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As the complexity of processor architectures increases, there is a widening gap between peak processor performance and sustained processor performance so that programs now tend to exploit only a fraction of available performance. While there is a tremendous amount of literature on program optimizations, compiler optimizations lack efficiency because they(More)
Modern compilers are responsible for translating the idealistic operational semantics of the source program into a form that makes efficient use of a highly complex heterogeneous machine. Since optimization problems are associated with huge and unstructured search spaces, this combinational task is poorly achieved in general , resulting in weak scalability(More)
Static compiler optimizations can hardly cope with the complex run-time behavior and hardware components interplay of modern processor architectures. Multiple architectural phenomena occur and interact simultaneously, which requires the optimizer to combine multiple program transformations. Whether these transformations are selected through static analysis(More)
Because processor architectures are increasingly complex, it is increasingly difficult to embed accurate machine models within compilers. As a result, compiler efficiency tends to decrease. Currently, the trend is on top-down approaches: static compilers are progressively augmented with information from the architecture as in profile-based, iterative or(More)
This paper presents a new distributed computation model adapted to manycore processors. In this model, the run is spread on the available cores by fork machine instructions produced by the compiler, for example at function calls and loops iterations. This approach is to be opposed to the actual model of computation based on cache and predictor. Cache(More)