The Bulk Synchronous Parallel (BSP) model, as well as parallel programming interfaces based on BSP, classically target distributed-memory parallel architectures. In earlier work, Yzelman and Bisseling designed a MulticoreBSP for Java library specifically for shared-memory architectures. In the present article, we further investigate this concept and introduce the new high-performance MulticoreBSP for C library. Among other features, this library supports nested BSP runs. We show that existing BSP software performs well regardless whether it runs on distributed-memory or shared-memory architectures, and show that applications in MulticoreBSP can attain high-performance results. The paper details implementing the Fast Fourier Transform and the sparse matrix--vector multiplication in BSP, both of which outperform state-of-the-art implementations written in other shared-memory parallel programming interfaces. We furthermore study the applicability of BSP when working on highly non-uniform memory access (NUMA) architectures.