<p>Over the last three decades, computer architects have been able to achieve an increase in performance for single processors by, e.g., increasing clock speed, introducing cache memories and using instruction level parallelism. However, because of power consumption and heat dissipation constraints, this trend is going to cease. In recent times, hardware engineers have instead moved to new chip architectures with multiple processor cores on a single chip. With multi-core processors, applications can complete more total work than with one core alone. To take advantage of multi-core processors, we have to develop parallel applications that assign tasks to different cores. On each core, pipeline, data and task parallelization can be used to achieve higher performance. Dataflow programming languages are attractive for achieving parallelism because of their high-level, machine-independent, implicitly parallel notation and because of their fine-grain parallelism. These features are essential for obtaining effective, scalable utilization of multi-core processors.</p><p>In this thesis work we have parallelized an existing audio codec - Adaptive Multi-Rate Wide Band (AMR-WB) - written in the C language for single core processor. The target platform is a multi-core AMR11 MP developer board. The final result of the efforts is a working AMR-WB encoder implemented in CAL and running in the OpenDF simulator. The C specification of the AMR-WB encoder was analysed with respect to dataflow and parallelism. The final implementation was developed in the CAL Actor Language, with the goal of exposing available parallelism - different dataflows - as well as removing unwanted data dependencies. Our thesis work discusses mapping techniques and guidelines that we followed and which can be used in any future work regarding mapping C based applications to CAL. We also propose solutions for some specific dependencies that were revealed in the AMR-WB encoder analysis and suggest further investigation of possible modifications to the encoder to enable more efficient implementation on a multi-core target system.</p>

Over the last three decades, computer architects have been able to achieve an increase in performance for single processors by, e.g., increasing clock speed, introducing cache memories and using instruction level parallelism. However, because of power consumption and heat dissipation constraints, this trend is going to cease. In recent times, hardware engineers have instead moved to new chip architectures with multiple processor cores on a single chip. With multi-core processors, applications can complete more total work than with one core alone. To take advantage of multi-core processors, we have to develop parallel applications that assign tasks to different cores. On each core, pipeline, data and task parallelization can be used to achieve higher performance. Dataflow programming languages are attractive for achieving parallelism because of their high-level, machine-independent, implicitly parallel notation and because of their fine-grain parallelism. These features are essential for obtaining effective, scalable utilization of multi-core processors. In this thesis work we have parallelized an existing audio codec - Adaptive Multi-Rate Wide Band (AMR-WB) - written in the C language for single core processor. The target platform is a multi-core AMR11 MP developer board. The final result of the efforts is a working AMR-WB encoder implemented in CAL and running in the OpenDF simulator. The C specification of the AMR-WB encoder was analysed with respect to dataflow and parallelism. The final implementation was developed in the CAL Actor Language, with the goal of exposing available parallelism - different dataflows - as well as removing unwanted data dependencies. Our thesis work discusses mapping techniques and guidelines that we followed and which can be used in any future work regarding mapping C based applications to CAL. We also propose solutions for some specific dependencies that were revealed in the AMR-WB encoder analysis and suggest further investigation of possible modifications to the encoder to enable more efficient implementation on a multi-core target system.