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Automatic Task Formation Techniques for the Multi-level Computing ArchitectureStewart, Kirk 30 July 2008 (has links)
The Multi-Level Computing Architecture (MLCA) is a multiprocessor system-on-chip architecture designed for multimedia applications. It provides a programming model
that simplifies the process of writing parallel applications by eliminating the need for explicit synchronization. However, developers must still invest effort to design applications that fully exploit the MLCA’s multiprocessing capabilities. We present a set of compiler techniques to streamline the process of developing applications for the MLCA. We present an algorithm to automatically partition a sequential application into tasks that can be executed in parallel. We also present code generation algorithms to translate annotated, sequential C code to the MLCA’s programming model. We provide an experimental evaluation of these techniques, performed with a prototype compiler based upon the open-source ORC compiler and integrated with the MLCA Optimizing Compiler. This evaluation shows that the performance of automatically generated code compares favourably to that of manually written code.
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Automatic Task Formation Techniques for the Multi-level Computing ArchitectureStewart, Kirk 30 July 2008 (has links)
The Multi-Level Computing Architecture (MLCA) is a multiprocessor system-on-chip architecture designed for multimedia applications. It provides a programming model
that simplifies the process of writing parallel applications by eliminating the need for explicit synchronization. However, developers must still invest effort to design applications that fully exploit the MLCA’s multiprocessing capabilities. We present a set of compiler techniques to streamline the process of developing applications for the MLCA. We present an algorithm to automatically partition a sequential application into tasks that can be executed in parallel. We also present code generation algorithms to translate annotated, sequential C code to the MLCA’s programming model. We provide an experimental evaluation of these techniques, performed with a prototype compiler based upon the open-source ORC compiler and integrated with the MLCA Optimizing Compiler. This evaluation shows that the performance of automatically generated code compares favourably to that of manually written code.
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