Difference between revisions of "Performance model"
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== Introduction == | == Introduction == | ||
| + | For performance engineering the focus is on resource-based analytic loop performance models. One premise that is often valid in scientific computing is the steady state assumption: Most | ||
| + | programs comprise loops that are much longer than typical pipeline lengths or other hardware latencies. The execution in each of those loops can be seen as continuous streams of data (input and/or output) being manipulated by a continuous, periodic stream of instructions. | ||
== Roofline model == | == Roofline model == | ||
Revision as of 13:44, 5 June 2019
There is a wide range of completely different things coined under the term performance model. Here we adopt “the physics way” of using models in computer science, specifically for the interaction between hardware and software. A model in this sense is a “mathematical description” based on a simplified machine model that ignores most of the details of what is going on under the hood; it makes certain assumptions, which must be clearly specified so that the range of applicability of the model is entirely clear.
Introduction
For performance engineering the focus is on resource-based analytic loop performance models. One premise that is often valid in scientific computing is the steady state assumption: Most programs comprise loops that are much longer than typical pipeline lengths or other hardware latencies. The execution in each of those loops can be seen as continuous streams of data (input and/or output) being manipulated by a continuous, periodic stream of instructions.