Maxeler’s Multiscale Dataflow Technology delivers unmatched performance per unit space and per Watt for high performance computing applications.
With Maxeler dataflow engines, the algorithm is mapped onto dataflow cores, and data streams from memory through the dataflow engine where operations are performed and data is forwarded directly from one dataflow core to another without being written to the off-chip memory. The dataflow structure not only provides high compute performance, but also naturally optimizes the use of memory bandwidth, so even algorithms that are traditionally regarded as memory bound such as sparse matrix solvers can still be accelerated by orders of magnitude.
Maxeler technology has been successfully utilized for large-scale complex Monte Carlo simulations, irregular financial tree-based partial differential equation (PDE) solvers, 3D finite difference (FD) and finite element (FE) solvers, as well as optimization and pattern matching problems. You can see examples of different computational methods in some of our publications:
- Finite difference: FD modeling beyond 70Hz
- Finite element: Surviving the end of scaling
- Conjugate descent based optimization: Fast 3D ZO CRS Stack
- Monte Carlo: Computational acceleration of derivatives