Aim: Enable a radical improvement in the performance and scalability of a wide range of real-world applications relying on linear algebra software for future extreme-scale systems.
- Development of novel architecture-aware algorithms that expose
as much parallelism as possible, exploit heterogeneity, avoid
communication bottlenecks, respond to escalating fault rates, and help meet emerging power constraints - Exploration of advanced scheduling strategies and runtime
systems focusing on the extreme scale and strong scalability in
multi/many-core and hybrid environments - Design and evaluation of novel strategies and software support for both offline and online auto-tuning
- Results will appear in the open source NLAFET software library