Development of FPGA-based High-Speed serial links for High Energy Physics Experiments

High Energy Physics (HEP) experiments generate high volumes of data which need to be transferred over long distance. Then, for data read out, reliable and high-speed links are necessary. Over the years, due to their extreme high bandwidth, serial links (especially optical) have been preferred over the parallel ones. So that, now, high-speed serial links are commonly used in Trigger and Data Acquisition (TDAQ) systems of HEP experiments, not only for data transfer, but also for the distribution of trigger and control systems. Examples of their wide use can be found at CERN, where each of the four big experiments mounted on the Large Hadron Collider (LHC) uses a huge amount of serial links in its read out system. Again at LHC, the Timing, Trigger and Control system (TTC), which broadcasts the timing signals, from the LHC machine to the experiments, uses optical serial link to distribute signals over kilometers of distance (diameter of LHC is 27 Km). Also for upgrades of LHC, physical layer components and protocol chips (ASIC) have been designed and are now under development: the Versatile Link and the GBT protocol (and ASICs) whose peculiarity relies in their radiation hardness. This PhD project is intended to respond to the requests of HEP experiments, developing: - a high-speed self-adapting serial link, which can be easily used in different application fields; - the serial interface of a read out board in the end-cap region of ATLAS Experiment at LHC; - the interface board for the barrel read out system of the ATLAS Experiments. Both the two last projects have required the development of fixed latency, high-speed serial links. In order to take advantage of flexibility, re-programmability and system integration of SRAM-based Field Programmable Gate Array devices (FPGAs), their serializer-deserializer (SERDES) embedded modules have been chosen for the development of the links. However, as a drawback, FPGA embedded SERDESes are typically designed for applications that do not require a deterministic latenc. Then, an accurate study of their architecture has been necessary, in order to find a configuration and a clocking scheme to guarantee a deterministic transmission delay in data transfers. The frequency agile, auto-adaptive serial link is capable to analyze the incoming data stream, by scanning the Unit Interval, and to find the highest transmission line rate, according to a given tolerated Bit Error Ratio (BER). It uses a new feature (RX eye margin analysis) of the RX side of the Xilinx 7 series FPGAs high-speed transceivers (GTX/GTH), in order to measure and display the receiver eye margin after the equalizer. When the new eye scan functionality is running, an additional sampler is activated in the GTX. It acquires a new sample (Offset Sample), with programmable (horizontal and vertical) offsets from the data sample point (Data Sample) used in standard operation. An eye scan measurement run is performed by acquiring a large number of Data Samples (which can range from tens of thousands to 1014 or more) and by counting the number of times the Offset Sample has a different value with respect to the Data Sample; the latter number is often called Error Count. The BER at a specific vertical and horizontal offset is given by the ratio between the Error Count and the Sample Count. By repeating the eye scan measurement for each horizontal and vertical offset in the Unit Interval (or in a part of the U.I.) a 2-D BER map can be produced which is usually called Statistical Eye. The auto-adaptive derail ink is designed around an FPGA-embedded microprocessor, which drives the programmable ports of the GTX, in order to perform a 2-D eye-scan, and takes care of the reconfiguration of the GTX parameters, in order to fully benefit from the available link bandwidth. Xilinx provides a standalone tool that allows performing the Eye Scan Analysis on the receiver side of the GTX/GTH transceiver, using the MicroBlaze Micro Controller System macro; the toolkit also includes the Eye Scan algorithm (providing the C code). Moreover, Xilinx supplies the hardware sources files for the implementation of a link based on the XAUI protocol, in which the GTXs are arranged in a loopback configuration. The original contribution of this work consists in the build-up, design and optimization of a full architecture, on top of the basic Xilinx tool, which: - drives the programmable ports of the GTX in order to modify the line rate of the link; - runs consecutive eye scans for various line rate; - analyses the results of the different scans, in order to find the maximum line rate sustainable by the link; - manages the synchronization between the transmitter and the receiver of the link, that will be needed at each line rate change. The application can be deployed as a monitoring tool in HEP experiments, in order to remotely monitor a transmission system or detect issues in the serial link physical layer. An application example could be some of the many experiments at Large Hadron Collider (LHC) at CERN, which have been intensively using different serial links, both for transmission of TTC signals and for trigger and data readout. Besides, this solution could be easily adapted in wide, different frameworks, as it can be used on top of any user’s existing link, as it has no specific requirement about link specification or protocol. The other two serial interface developed in this project are in the framework of the ATLAS experiment. ATLAS is one of the four detectors installed on the LHC proton-proton collider built at CERN. It was designed to collide two opposing particle beams at an energy of 14 TeV and to reach a luminosity of 1034 cm-2/s. In order to reach the design parameters, the LHC system will be upgraded in several phases. In order to take advantage of the improved LHC operation, the ATLAS detector must be upgraded following the same schedule as the LHC upgrade. The main focus of the Phase-I ATLAS upgrade (to be completed by 2018) is on the Level-1 trigger where upgrades are planned for both the muon and the calorimeter trigger systems. In particular, for the end-cap region of the muon spectrometer, the installation of a new set of precision tracking and trigger detectors was approved, called the ‘New Small Wheels’ (NSW). It will be instrumented with micro-mesh gaseous structure detectors (MM) and small-strip Thin Gap Chambers (sTGC). These detectors will solve two points of particular importance at high luminosity: high rate of fake high-pt level-1 muon triggers, and high L1 muon rate with the current momentum threshold. With the introduction of new detectors, new electronics need to be developed, in particular new trigger electronics for both the MM and sTGC. I was involved in the development of serial interface of the FPGA-based sTGC trigger board that uses information from the coarse sTGC readout pads. The sTGC pad trigger board receives serial information coming from 24 front-end chips at 4.8 Gb/s. On the board, data are deserialised, aligned and analyzed by the trigger algorithm. The trigger logic processes the data and choses two candidates at each Bunch Crossing. The result is then serialised and used for selective fine-grained strip readout. I developed the pad trigger board interface logic. The data format from the front-end chips has been agreed upon, and defines the requirements on the receiver and decoding logic. The number of output lines is 24 and the data are 8B/10B formatted. While the receiver uses the Xilinx Kintex-7 GTX transceivers, the output lines are driven by double data rate (DDR) shift registers at 640 Mb/s. A fixed latency in the sTGC trigger chain was guaranteed through the implementation and configuration of all serialisers and deserialisers. In order to test the project, I also developed a simple microprocessor-based protocol for accessing the board via terminal (rs232). A demonstrator board is now being developed. Another Phase-I Level-1 trigger upgrade consists of a new Muon to Central Trigger Processor Interface (MUCTPI). The MUCTPI receives muon candidate information from each of the muon detectors, selects muon candidates and sends them to the Central Trigger Processor (CTP). In the first runs of ATLAS, the L1 Barrel trigger candidate data were transferred to the MuCTPI via copper cables. In order to cope with the trigger upgrade, serial optical links are necessary. The optical links will provide a much higher bandwidth (up to 6.4 Gb/s) which will be used to transfer additional information from the sector logic modules, for example data for more than two muon candidates. They will also provide a lower transmission latency. I developed the interface board between the new MUCTPI and the Resistive Plate Chambers (RPC) muon trigger, using the Xilinx Artix-7 FPGA GTP transceivers. I took care of the study of feasibility of the new serial optical transmitter and the logic for the new data format. Also in this case, the fixed latency has been a requirement to be fulfilled

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients

Carriers of ADAMTS13 Rare Variants Are at High Risk of Life-Threatening COVID-19

Thrombosis of small and large vessels is reported as a key player in COVID-19 severity. However, host genetic determinants of this susceptibility are still unclear. Congenital Thrombotic Thrombocytopenic Purpura is a severe autosomal recessive disorder characterized by uncleaved ultra-large vWF and thrombotic microangiopathy, frequently triggered by infections. Carriers are reported to be asymptomatic. Exome analysis of about 3000 SARS-CoV-2 infected subjects of different severities, belonging to the GEN-COVID cohort, revealed the specific role of vWF cleaving enzyme ADAMTS13 (A disintegrin-like and metalloprotease with thrombospondin type 1 motif, 13). We report here that ultra-rare variants in a heterozygous state lead to a rare form of COVID-19 characterized by hyper-inflammation signs, which segregates in families as an autosomal dominant disorder conditioned by SARS-CoV-2 infection, sex, and age. This has clinical relevance due to the availability of drugs such as Caplacizumab, which inhibits vWF-platelet interaction, and Crizanlizumab, which, by inhibiting P-selectin binding to its ligands, prevents leukocyte recruitment and platelet aggregation at the site of vascular damage

Gain- and Loss-of-Function CFTR Alleles Are Associated with COVID-19 Clinical Outcomes

Carriers of single pathogenic variants of the CFTR (cystic fibrosis transmembrane conductance regulator) gene have a higher risk of severe COVID-19 and 14-day death. The machine learning post-Mendelian model pinpointed CFTR as a bidirectional modulator of COVID-19 outcomes. Here, we demonstrate that the rare complex allele [G576V;R668C] is associated with a milder disease via a gain-of-function mechanism. Conversely, CFTR ultra-rare alleles with reduced function are associated with disease severity either alone (dominant disorder) or with another hypomorphic allele in the second chromosome (recessive disorder) with a global residual CFTR activity between 50 to 91%. Furthermore, we characterized novel CFTR complex alleles, including [A238V;F508del], [R74W;D1270N;V201M], [I1027T;F508del], [I506V;D1168G], and simple alleles, including R347C, F1052V, Y625N, I328V, K68E, A309D, A252T, G542*, V562I, R1066H, I506V, I807M, which lead to a reduced CFTR function and thus, to more severe COVID-19. In conclusion, CFTR genetic analysis is an important tool in identifying patients at risk of severe COVID-19

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

A first update on mapping the human genetic architecture of COVID-19

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