Detector software

E.g. simulation of detector components

PA-PRO-2015-008

Publication title:

Antihyperon-Hyperon production in antiproton-proton annihilations with PANDA at FAIR

Publication author:

Michael Papenbrock

File upload:

PA-PRO-2015-008.pdf

Publication type:

Paper (PA)

Papers:

Proceedings (PRO)

Publication classification:

Publication date:

Monday, 17 August, 2015

Submitted by michael.papenbr... on Tue, 04/08/2015 - 10:13.

Publication abstract:

Proceedings for the FewBody conference in 2015. The corresponding talked focused on spin observables in antihyperon-hyperon production as well as highlighting the activities of the Uppsala group in terms of software development for PANDA. The discussion for the talk can be found here: https://panda.gsi.de/publication/ta-con-2015-011

PA-PRO-2015-004

Publication title:

Online Tracking Algorithms on GPUs for the PANDA Experiment at FAIR

Publication author:

L. Bianchi, A. Herten, J. Ritman, T. Stockmanns

File upload:

PA-PRO-2015-004.pdf

Publication type:

Paper (PA)

Papers:

Proceedings (PRO)

Publication classification:

Detector software

Publication date:

Sunday, 17 May, 2015

Submitted by l.bianchi@fz-ju... on Mon, 11/05/2015 - 23:56.

Publication abstract:

PANDA is a future hadron and nuclear physics experiment at the FAIR facility in construction in Darmstadt, Germany. In contrast with the majority of current experiments, PANDA's strategy for data acquisition is based on event reconstruction and selection from free-streaming data, performed in real time entirely by software algorithms using global detector information. This paper reports the status of the development of algorithms for the reconstruction of charged particle tracks, optimized for use in online data processing applications, using General-Purpose Graphic Processing Units. Two algorithms for trackfinding, the Triplet Finder and the Circle Hough are described, with details of their GPU implementations. Average track reconstruction times of less than 100 ns are obtained running the Triplet Finder on state-of-the-art computing-grade GPU cards. In addition, a proof-of-concept system for the dispatch of data to tracking algorithms using Message Queues is presented.