CERN Accelerating science

ATLAS Note
Report number	ATL-UPGRADE-PROC-2011-004
Title	A new “Variable Resolution Associative Memory” for High Energy Physics
Author(s)	Annovi, A (Frascati) ; Amerio, S (INFN, Padua) ; Beretta, M (Frascati) ; Bossini, E (INFN, Pisa) ; Crescioli, F (INFN, Pisa) ; Dell'Orso, M (INFN, Pisa) ; Giannetti, P (INFN, Pisa) ; Hoff, J (Fermilab) ; Liberali, V (INFN, Milan) ; Liu, T (Fermilab) ; Magalotti, D (INFN, Perugia) ; Piendibene, M (INFN, Pisa) ; Sacco, A (INFN, Pisa) ; Schoening, A (U. Heidelberg, ITP) ; Soltveit, H K (U. Heidelberg, ITP) ; Stabile, A (INFN, Milan) ; Tripiccione, R (INFN, Ferrara) ; Vitillo, R (INFN, Pisa) ; Volpi, G (Frascati)
Corporate Author(s)	The ATLAS collaboration
Publication	2011
Imprint	20 May 2011
Number of pages	8
Subject category	Detectors and Experimental Techniques
Accelerator/Facility, Experiment	CERN LHC ; ATLAS
Free keywords	TDAQ, UPGRADE
Abstract	We describe an important advancement for the Associative Memory device (AM). The AM is a VLSI processor for pattern recognition based on Content Addressable Memory (CAM) architecture. The AM is optimized for on-line track finding in high-energy physics experiments. Pattern matching is carried out finding track candidates in coarse resolution “roads”. A large AM bank stores all trajectories of interest, called “patterns”, for a given detector resolution. The AM extracts roads compatible with a given event during detector read-out. Two important variables characterize the quality of the AM bank: its “coverage” and the level of “found fakes”. The coverage, which describes the geometric efficiency of a bank, is defined as the fraction of tracks that match at least a pattern in the bank. Given a certain road size, the coverage of the bank can be increased just adding patterns to the bank, while the number of found fakes unfortunately is roughly proportional to this number of patterns in the bank. Moreover, as the luminosity increases, the fake rate increases rapidly because of the increased silicon occupancy. To counter that, we must reduce the width of our roads to improve resolution. If we increase the road resolution using the current technology, the system would become very large and extremely expensive. We propose an elegant solution to this problem: the “variable resolution patterns”. Each pattern and each detector layer within a pattern will be able to use the best resolution, but we will use a “don’t care” feature (inspired from ternary CAMs) to reduce the resolution when a lower resolution is more appropriate. In other words can use patterns of variable shape. As a result we reduce the number of found fake roads, while keeping high the efficiency and avoiding the bank blow-up due to the improved resolution.
Copyright/License	Preprint: (License: CC-BY-4.0)

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