Trapezoid: A Versatile Accelerator for Dense and Sparse Matrix Multiplications
Accelerating matrix multiplication is crucial to achieve high performance in many application
domains, including neural networks, graph analytics, and scientific computing. These …
domains, including neural networks, graph analytics, and scientific computing. These …
Azul: An Accelerator for Sparse Iterative Solvers Leveraging Distributed On-Chip Memory
Solving sparse systems of linear equations is a fundamental primitive in many numeric
algorithms. Iterative solvers provide an efficient way of solving large, highly sparse systems …
algorithms. Iterative solvers provide an efficient way of solving large, highly sparse systems …
Multi-Issue Butterfly Architecture for Sparse Convex Quadratic Programming
Convex quadratic optimization solvers are extensively utilized in various domains; however,
achieving optimal performance in diverse situations remains a significant challenge due to …
achieving optimal performance in diverse situations remains a significant challenge due to …
Large problems are not necessarily hard: A case study on distributed NMPC paying off
G Stomberg, M Raetsch, A Engelmann… - arXiv preprint arXiv …, 2024 - arxiv.org
A key motivation in the development of distributed Model Predictive Control (MPC) is to
widen the computational bottleneck of centralized MPC for large-scale systems. Parallelizing …
widen the computational bottleneck of centralized MPC for large-scale systems. Parallelizing …