23Glavtchev:2011:FSLFeature-Based Speed Limit Sign Detection Using a Graphics Processing Unit
22Park:2005:AFFA Framework for Real-Time Volume Visualization of Streaming Scattered Data
21Stuart:2011:EMTExtending MPI to Accelerators
21Stone:2011:GPAGPGPU parallel algorithms for structured-grid CFD codes
20Kniss:2005:OTOOctree Textures on Graphics Hardware
20Stuart:2010:GCGPU-to-CPU Callbacks
20Wu:2015:PCOPerformance Characterization of High-Level Programming Models for GPU Graph Analytics
20Phillips:2010:UTSUnsteady Turbulent Simulations on a Cluster of Graphics Processors
19Muyan-Ozcelik:2010:ATAA Template-Based Approach for Real-Time Speed-Limit-Sign Recognition on an Embedded System using GPU Computing
19Gupta:2009:TOFThree-Layer Optimizations for Fast GMM Computations on GPU-like Parallel Processors
17Patney:2010:FCAFragment-Parallel Composite and Filter
17Li:2012:KOTkANN on the GPU with Shifted Sorting
17Serebrin:2002:ASPA Stream Processor Development Platform
17Szumel:2006:TVPThe Virtual Pheromone Communication Primitive
15Tzeng:2012:FCHFinding Convex Hulls Using Quickhull on the GPU
15Gosink:2009:DPBData Parallel Bin-Based Indexing for Answering Queries on Multi-Core Architectures
14Ma:2007:UVRUltra-Scale Visualization: Research and Education
14Tzeng:2012:HPDHigh-Quality Parallel Depth-of-Field Using Line Samples
14Wang:2016:ACSA Comparative Study on Exact Triangle Counting Algorithms on the GPU
14Pan:2017:MGAMulti-GPU Graph Analytics
13Yang:2015:FSMFast Sparse Matrix and Sparse Vector Multiplication Algorithm on the GPU
13Zhang:2011:APEA Parallel Error Diffusion Implementation on a GPU
12Gupta:2011:CAMCompute \& Memory Optimizations for High-Quality Speech Recognition on Low-End GPU Processors
11Khailany:2000:ISAImagine: Signal and Image Processing Using Streams
11Zhang:2011:AHMA Hybrid Method for Solving Tridiagonal Systems on the GPU
10Ebeida:2013:SDSifted Disks
10Wang:2017:GGGGunrock: GPU Graph Analytics
10Ashkiani:2016:GMGPU Multisplit
9Muyan-Ozcelik:2011:RSRReal-Time Speed-Limit-Sign Recognition on an Embedded System Using a GPU
8Patney:2015:PAFPiko: A Framework for Authoring Programmable Graphics Pipelines
7Zhang:2012:PDEPlane-dependent Error Diffusion on a GPU
6Owens:2004:GTFGPUs tapped for general computing
5Muyan-Ozcelik:2016:MREMultitasking Real-time Embedded GPU Computing Tasks
5Ebeida:2016:DDTDisk Density Tuning of a Maximal Random Packing
4Owens:2007:TMSTowards Multi-GPU Support for Visualization
3Ashkiani:2018:GLAGPU LSM: A Dynamic Dictionary Data Structure for the GPU
3Mak:2014:GAEGPU-Accelerated and Efficient Multi-View Triangulation for Scene Reconstruction
3Geil:2014:WGCWTF, GPU! Computing Twitter's Who-To-Follow on the GPU
3Weber:2015:PRAParallel Reyes-style Adaptive Subdivision with Bounded Memory Usage
3Phillips:2011:AO2Acceleration of 2-D Compressible Flow Solvers with Graphics Processing Unit Clusters
2Abdelkader:2017:ACRA Constrained Resampling Strategy for Mesh Improvement
2Seitz:2013:AGIA GPU Implementation for Two-Dimensional Shallow Water Modeling
2Owens:2004:OTSOn The Scalability of Sensor Network Routing and Compression Algorithms
2Ashkiani:2016:PATParallel Approaches to the String Matching Problem on the GPU
2Wang:2016:FPSFast Parallel Skew and Prefix-Doubling Suffix Array Construction on the GPU
2Ashkiani:2018:ADHA Dynamic Hash Table for the GPU
1Szumel:2003:OTFOn the Feasibility of the UC Davis Metanet
1Ashkiani:2017:GMGPU Multisplit: an extended study of a parallel algorithm
1Muyan-Ozcelik:2017:MFMMethods for Multitasking among Real-time Embedded Compute Tasks Running on the GPU
1Wang:2017:MALMini-Gunrock: A Lightweight Graph Analytics Framework on the GPU
1Gosink:2008:BIABin-Hash Indexing: A Parallel Method For Fast Query Processing
1Abdelkader:2018:SCFSampling Conditions for Conforming Voronoi Meshing by the VoroCrust Algorithm
1Silberstein:2011:ASCApplying Software-Managed Caching and CPU/GPU Task Scheduling for Accelerating Dynamic Workloads

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