Sequoia: programming the memory hierarchy
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
CellSs: a programming model for the cell BE architecture
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Sequoia: programming the memory hierarchy
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Compilation for explicitly managed memory hierarchies
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
Evaluation of memory performance on the cell BE with the SARC programming model
Proceedings of the 9th workshop on MEmory performance: DEaling with Applications, systems and architecture
Celling SHIM: compiling deterministic concurrency to a heterogeneous multicore
Proceedings of the 2009 ACM symposium on Applied Computing
Achieving high memory performance from heterogeneous architectures with the SARC programming model
Proceedings of the 10th workshop on MEmory performance: DEaling with Applications, systems and architecture
Transactions on high-performance embedded architectures and compilers III
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The Cell processor is a typical example of a heterogeneous multiprocessor on-chip architecture that uses several levels of parallelism to deliver high performance. Reducing the gap between peak performance and effective performance is the challenge for software tool developers and the application developers. Image processing and media applications are typical "main stream" applications. We use the Harris algorithm for detection of Points of Interest in an image as a benchmark to compare the performance of several parallel schemes on a Cell processor. The impact of the DMA controlled data transfers and the synchronizations between SPEs explains the differences between the performance of the different parallelization schemes. These results will be used to design a tool for an efficient mapping of image processing applications on multi-core architectures.