This paper describes the large capacity hierarchical branch predictor in the 5.5 GHz IBM zEnterprise EC12 microprocessor. Performance analyses in a simulation model and on zEC12 hardware demonstrate the benefit of this hierarchy compared to a smaller one level predictor. Novel structures and algorithms for two level branch prediction are presented. Prediction information about multiple branches is bulk transferred from the second level into the first upon detecting a perceived miss in the first level. The second level does not directly make branch predictions. Access to the second level is limited when it is unlikely to be productive. The second level is systematically searched in an order that is likely to provide hits as early as possible. On the workloads analyzed in the simulation model, measurements show a maximum core performance benefit of 13.8%. On the two workloads analyzed on zEC12 hardware 3.4% and 5.3% system performance improvements are achieved.

The FlexMux specified in MPEG-4 systems merges different ElementaryStreams into one FlexMux channel. Statistical traffic models for the different ElementaryStream types and for the impact of the FlexMux are considered in order to estimate the statistical properties of the FlexMux output. The resulting FlexMux output p.d.f. is used to estimate the CBR channel bandwidth required to limit the loss to a given percentage.

As MPEG-4 uses objects to compose scenes, and each object is transmitted using one or more data streams (e.g. for audio, video base, and video enhancement layers) the network overhead for a single service can be very high. MPEG-4 systems specifies a multiplexing tool to reduce the network overhead. This multiplexer can drop frames, if the frames deadlines and the network channel QoS make a timely transmission impossible. The need to estimate the loss introduced by the multiplexer arises, even more so since MPEG-4 objects appear and disappear at random times, which increases the dynamic of the output traffic specification and QoS renegotiations. We present an approach to estimate the loss introduced by the multiplexer. The approach is based on statistical models for video and audio streams as well as for the dropping multiplexer.