Earticle

Programming models for cloud computing has been a research focus recently. Current programming models for cloud computing mainly focus on improving the efficiency of the cloud computing platforms but little has been done on the performance predictability of models. This paper presents a cloud computing programming model, called BSPCloud. The BSPCloud has the advantages of predictable performance. BSPCloud uses a hybrid of distributed-memory and shared-memory bulk synchronous parallel (BSP) programming model. Computing tasks are first divided into a set of coarse granularity bulks which are computed by the distributed-memory BSP model, and each coarse granularity bulk is further divided into a set of bulk threads which are computed by the shared-memory BSP model. BSPCloud makes full use of the multi-core architecture, and more importantly, the performance of the BSPCloud is predictable. We have implemented a proof-of-concept BSPCloud parallel programming library in java. We give the implementation of BSPCloud parallel programming library and show how the library implements hybrid programming. We detail applying the BSPCloud library on matrix multiplication. The performance predictability and speedup are evaluated in the cloud platform. We give the results of experiments.