View-Oriented Parallel Programming (VOPP) is a novel parallel programming model which uses views for communication between multiple processes. With the introduction of views, mutual exclusion and shared data access are bundled together, which offers both convenience and high performance to parallel programming. This paper presents the implementation of VOPP on Chip-Multithreading processors, e.g. UltraSPARC T1. We demonstrate that our implementation of VOPP on multi-core platforms (namely Maotai) shows significantly better performance than directly applying the original DSM implementation of VOPP(namely VODCA) on our platform. Besides, we compare the performance of VOPP with MPI and OpenMP. The experimental results demonstrate that VOPP has better scalability than both MPI and OpenMP on our platform.
Data races hamper parallel programming and threaten the reliability of future software. This paper proposes the data race prevention scheme View-Oriented Data race Prevention (VODAP), which can prevent data races in the View-Oriented Parallel Programming (VOPP) model. VOPP is a novel shared-memory data-centric parallel programming model, which uses views to bundle mutual exclusion with data access. We have implemented the data race prevention scheme with a memory protection mechanism. Experimental results show that the extra overhead of memory protection is trivial in our applications. The performance is evaluated and compared with modern programming models such as OpenMP and Cilk.
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