Most recent research in instruction-level parallelism has focused on general-purpose applications such as the SPEC benchmarks. Many quantitative experiments have been performed over the years measuring the impact of different execution models and optimization techniques on these applications. Researchers have been developing various ILP architectures for media processors in order to exploit parallelism in audio, video, and graphics applications. It has been assumed that these applications contain far more potential parallelism than general-purpose code, but there have been few attempts to quantify the available parallelism. We present a linear complexity global scheduling algorithm that can process very long traces up to 1 billion operations. Therefore, traces of video applications such as MPEG1, MPEG2, MPEG4 and H.263 encoders and decoders can be analyzed. Using an idealized execution model, speedups of over 1000 have been found in some applications. The experiment shows that eliminating currently identifiable bottlenecks can allow the exploitation of huge amounts of ILP in audio and video applications.
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