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| 1 : | jhr | 97 | %!TEX root = report.tex |
| 2 : | % | ||
| 3 : | |||
| 4 : | \chapter{Introduction} | ||
| 5 : | jhr | 100 | |
| 6 : | Diderot is a domain-specific language for programming image analysis algorithms on | ||
| 7 : | parallel hardware. | ||
| 8 : | It supports a high-level programming model based on the mathematics of continuous | ||
| 9 : | tensor fields that are reconstructed from discrete image-data sets (\eg{}, MRI data). | ||
| 10 : | Diderot is also designed to be implemented on parallel hardware. | ||
| 11 : | |||
| 12 : | \section{Basic concepts} | ||
| 13 : | The design of Diderot is based on three core concepts: image data, the continuous fields | ||
| 14 : | that are reconstructed from them, and the actors that represent the computations over | ||
| 15 : | the fields. | ||
| 16 : | We give a high-level overview of these in this section. | ||
| 17 : | |||
| 18 : | \subsection{Images} | ||
| 19 : | |||
| 20 : | \subsection{Fields} | ||
| 21 : | |||
| 22 : | \subsection{Actors} | ||
| 23 : | |||
| 24 : | |||
| 25 : | \section{Diderot by example} | ||
| 26 : | % include VR example here |
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