Abstract:
This article presents OPTIMO, a 65-nm, 16-b, fully programmable, spatial-array processor with 49 cores and a hierarchical multi-cast network for solving distributed optim...Show MoreMetadata
Abstract:
This article presents OPTIMO, a 65-nm, 16-b, fully programmable, spatial-array processor with 49 cores and a hierarchical multi-cast network for solving distributed optimizations via the alternating direction method of multipliers (ADMM). ADMM is a projection-based method for solving generic-constrained optimizations' problems. In essence, it relies upon decomposing the decision vector into subvectors, updating sequentially by minimizing an augmented Lagrangian function, and eventually updating the Lagrange multiplier. The ADMM algorithm has typically been used for solving problems in which the decision variable is decomposed into two or multiple subvectors. We demonstrate six template algorithms and their applications and measure a peak energy efficiency of 279 GOPS/W.
Published in: IEEE Journal of Solid-State Circuits ( Volume: 55, Issue: 3, March 2020)