Future on-chip manycore systems are expected to have hundreds of cores, and to be used for a number of applications to amortize their fabrication costs. In this paper, we examine how software pipelines, which are useful for streaming/multimedia applications, can be efficiently executed on a manycore system with shared memory. The goal is to balance the stages of the pipeline under workload and resource variations. This paper presents ADAPT, a method to quickly detect bottleneck stages and add cores (workers) to those bottleneck stages at run-time. Further, if there are no idle workers, then a shuffling of workers across stages is performed to improve/maintain throughput. ADAPT is implemented in a 48-core system which is built using a commercial core and tool suite. For a variety of applications, ADAPT takes less than 2 μs for one run-time adaptation, and achieves up to 2.1× the throughput of a state-of-the-art method (which is modified and implemented in the same system for a fair comparison). These results illustrate the applicability of ADAPT for fine-grained run-time management of manycore systems to achieve high throughput for software pipelines.