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Our approach considers CPU utilization for mapping running threads with the appropriate core that can potentially deliver the actual needed capacity. The paper also introduces a mapping algorithm that is able to map threads to cores in an<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mi>O<\/mml:mi><mml:mo stretchy=\"false\">(<\/mml:mo><mml:mi>N<\/mml:mi><mml:mtext>\u2009<\/mml:mtext><mml:mi mathvariant=\"normal\">l<\/mml:mi><mml:mi mathvariant=\"normal\">o<\/mml:mi><mml:mi mathvariant=\"normal\">g<\/mml:mi><mml:mtext>\u2009<\/mml:mtext><mml:mi>M<\/mml:mi><mml:mo stretchy=\"false\">)<\/mml:mo><\/mml:math>time complexity, where<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M2\"><mml:mrow><mml:mi>N<\/mml:mi><\/mml:mrow><\/mml:math>is the number of cores and<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M3\"><mml:mrow><mml:mi>M<\/mml:mi><\/mml:mrow><\/mml:math>is the number of types of cores. In addition to that we also introduced a method of profiling heterogeneous architectures based on the discrepancy between the performances of individual cores. 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