The real-time execution of contemporary complex media applications requires energy-efficient processing capabilities beyond those of current superscalar processors. We observe that the complexity of contemporary media applications requires support for multiple forms of parallelism, including ILP, TLP, and various forms of DLP, such as subword SIMD, short vectors, and streams. Based on our observations, we propose an architecture, called ALP, that efficiently integrates all of these forms of parallelism with evolutionary changes to the programming model and hardware. The novel part of ALP is a DLP technique called  SIMD vectors and streams (SVectors/SStreams) , which is integrated within a conventional superscalar-based CMP/SMT architecture with subword SIMD. This technique lies between subword SIMD and vectors, providing significant benefits over the former at a lower cost than the latter. Our evaluations show that each form of parallelism supported by ALP is important. Specifically, SVectors/SStreams are effective, compared to a system with the other enhancements in ALP. They give speedups of 1.1 to 3.4X and energy-delay product improvements of 1.1 to 5.1X for applications with DLP.
['Ruchira Sasanka', 'M. Li', 'Sarita V. Adve', 'Yen-Kuang Chen', 'Eric Debes']
ALP: Efficient support for all levels of parallelism for complex media applications