Buffer Capacity Computation for Throughput Constrained Streaming Applications with Data-Dependent Inter-Task Communication

TL;DR: A dataflow model that allows for data-dependent communication, together with an algorithm that computes buffer capacities that guarantee satisfaction of a throughput constraint is introduced.

Abstract: Streaming applications are often implemented as task graphs, in which data is communicated from task to task over buffers. Currently, techniques exist to compute buffer capacities that guarantee satisfaction of the throughput constraint if the amount of data produced and consumed by the tasks is known at design-time. However, applications such as audio and video decoders have tasks that produce and consume an amount of data that depends on the decoded stream. This paper introduces a dataflow model that allows for data-dependent communication, together with an algorithm that computes buffer capacities that guarantee satisfaction of a throughput constraint. The applicability of this algorithm is demonstrated by computing buffer capacities for an H.263 video decoder.