Tecniche di progettazione tollerante alle variazioni per circuiti digitali in tecnologie nanometriche

The digital electronic market development is founded on the continuous reduction of the transistors size, to reduce area, power, cost and increase the computational performance of integrated circuits. This trend, known as technology scaling, is approaching the nanometer size. The lithographic process in the manufacturing stage is increasing its uncertainty with the scaling down of the transistors size, resulting in a larger parameter variation in future technology generations. Furthermore, the exponential relationship between the leakage current and the threshold voltage, is limiting the threshold and supply voltages scaling, increasing the power density and creating local thermal issues, such as hot spots, thermal runaway and thermal cycles. In addiction, the introduction of new materials and the smaller devices dimension are reducing transistors robustness, that combined with high temperature and frequently thermal cycles, are speeding up wear out processes. Those effects are no longer addressable only at the process level. Consequently the deep sub-micron devices will require solutions which will imply several design levels, as system and logic, and new approaches called Design For Manufacturability (DFM) and Design For Reliability. The purpose of the above approaches is to bring in the early design stages the awareness of the device reliability and manufacturability, in order to introduce logic and system able to cope with the yield and reliability loss. The ITRS roadmap suggests the following research steps to integrate the design for manufacturability and reliability in the standard CAD automated design flow: i) The implementation of new analysis algorithms able to predict the system thermal behavior with the impact to the power and speed performances. ii) High level wear out models able to predict the mean time to failure of the system (MTTF). iii) Statistical performance analysis able to predict the impact of the process variation, both random and systematic. The new analysis tools have to be developed beside new logic and system strategies to cope with the future challenges, as for instance: i) Thermal management strategy that increase the reliability and life time of the devices acting to some tunable parameter,such as supply voltage or body bias. ii) Error detection logic able to interact with compensation techniques as Adaptive Supply Voltage ASV, Adaptive Body Bias ABB and error recovering, in order to increase yield and reliability. iii) architectures that are fundamentally resistant to variability, including locally asynchronous designs, redundancy, and error correcting signal encodings (ECC). The literature already features works addressing the prediction of the MTTF, papers focusing on thermal management in the general purpose chip, and publications on statistical performance analysis. In my Phd research activity, I investigated the need for thermal management in future embedded low-power Network On Chip (NoC) devices.I developed a thermal analysis library, that has been integrated in a NoC cycle accurate simulator and in a FPGA based NoC simulator. The results have shown that an accurate layout distribution can avoid the onset of hot-spot in a NoC chip. Furthermore the application of thermal management can reduce temperature and number of thermal cycles, increasing the systemreliability. Therefore the thesis advocates the need to integrate a thermal analysis in the first design stages for embedded NoC design. Later on, I focused my research in the development of statistical process variation analysis tool that is able to address both random and systematic variations. The tool was used to analyze the impact of self-timed asynchronous logic stages in an embedded microprocessor. As results we confirmed the capability of self-timed logic to increase the manufacturability and reliability. Furthermore we used the tool to investigate the suitability of low-swing techniques in the NoC system communication under process variations. In this case We discovered the superior robustness to systematic process variation of low-swing links, which shows a good response to compensation technique as ASV and ABB. Hence low-swing is a good alternative to the standard CMOS communication for power, speed, reliability and manufacturability. In summary my work proves the advantage of integrating a statistical process variation analysis tool in the first stages of the design flow.

Relationship between aetiology and left ventricular systolic dysfunction in hypertrophic cardiomyopathy

Background: Hypertrophic cardiomyopathy (HCM) is a common cardiac disease caused by a range of genetic and acquired disorders. The most common cause is genetic variation in sarcomeric proteins genes. Current ESC guidelines suggest that particular clinical features (‘red flags’) assist in differential diagnosis. Aims: To test the hypothesis that left ventricular (LV) systolic dysfunction in the presence of increased wall thickness is an age-specific ‘red flag’ for aetiological diagnosis and to determine long-term outcomes in adult patients with various types of HCM. Methods: A cohort of 1697 adult patients with HCM followed at two European referral centres were studied. Aetiological diagnosis was based on clinical examination, cardiac imaging and targeted genetic and biochemical testing. Main outcomes were: all-cause mortality or heart transplantation (HTx) and heart failure (HF) related-death. All-cause mortality included sudden cardiac death or equivalents, HF and stroke-related death and non-cardiovascular death. Results: Prevalence of different aetiologies was as follows: sarcomeric HCM 1288 (76%); AL amyloidosis 115 (7%), hereditary TTR amyloidosis 86 (5%), Anderson-Fabry disease 85 (5%), wild-type TTR amyloidosis 48 (3%), Noonan syndrome 15 (0.9%), mitochondrial disease 23 (1%), Friedreich’s ataxia 11 (0.6%), glycogen storage disease 16 (0.9%), LEOPARD syndrome 7 (0.4%), FHL1 2 (0.1%) and CPT II deficiency 1 (0.1%). Systolic dysfunction at first evaluation was significantly more frequent in phenocopies than sarcomeric HCM [105/409 (26%) versus 40/1288 (3%), (p<0.0001)]. All-cause mortality/HTx and HF-related death were higher in phenocopies compared to sarcomeric HCM (p<0.001, respectively). When considering specific aetiologies, all-cause mortality and HF-related death were higher in cardiac amyloidosis (p<0.001, respectively). Conclusion: Systolic dysfunction at first evaluation is more common in phenocopies compared to sarcomeric HCM representing an age-specific ‘red flag’ for differential diagnosis. Long-term prognosis was more severe in phenocopies compared to sarcomeric HCM and when comparing specific aetiologies, cardiac amyloidosis showed the worse outcomes.