Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization
This work extends communication-avoiding Krylov subspace techniques to first-order block coordinate descent methods for support vector machines and proximal least-squares problems. The synchronization-avoiding variants reduce latency by a tunable factor of $s$ and attain speedups up to 5.1x on a Cray XC30 supercomputer.