Digits Architectures Logiciels Informatique


Aubert Pierre : High Performance Computing for gamma ray detection

Jeudi 22 Mars 2018

The Ground based gamma-ray detector, like H.E.S.S, MAGIC, VERITAS, use two kind of analysis method.
The more common method is based on momentum calculation of the pictures (Hillas like methods), but it does not allow a good way to reject the noise.
The other way is to used precomputed pictures (called templates) of the expected signal in the telescopes.
This way allows a better stereoscopic reconstruction and discrimination.

The precision of this method implies a huge time of computation before the analysis, and also an expensive time during the analysis
because the pictures of the same event are compared pixel by pixel simultaneously.

Unfortunately, the CTA experiment will produce too much data for such analysis, 169 GB/s,
and it is not possible to have telescopes ordered by events due to the amount of produced data.
This imply the stereoscopic reconstructions using telescopes pictures are unrealizable.

The first part exposes how to deeply optimized the Hillas parameter computation.

The second part explains how to do pictures comparison by extracting the relevant information of the pictures in a massively parallel way,
and allows a stereoscopic reconstruction using the best templates physical parameters with likelihood computation when the data are quite reduced.

This algorithm used the Single Value Decomposition (SVD) algorithm to extract each picture's information in one or several singular values.
Thus, the computation time due to the image comparison diminish mercy to the simplification allowed by the singular values.
In the other hand, the computation time used to generate the template increases.