Sep 26 – 30, 2011
Vienna, Austria
Europe/Zurich timezone

Associative Memory design for the Fast TracKer processor (FTK) at ATLAS

Sep 27, 2011, 11:50 AM
25m
Room EI 7 (Vienna, Austria)

Room EI 7

Vienna, Austria

<font face="Verdana" size="2"><b>Vienna University of Technology</b> Department of Electrical Engineering Gusshausstraße 27-29 1040 Vienna, Austria
Oral ASICs A1b - ASICs

Speaker

Dr Matteo Beretta (Istituto Nazionale Fisica Nucleare (INFN) - Laboratori Nazionali di Frascati)

Description

We describe a VLSI processor for pattern recognition based on Content Addressable Memory (CAM) architecture, optimized for on-line track finding in high-energy physics experiments. We have developed this device using 65 nm technology combining a full custom CAM cell with standard-cell control logic. The customized design maximizes the pattern density, minimizes the power consumption and implements the functionalities needed for the planned Fast Tracker (FTK) [2], an ATLAS trigger upgrade project at LHC. We introduce a new variable resolution pattern matching technique using “don’t care” bits to set the pattern-matching window for each pattern and each layer can be independently.

Summary 500 words

We present a new VLSI processor for pattern recognition based on Content Addressable Memory (CAM), optimized for on-line track finding in high-energy physics experiments. A large CAM bank stores all trajectories of interest and extracts the ones compatible with a given event.
This task is naturally parallelized by a CAM architecture able to output identified trajectories, recognized among a huge amount of possible combinations, in just a few 100 MHz clock cycles. This device is optimized for the planned Fast Tracker (FTK) [1] processor, an ATLAS trigger upgrade project at LHC.

The CAM memory array, organised in macro blocks, has been designed with a full-custom approach to minimizearea and power consumption. The full-custom macro block contains 8 sub-blocks of 32 CAM words of 18 bits (cells) each. The peculiar feature of this CAM device is that matches are obtained as multiple matches of different CAM words at different times. Eight CAM words are organized into a “pattern”. The matches of single CAM words are stored into latches and kept until an init is issued. The pattern matches if all or a majority of the CAM words are matched. Typical applications use this feature to perform pattern recognition for detectors with up to 8 layers.
Six dedicated bits of each CAM word can be used to implement 3 ternary bits (”don’t care bits”) and implement variable size patterns.
To reduce power consumption, we have used a mixed solution of current-race and selective-precharge matchlinesensing techniques. The area of the sub-block is 55.42 μm × 57.60 μm. Between sub block pairs we have placeda dummy row which controls the timing of the enable signals of the current generators and the matchline resets.
To prevent malfunctions due to process and mismatch variations, the timing of control signals can be trimmed bymeans of a programmable delay. The total area of a macro block containing 4.6 kbits is 225.40 μm × 122.40 μm.
Whereas, the estimated power consumption is in the worst power case about 0.5 mW at 1.44 V corresponding to15 μW for each pattern of 8*18 bits. Finally, the full-custom block frame has been designed to be compatible with the standard cell environment in order to allow integration with interface and control logic. We describe the design of a 12mm2 MPW prototype and of the final AMchip, of which the parameters are summarized in table 1.
We discuss also possible future extensions based on 3-D technology. This processor has a flexible and easilyconfigurable structure that makes it suitable for applications also in other experimental environments. Most application are expected to benefits from the variable resolution feature.
For the FTK application we expect a gain equivalent to a factor of 5 extra patterns at with a silicon area cost of jsut less than 20%.

References
[1] A. Annovi et al., “The fast tracker architecture for the LHC baseline luminosity,” PoS, vol. EPS-HEP2009, p. 136, 2009.

Primary author

Dr Matteo Beretta (Istituto Nazionale Fisica Nucleare (INFN) - Laboratori Nazionali di Frascati)

Co-authors

Dr Alberto Annovi (Istituto Nazionale Fisica Nucleare (INFN) - Laboratori Nazionali di Frascati) Mr Alberto Stabile (Istituto Nazionale Fisica Nucleare (INFN) - Sezione di Milano) Prof. Andre Schoening (University of Heidelberg) Mr Edoardo Bossini (Istituto Nazionale Fisica Nucleare (INFN) - Sezione di Pisa) Dr Francesco Crescioli (Istituto Nazionale Fisica Nucleare (INFN) - Sezione di Pisa) Mr Hans Kristian Soltveit (University of Heidelberg) Ms Ilaria Sacco (University of Mannheim) Dr Jim Hoff (Fermilab) Prof. Mauro Dell'Orso (Istituto Nazionale Fisica Nucleare (INFN) - Sezione di Pisa) Dr Paola Giannetti (Istituto Nazionale Fisica Nucleare (INFN) - Sezione di Pisa) Dr Silvia Amerio (Fermilab) Dr Ted Liu (Fermilab) Prof. Tripiccione Raffaele (University of Ferrara) Prof. Valentino Liberali (Università degli Studi di Milano)

Presentation materials