Gecikme verimli sakla-ve-yönlendir şemasında iletişim hacmi artışının azaltılması

Sparse matrix operations such as sparse matrix-vector (SpMV) are latency bound applications where number of messages sent by processors dominate the overall communication overhead. In prior work, Store and Forward (STFW) scheme was proposed and implemented to scale such fine-grain operations as SpMV by operating on specialized Virtual Process Topologies (VPTs). However, the STFW scheme incur an increase in the communication volume due to the STFW overhead. This increase in total communication volume disturbs the scalability of the STFW scheme, especially in sparse matrix-matrix (SpMM) kernels where a sparse matrix is post-multiplied by a tall-and-skinny dense matrix. In this work, we propose and implement a Kernighan-Lin-based (KL) heuristic to iteratively improve the one-to-one mapping produced by the initial task partition. The objective of this heuristic is to reduce the increase in the total communication volume to be incurred by the STFW scheme in SpMV, and SpMM type of kernels. We evaluated the effectiveness of the proposed KL-based heuristic in improving the Total Communication Volume and Maximum Weighted Communication Volume metrics through experimental performance comparisons using VPTs of various dimensions and constructive mapping methods.