On the effective parallel programming of multi-core processors

Multi-core processors are considered now the only feasible alternative to the large single-core processors which have become limited by technological aspects such as power consumption and heat dissipation. However, due to their inherent parallel structure and their diversity, multi-cores are difficult to program. There is a variety of different approaches to simplify multi-core programming, but most of them are only solving parts of the problem, leaving the rest as (unrealistic) assumptions. This thesis proposes a unitary framework (called MAP) for effective programming of multi-core processors, filling a gap in the multi-core programming models landscape. The framework is designed to assist the programmer in application design, implementation, optimization, and performance analysis. MAP is built using the expertise and guidelines gathered while programming three types of multi-core processors for three different classes of applications. Thus, MAP has several stages: application design, modeling, prototyping, and tuning, as well as performance checkpoints and a performance guided feedback loop. Overall, MAP is a viable application-centric approach to programming for multi-core processors. However, part of the tool support is lacking and more has to be done, as future work, to replace some of the phases which are now developed by hand with (semi-)automated tools