Final Report Summary - ARTLHCFE (Accurate Real-time Tracking in LHC Full Events)
Executive Summary:
The main very general goal of the ARTLHCFE project is to advance the high energy physics (HEP) research that focuses on the fundamental nature of matter and energy, space and time. Any discovery in this field will help to deepen our understanding of nature and to answer compelling questions about the origin of particle masses, the existence of new symmetries of nature as well as extra dimensions. Answers to such fascinating questions can be found at particle accelerators and collider facilities. HEP experiments are testing our knowledge of the universe at very high precision, producing an incredible amount of data and becoming incredibly complex and expensive; my specific work in the trigger and Super-Computer research area becomes every day more important to increase the efficiency for sample collection with this complex system and as final outcome to save money. These experiments need an enormous computing power to analyze and collect data. Ideas for making the trigger more powerful and at lower cost are very important. The strategy of the "optimal mapping of a complex algorithm in different technologies" is a general approach that can speed up enormously any kind of calculation by providing the capability of a high degree of parallelism. The trend of using a combination different technologies such as CPUs and FPGAs for systems requiring high computing power and extremely short execution time has been expanding not only in physics experiments, but even in non-academic fields, like for example financial applications. It could be very important in the area of medical imaging for real time, fast diagnosis, when the patient is under examination.
This combination of electronic technologies is promising, but it is more challenging than the use of a multi-core CPU, since it requires the use of FPGA hardware and the knowledge of computer-aided-design (CAD) tools. It requires in fact the capability to exploit these powerful instruments at the highest level. For this reason I think the HEP work in this area is important for showing the potential of these devices and spreading the skills needed to use them efficiently. If people become expert with these tools the world computing power could make an incredible jump and we could save money (less expensive systems), energy (minor consumption), and space (more compact systems).
In order to achieve these goals I'm pushing the development of the FastTracKer (FTK) processor for online trajectory reconstruction in the ATLAS experiment. This project combines an Associative Memory ASIC specialized for massive parallelism in data correlation searches and FPGAs for all other functions. This choice was driven by a balance between the development and production cost versus the gains in performance.
I have led the development of the FastTracker simulation the essential tool to study and design the FTK processor and the procedures used by it. This tool is now nearly ready to be used not only for FTK development, but also by the wider audience of the ATLAS experiment. The inclusion of all FTK algorithms in the FTK simulation is a major milestone that was met and allowed to complete the studies needed for the FTK Technical design report. A preliminary version of the FTK performance and direct applications to the ATLAS trigger is available in [1]. My activity was crucial for the completion of the FTK TDR [2] during the last year of the ARTLHCFE project. The FTK TDR was eventually endorsed the LHCC in September 2013. In the last months of the project I have been involved in several aspects of the preparation of an FTK performance note that describes the use and integration of FTK in the ATLAS High-Level Triggers. The note is now being finalized and presented to ATLAS. During 2014 it will be completed and it will eventually become a public ATLAS note.
Regarding the Associative Memory I studied the novel variable resolution Associative Memory technique recently introduced for the FTK project [3]. This new device increases the effectiveness of Associative Memory devices by a factor roughly 5 and there is more potential yet to be explored. The proof of concept and study of the variable resolution Associative Memory performances is the most innovative result of my activity. During summer 2012 a first prototype of the variable resolution Associative Memory has been delivered and successfully tested (see figures 1 and 2 in the attached file). The first version of this device is now ready for use [4].
My studies influenced key choices in the development of electronics boards that are building blocks of FTK: the Data Formatter, the Data Organizer and the Track Fitter. This work allowed to have an optimal use of the hardware resources that makes the FTK an efficient processor compared to CPUs. The FTK project now has a valid configuration being realized in hardware that will allow to process the crowded event with up to 75 simultaneous proton-proton collision and thousands of charged tracks that the ATLAS experiment will collect until the end of the current decade.
Since the first prototypes of the FastTracker boards are becoming available, I worked to integrate them in the ATLAS experiment. This activity pursue the immediate goal of integrating the FTK processor in ATLAS and the longer term goal to show the powerfulness of the approach followed by FTK. The existing FTK prototypes have been installed in ATLAS and are under test (see figure 3 in the attached file). The integration of the FTK boards continued until the end of the project. During early 2013, the FTK boards have been included in data taking and pattern matching has been shown with real data. The acquired data compared well with FTK simulation. This was a major achievement and a milestone in the preparation of the FTK TDR.
Finally, for the development of trigger strategies using FTK it is important to have under control the effect that the trigger selection has on the data sample collected and to be analyzed. I had an important connection role between the FTK team and the ATLAS community in the studies to define the optimal use of the FTK information in the event selection.
In order to stay up to date with data analysis problematics and to contribute directly to the understanding of the fundamental constituents of matter, I joined the group searching for Higgs boson in the gold ZZ channel. This is one of the analyses that gave a large contribution to a Higgs-like particle discovery announced in July 2012 [5]. I continued my activity for Higgs data analysis contributing to the optimization of the selection used for the discovery and the study of the Higgs boson properties [6,7].
While the development of the FastTracker is in progress I'm disseminating the project results to allow a wider application of the FTK techniques. Both the ATLAS and CMS experiment are evaluating the Associative Memory technology for future tracking processors to be used for high-luminosity LHC (HL-LHC) upgrades. For the future this technology is moving from Level-2 application with typical events rate of 100kHz to Level-1 applications when events collected by the experiment need to be analyzed at rates up to 40MHz. Both ATLAS and CMS have shown great interest for use of the AM technology for the Level-1 track triggers that are in early design stages [8].
The associative memory processor for real-time pattern matching applications can be used for brain studies. The most convincing models that try to validate brain functioning hypothesis are extremely similar to the real time architectures we developed for HEP. The AM pattern matching function has demonstrated to be able to play a key role in high rate filtering/reduction tasks. The conjecture of [9]: "the brain works by dramatically reducing input information by selecting for higher-level processing and long-term storage only those input data that match a particular set of memorized patterns" matches well the Associative Memory algorithm. The use of the Associative Memory to verify this conjecture will be also part of a Marie Curie IAPP project starting in 2013. Furthermore, The Instituto de Plasmas e Fusion Nuclear (IPFN-IST) in Portugal recently manifested interest to study the use of Associative Memory technology in Plasma Tomography image reconstruction for the extraction of salient visual patterns for real-time control in nuclear fusion plasma experiments.
[1] A. Andreazza et al., The FastTrack Real Time Processor and Its Impact on Muon Isolation, Tau and b-Jet Online
Selections at ATLAS, IEEE Trans. Nucl. Sci. 59, 348. http://dx.doi.org/10.1109/TNS.2011.2179670
[2] "Fast Tracker Technical Design Report", CERN-LHCC-2013-007
[3] A. Annovi et al., A new "Variable Resolution Associative Memory" for High Energy Physics
https://cdsweb.cern.ch/record/1352152 doi:10.1109/ANIMMA.2011.6172856
[4] A. Annovi et al., Associative Memory Design for the FastTrack Processor (FTK) at ATLAS
https://cdsweb.cern.ch/record/1402465?ln=en IEEE 2011 Conference records, doi:10.1109/RTC.2010.5750451
[5] ATLAS Collaboration, Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC, Phys.Lett. B716 (2012) 1-29, doi:10.1016/j.physletb.2012.08.020
[6] ATLAS Collaboration, Measurements of Higgs boson production and couplings in diboson final states with the ATLAS detector at the LHC. Phys. Lett. B 726 (2013), pp. 88-119
[7] ATLAS Collaboration, Evidence for the spin-0 nature of the Higgs boson using ATLAS data. Phys. Lett. B 726 (2013), pp. 120-144
[8] A. Annovi et al., Associative memory for L1 track triggering in LHC environment, Real Time Conference (RT), 2012 18th IEEE-NPSS, 10.1109/RTC.2012.6418193
[9] M. M. Del Viva, G. Punzi, D. Benedetti, "Information and Perception of Meaningful Patterns" PLoS ONE 8(7) (2013) doi: 10.1371/journal.pone.0069154
