GPI2 for GPUs: A PGAS framework for efficient communication in hybrid clusters
Lena Oden · Advances in parallel computing · 2014
Due to their high parallelism graphics processing units (GPUs) and GPU-based clusters have gained popularity in high-performance computing. However, data transfer in GPU-based clusters remains a challenging problem, due to the disjoint memory of GPU and host. New technologies, such as GPUDirect RDMA, improve data transfer among multiple GPUs, but they require many manual interventions from programmers to reach optimal performance.