Matrix vector multiply techniques

Techniques are disclosed relating to parallel computing. In some embodiments, fine-grained data communication facilitates operations on large data sets such as multiplication of a sparse matrix by a vector. In this example, a first data set (the matrix) and a second data set (the vector) are distributed across multiple processing nodes. Performance of the overall multiplication operation may require communication of data among the processing nodes. In various embodiments, fine-grained communication of this data may reduce processing times and/or power consumption by avoiding congestion.