The continuous increase of the number of processing cores on die poses a new set of challenges to HPC applications programming including how to model, write, and verify software that has to use the full power of NoC-based manycore processors. Therefore, to simplify program development for the Single-chip Cloud Computer (SCC), it is desirable to have high-level, shared memory-based parallel programming abstractions (e.g., an OpenMP-like programming model). One of the key components of any similar programming model are barrier synchronization primitives, coordinating the work of parallel threads. To allow high-level barrier constructs to deliver good performance, we need an efficient implementation of the underlying synchronization algorithm. In this paper, we propose effective barrier synchronization implementations for shared-memory programming on non-cache-coherent cluster-on-chip represented by the Intel SCC. In particular, we present an extensive evaluation of the overhead associated with integrating barrier algorithms required for OpenMP runtime libraries on such a machine, validating several implementation variants that efficiently exploit the network topology and leveraging SCC-specific hardware. We provide a detailed evaluation of the performance achieved by different approaches by using micro-benchmarks.