Techniques for solving large-scale graph problems on heterogeneous platforms

Abstract

The paper introduces techniques for solving various large-scale graph problems on hybrid architectures. The proposed approach is illustrated on the computation of minimum spanning tree and shortest paths. We provide a precise mathematical description accompanied by the information structure of required algorithms. Efficient parallel implementations of several graph algorithms are proposed based on this analysis. Hybrid computations allow using all the available resources on both multi-core CPUs and GPUs. Our implementation uses out-of-core memory algorithms to handle graphs that don’t fit in the main memory. Experimental results confirm high performance and scalability of the proposed solutions. Moreover, the proposed approach can be applied to other graph processing problems, which have recently rapidly increased in demand.