A Minimum Cost Approach for Segmenting Networks of Lines
International Journal of Computer Vision
IEEE Transactions on Parallel and Distributed Systems
A data and task parallel image processing environment
Parallel Computing - Parallel computing in image and video processing
Approaches for Integrating Task and Data Parallelism
IEEE Concurrency
Fast Anisotropic Gauss Filtering
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
A Software Architecture for User Transparent Parallel Image Processing on MIMD Computers
Euro-Par '01 Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing
A PVM Implementation of a Portable Parallel Image Processing Library
EuroPVM '96 Proceedings of the Third European PVM Conference on Parallel Virtual Machine
Concurrency and Computation: Practice & Experience
Commodity cluster-based parallel processing of hyperspectral imagery
Journal of Parallel and Distributed Computing
Optimization principles and application performance evaluation of a multithreaded GPU using CUDA
Proceedings of the 13th ACM SIGPLAN Symposium on Principles and practice of parallel programming
Program optimization carving for GPU computing
Journal of Parallel and Distributed Computing
CUDA-Lite: Reducing GPU Programming Complexity
Languages and Compilers for Parallel Computing
A Grid framework to enable parallel and concurrent TMA image analyses
International Journal of Grid and Utility Computing
A GPGPU compiler for memory optimization and parallelism management
PLDI '10 Proceedings of the 2010 ACM SIGPLAN conference on Programming language design and implementation
Debunking the 100X GPU vs. CPU myth: an evaluation of throughput computing on CPU and GPU
Proceedings of the 37th annual international symposium on Computer architecture
Programming Massively Parallel Processors: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach
User transparent task parallel multimedia content analysis
Euro-Par'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part II
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The research area of Multimedia Content Analysis (MMCA) considers all aspects of the automated extraction of knowledge from multimedia archives and data streams. To satisfy the increasing computational demands of emerging MMCA problems, there is an urgent need to apply High Performance Computing (HPC) techniques. As most MMCA researchers are not also HPC experts, however, there is a demand for programming models and tools that are both efficient and easy to use. Existing user transparent parallelization tools generally use a data parallel approach in which data structures (e.g. video frames) are scattered among the available nodes in a compute cluster. For certain MMCA applications a data parallel approach induces intensive communication, however, which significantly decreases performance. In these situations, we can benefit from applying alternative approaches. We present Pyxis-DT, a user transparent parallel programming model for MMCA applications that employs both data and task parallelism. Hybrid parallel execution is obtained by run-time construction and execution of a task graph consisting of strictly defined building block operations. Results show that for realistic MMCA applications the concurrent use of data and task parallelism can significantly improve performance compared to using either approach in isolation. Extensions for GPU clusters are also presented.