TEACHING IN THE CLOUD MICROELECTRONICS UBIQUITOUS LAB (MULAB)

CAD laboratory students activity is mandatory for microelectronics teaching. This, applied in the deep-submicron era, creates new challenges to couple software management simplicity to user friendliness inside lab sessions, which requires the use of complex tools and concepts. In this paper, a new approach to microelectronics CAD deployment is presented, based on virtualization capabilities of new servers hardware and software technology. A test case, realized at Politecnico di Torino, degree of Electronic Engineering, is presented, with real world results on resource consumption and user satisfactio

Feedbacks in QCA: a Quantitative Approach

In the post-CMOS scenario a primary role is played by the quantum-dot cellular automata (QCA) technology. Irrespective of the specific implementation principle (e.g., either molecular, or magnetic or semiconductive in the current scenario) the intrinsic deep-level pipelined behavior is the dominant issue. It has important consequences on circuit design and performance, especially in the presence of feedbacks in sequential circuits. Though partially already addressed in literature, these consequences still must be fully understood and solutions thoroughly approached to allow this technology any further advancement. This paper conducts an exhaustive analysis of the effects and the consequences derived by the presence of loops in QCA circuits. For each problem arisen, a solution is presented. The analysis is performed using as a test architecture, a complex systolic array circuit for biosequences analysis (Smith–Waterman algorithm), which represents one of the most promising application for QCA technology. The circuit is based on nanomagnetic logic as QCA implementation, is designed down to the layout level considering technological constraints and experimentally validated structures, counts up to approximately 2.3 milion nanomagnets, and is described and simulated with HDL language using as a testbench realistic protein alignment sequences. The results here presented constitute a fundamental advancement in the emerging technologies field since: 1) they are based on a quantitative approach relying on a realistic and complex circuit involving a large variety of QCA blocks; 2) they strictly are reckoned starting from current technological limits without relying on unrealistic assumptions; 3) they provide general rules to design complex sequential circuits with intrinsically pipelined technologies, like QCA; and 4) they prove with a real application benchmark how to maximize the circuits performance

Biosequences analysis on NanoMagnet Logic

In the last decade Quantum dot Cellular Automata technology has been one of the most studied among the emerging technologies. The magnetic implementation, NanoMagnet Logic (NML), is particularly interesting as an alternative solutions to CMOS technology. The main advantages of NML circuits resides in the possibility to mix logic and memory in the same device, the expected low power consumption and the remarkable tolerance to heat and radiations. NML and QCA circuits behavior is different w.r.t. their CMOS counterparts. Consequently architecture organization must be tailored to their characteristics, and it is important to identify which applications are best suited for this technology. Our contribution reported in this paper represents a considerable step-forward in this direction. We present an optimized implementation on NML technology of an hardware accelerator for biosequences analysis. The architecture leverages the systolic array structure, which is the best organization for this technology due to the regularity of the layout. The circuit is described using a VHDL model, simulated to verify the correct functionality from the application point of view, and performance are evaluated, both in terms of speed and power consumption. Results pinpoints that NML technology with the appropriate clock solution can reach a considerable reduction in power consumption over CMOS. This analysis highlights quantitatively, and not only qualitatively, that NML logic is perfectly suited for Massively Parallel Data Analysis applications

Design of Pyrrole-Based Gate-Controlled Molecular Junctions Optimized for Single-Molecule Aflatoxin B1 Detection

Food contamination by aflatoxins is an urgent global issue due to its high level of toxicity and the difficulties in limiting the diffusion. Unfortunately, current detection techniques, which mainly use biosensing, prevent the pervasive monitoring of aflatoxins throughout the agri-food chain. In this work, we investigate, through ab initio atomistic calculations, a pyrrole-based Molecular Field Effect Transistor (MolFET) as a single-molecule sensor for the amperometric detection of aflatoxins. In particular, we theoretically explain the gate-tuned current modulation from a chemical–physical perspective, and we support our insights through simulations. In addition, this work demonstrates that, for the case under consideration, the use of a suitable gate voltage permits a considerable enhancement in the sensor performance. The gating effect raises the current modulation due to aflatoxin from 100% to more than 103÷104 %. In particular, the current is diminished by two orders of magnitude from the μA range to the nA range due to the presence of aflatoxin B1. Our work motivates future research efforts in miniaturized FET electrical detection for future pervasive electrical measurement of aflatoxins

Biosequences analysis on NanoMagnet Logic

In the last decade Quantum dot Cellular Automata technology has been one of the most studied among the emerging technologies. The magnetic implementation, NanoMagnet Logic (NML), is particularly interesting as an alternative solutions to CMOS technology. The main advantages of NML circuits resides in the possibility to mix logic and memory in the same device, the expected low power consumption and the remarkable tolerance to heat and radiations. NML and QCA circuits behavior is different w.r.t. their CMOS counterparts. Consequently architecture organization must be tailored to their characteristics, and it is important to identify which applications are best suited for this technology. Our contribution reported in this paper represents a considerable step-forward in this direction. We present an optimized implementation on NML technology of an hardware accelerator for biosequences analysis. The architecture leverages the systolic array structure, which is the best organization for this technology due to the regularity of the layout. The circuit is described using a VHDL model, simulated to verify the correct functionality from the application point of view, and performance are evaluated, both in terms of speed and power consumption. Results pinpoints that NML technology with the appropriate clock solution can reach a considerable reduction in power consumption over CMOS. This analysis highlights quantitatively, and not only qualitatively, that NML logic is perfectly suited for Massively Parallel Data Analysis applications

Hybrid-SIMD: a Modular and Reconfigurable approach to Beyond von Neumann Computing

The increasing complexity of real-life applications demands constant improvements of microprocessor systems. One of the most frequently adopted microprocessor design scheme is the von Neumann architecture. Central Processing Unit (CPU performs computations and communicates with memory in a constant exchange of information. This unceasing motion of data between these two components became a significant performance bottleneck. A lot of power, energy, and computational time are wasted in this communication. With Beyond von Neumann Computing (BvNC paradigms, calculations are performed inside or very close to a memory array. BvNC approaches are proposed in the literature, mainly based on modifications of existing memories, enabling simple computations. Others exploit emerging technologies to both store and compute data, using analog operations. In this work we follow a different approach, where computational units are placed close to memory cells, improving versatility and performance. We propose a Hybrid-SIMD architecture made of memory and computing elements in an interleaved structure. Hybrid-SIMD can be used both as a low density memory and as SIMD accelerator. We insert our design in a classical von Neumann system based on a RISC-V processor, and we estimate its impact, demonstrating its capability to improve speed reducing at the same time energy consumption