Even in scientific computing, code development often lacks a basic understanding of performance bottlenecks and relevant optimization opportunities. Textbook code transformations are applied blindly without a clear goal in mind. This course teaches a structured model-based performance engineering approach on the compute node level. It aims at a deep understanding of how code performance comes about, which hardware bottlenecks apply and how to work around them. The pivotal ingredient of this process is a model which links software requirements with hardware capabilities. Such models are often simple enough to be done with pencil and paper (such as the well-known Roofline model), but they lead to deep insights and strikingly accurate runtime predictions. The lecture starts with simple benchmark kernels and advances to various algorithms from computational science.
Friedrich-Alexander Universität Erlangen-Nürnberg, Germany &
Università della Svizzera italiana, Switzerland
Course dates: March 27-31, 2017
- Lecture slides
- Hands-on exercises
- Additional material