Stream languages explicitly describe fork-join parallelism and pipelines, offering a powerful programming model for many-core Multi-Processor Systems on Chip (MPSoC). In an embedded resource-constrained system, adapting stream programs to fit memory requirements is particularly important. In this paper we present a new approach to re- duce the memory footprint required to run stream programs on MPSoC. Through an exploration of equivalent program variants, the method selects parallel code minimizing mem- ory consumption. For large program instances, a heuristic accelerating the exploration phase is proposed and evalu- ated. We demonstrate the interest of our method on a panel of ten significant benchmarks. Using a multi-core modulo scheduling technique, our approach lowers considerably the minimal amount of memory required to run seven of these benchmarks while preserving throughput.