--- ---

John Owens's calculated h-index is 29. This page was automatically generated on 2012-01-25.

1302Owens:2007:ASOA Survey of General-Purpose Computation on Graphics Hardware
446Owens:2008:GCGPU Computing
358Rixner:2000:MASMemory Access Scheduling
301Khailany:2001:IMPImagine: Media Processing with Streams
297Rixner:2000:ROFRegister Organization for Media Processing
267Rixner:1998:ABAA Bandwidth-Efficient Architecture for Media Processing
263Kapasi:2003:PSPProgrammable Stream Processors
256Sengupta:2007:SPFScan Primitives for GPU Computing
229Harris:2007:PPSParallel Prefix Sum (Scan) with CUDA
199Kapasi:2002:TISThe Imagine Stream Processor
173Owens:2007:RCFResearch Challenges for On-Chip Interconnection Networks
119Lefohn:2006:GGEGlift: Generic, Efficient, Random-Access GPU Data Structures
96Owens:2005:SAAStreaming Architectures and Technology Trends
94Kapasi:2000:ECOEfficient Conditional Operations for Data-parallel Architectures
87Owens:2002:MPAMedia Processing Applications on the Imagine Stream Processor
69Owens:2000:PROPolygon Rendering on a Stream Architecture
65Silberstein:2008:ECOEfficient Computation of Sum-products on GPUs Through Software-Managed Cache
55Samant:2008:HPCHigh performance computing for deformable image registration: Towards a new paradigm in adaptive radiotherapy
55Khailany:2003:ETVExploring the VLSI Scalability of Stream Processors
54Muyan-Ozcelik:2008:FDRFast Deformable Registration on the GPU: A CUDA Implementation of Demons
49Mattson:2000:CSCommunication Scheduling
48Owens:2002:CGOComputer Graphics on a Stream Architecture
44Kass:2006:IDOInteractive Depth of Field Using Simulated Diffusion on a GPU
35Park:2006:DSIDiscrete Sibson Interpolation
32Owens:2002:CRAComparing Reyes and OpenGL on a Stream Architecture
31Lefohn:2005:IEPImplementing Efficient Parallel Data Structures on GPUs
31Patney:2008:RRAReal-Time Reyes-Style Adaptive Surface Subdivision
30Zhang:2010:FTSFast Tridiagonal Solvers on the GPU
29Lefohn:2007:RSMResolution-Matched Shadow Maps

28Stuart:2009:MPOMessage Passing on Data-Parallel Architectures
28Alcantara:2009:RPHReal-Time Parallel Hashing on the GPU
28Sengupta:2006:AWSA Work-Efficient Step-Efficient Prefix Sum Algorithm
26Riffel:2004:MFMMio: Fast Multipass Partitioning via Priority-Based Instruction Scheduling
25Szumel:2005:TAMTowards a Mobile Agent Framework for Sensor Networks
25Moerschell:2008:DTMDistributed Texture Memory in a Multi-GPU Environment
19Lefohn:2005:DASDynamic Adaptive Shadow Maps on Graphics Hardware
16Park:2005:AFFA Framework for Real-Time Volume Visualization of Streaming Scattered Data
15Zhang:2011:AQPA Quantitative Performance Analysis Model for GPU Architectures
15Phillips:2009:RAPRapid Aerodynamic Performance Prediction on a Cluster of Graphics Processing Units
13Owens:2005:AOGAssessment of Graphic Processing Units (GPUs) for Department of Defense (DoD) Digital Signal Processing (DSP) Applications
12Budge:2009:ODMOut-of-core Data Management for Path Tracing on Hybrid Resources
12Kniss:2005:OTOOctree Textures on Graphics Hardware
12Patney:2009:PVTParallel View-Dependent Tessellation of Catmull-Clark Subdivision Surfaces
12Serebrin:2002:ASPA Stream Processor Development Platform
10Stuart:2010:MVRMulti-GPU Volume Rendering using MapReduce
9Khailany:2000:ISAImagine: Signal and Image Processing Using Streams
8Szumel:2006:TVPThe Virtual Pheromone Communication Primitive
8Tzeng:2010:TMFTask Management for Irregular-Parallel Workloads on the GPU
6Gosink:2009:DPBData Parallel Bin-Based Indexing for Answering Queries on Multi-Core Architectures
6Ma:2007:UVRUltra-Scale Visualization: Research and Education
6Stuart:2011:MMOMulti-GPU MapReduce on GPU Clusters
5Ebeida:2011:EMPEfficient Maximal Poisson-Disk Sampling
4Owens:2004:GTFGPUs tapped for general computing
4Davidson:2011:AAMAn Auto-tuned Method for Solving Large Tridiagonal Systems on the GPU
4Kapasi:2001:SSStream Scheduling
4Sengupta:2011:EPSEfficient Parallel Scan Algorithms for many-core GPUs
3Ebeida:2011:EAGEfficient and Good Delaunay Meshes From Random Points
3Patney:2010:FCAFragment-Parallel Composite and Filter
2Stuart:2010:GCGPU-to-CPU Callbacks
2Muyan-Ozcelik:2010:ATAA Template-Based Approach for Real-Time Speed-Limit-Sign Recognition on an Embedded System using GPU Computing
2Davidson:2010:TTFToward Techniques for Auto-Tuning GPU Algorithms
1Glavtchev:2011:FSLFeature-Based Speed Limit Sign Detection Using a Graphics Processing Unit
1Davidson:2011:RPFRegister Packing for Cyclic Reduction: A Case Study
1Phillips:2010:UTSUnsteady Turbulent Simulations on a Cluster of Graphics Processors
1Ebeida:2011:ICRIsotropic conforming refinement of quadrilateral and hexahedral meshes using two-refinement templates
1Zhang:2011:APEA Parallel Error Diffusion Implementation on a GPU
1Zhang:2011:AHMA Hybrid Method for Solving Tridiagonal Systems on the GPU
1Jenkins:2011:LLFLessons Learned from Exploring the Backtracking Paradigm on the GPU
1Szumel:2003:OTFOn the Feasibility of the UC Davis Metanet

---