Search

The amazing development of transistor technology has been the main driving force behind modern electronics. Over time, this process has slowed down introducing performance bottlenecks in data-intensive applications. A main cause is the classical von Neumann architecture, which entails constant data exchanges between processing units and data memory, wasting time and power. As a possible alternative, the Beyond von Neumann approach is now rapidly spreading. Although architectures following this paradigm vary a lot in layout and functioning, they all share the same principle: bringing computing elements as near as possible to memory while inserting customized processing elements, able to elaborate more data. Thus, power and time are saved through parallel execution and usage of processing components with local memory elements, optimized for running data-intensive algorithms. Here, a new memory-mapped co-processor (MeMPA) is presented to boost systems performance. MeMPA relies on a programmable matrix of fully interconnected processing blocks, each provided with memory elements, following the Multiple-Single Instruction Multiple Data model. Specifically, MeMPA can perform up to three different instructions, each on different data blocks, concurrently. Hence, MeMPA efficiently processes data-crunching algorithms, achieving energy and time savings up to 81.2% and 68.9%, respectively, compared with a RISC-V-based system. [ABSTRACT FROM AUTHOR]

Chitosan is a polysaccharide obtained by deacetylation of chitin, and it is involved in defence mechanisms of plants toward diseases. In the present work, V. vinifera L. cv. Ortrugo, grafted on 420A rootstock was grown in pot and treated, at veraison, by 0.03% chitosan solution at cluster level. Just before the treatment (T0) and 24 hours (T1), 48 hours (T2), 72 hours (T3) and 10 days (T4) later, the concentration of stilbenic compounds was detected, and at T1 proteomics and metabolomics analyses were done. Proteomics relies on the analysis of the complete set of proteins existing in a given substrate, while metabolomics relies on the analyses of the complete set of metabolites in a given substrate. The treatment improved the stilbene concentration over the control at T1. Proteomic analysis showed that superoxide dismutase (SOD) and phenylalanine ammonia-lyase (PAL) were overexpressed in the treated grapes. SOD is known to be an enzyme active against reactive oxygen species (ROS) while PAL is a key enzyme in the phenylpropanoids pathway. Metabolomics analysis highlighted the positive role of the treatment in improving the triperpenoid concentration (betulin, erythrodiol, uvaol, oleanolate); these compounds are known to be effective against microbes, insects and fungi.

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. [ABSTRACT FROM AUTHOR]

Classical simulation of Noisy Intermediate Scale Quantum computers is a crucial task for testing the expected performance of real hardware. The standard approach, based on solving Schrödinger and Lindblad equations, is demanding when scaling the number of qubits in terms of both execution time and memory. In this article, attempts in defining compact models for the simulation of quantum hardware are proposed, ensuring results close to those obtained with standard formalism. Molecular Nuclear Magnetic Resonance quantum hardware is the target technology, where three non-ideality phenomena—common to other quantum technologies—are taken into account: decoherence, off-resonance qubit evolution, and undesired qubit-qubit residual interaction. A model for each non-ideality phenomenon is embedded into a MATLAB simulation infrastructure of noisy quantum computers. The accuracy of the models is tested on a benchmark of quantum circuits, in the expected operating ranges of quantum hardware. The corresponding outcomes are compared with those obtained via numeric integration of the Schrödinger equation and the Qiskit’s QASMSimulator. The achieved results give evidence that this work is a step forward towards the definition of compact models able to provide fast results close to those obtained with the traditional physical simulation strategies, thus paving the way for their integration into a classical simulator of quantum computers. [ABSTRACT FROM AUTHOR]

Nanomagnet logic (NML) is one of the most novel solutions studied as complementary technology to CMOS transistors. Information propagation involves only a change in spin orientation, no charge movement is present. Since the basic element is a nanomagnet, NML circuits have no stand-by power consumption and the ability to mix logic and memory in the same device. While CMOS is a multilayer technology, until now NML is confined to one single physical layer. The consequence is that circuit area grows exponentially due to interconnections overhead. In this paper, we present an innovative solution that drastically reduces the area wasted for interconnection wires relying on the properties of domain walls (DWs). We mix DWs and NML technologies in a unique DW logic (DWL) solution that exploits the advantages of both technologies. The proposed solution is technologically compatible with up-to-date fabrication processes. All the results here presented for the NML logic blocks and the DWs interconnections and their combination are obtained through rigorous micromagnetic simulations. Moreover, we implemented as a case study an high performance adder (Pentium 4 adder) and evaluated its features with increasing parallelism and compared with the simple NML implementation in order to explore the potential of DWL technology at circuit and architectural level. The reduction in circuit area corresponds to a notable reduction in both the latency and power consumption. The improvements in NML technology are shown by both the remarkable performance improvement and new possibilities offered by this novel solution. [ABSTRACT FROM AUTHOR]

Emerging technologies are gaining an increasing attention due to the slowdown of CMOS development. NanoMagnet Logic (NML), among emerging technologies, increases the potentials for developing fully magnetic circuits. Using a magnet as a building block for logic circuits has the advantage to merge logic and memory in the same device. Moreover, circuits have low dynamic and no stand-by power consumption. Even though demonstrations exist for small circuits, the experimental feasibility of complex NML circuits still represents a critical point for this technology. In this paper, we outline the possibility to design NML circuits based on the technological structure of magnetic RAMs (MRAMs). NML circuits based on MRAMs rely on a well-developed technology that provides a natural interface with CMOS world. To study this new NML implementation a novel tool, NANOcom, was developed to easily design complex circuits. Simulations were then performed using an high-level behavioral model described using VHDL language. Two types of circuit layouts, based on different technological constraints, are investigated. To evaluate the performance of this new NML implementation, a 4-bit Galois multiplier is used as a testbench. The Galois multiplier is the basic block of cryptographic circuits, an ideal target for this technology. Results obtained are encouraging and can unlock interesting options for the future development of NML technology. [ABSTRACT FROM PUBLISHER]

In the post-CMOS scenario, field coupled nanotechnologies represent an innovative and interesting new direction for electronic nanocomputing. Among these technologies, nanomagnet logic (NML) makes it possible to finally embed logic and memory in the same device. To fully analyze the potential of NML circuits, design tools that mimic the CMOS design-flow should be used for circuit design. We present, in this paper, the latest and improved version of Torino Politecnico Nanotechnology (ToPoliNano), our design and simulation framework for field coupled nanotechnologies. ToPoliNano emulates the top-down design process of CMOS technology. Circuits are described with a VHSIC hardware description language netlist and layout is then automatically generated considering in-plane NML (iNML) technology. The resulting circuits can be simulated and performance can be analyzed. In this paper, we describe several enhancements to the tool itself, like a circuit editor for custom design of field coupled nanodevices, improved algorithms for netlist optimization and new algorithms for the place and route of iNML circuits. We have validated and analyzed the tool by using extensive metrics, both by using standard circuits and ISCAS’85 benchmarks. This contribution highlights the improvements of ToPoliNano, which is now a innovative and complete tool for the development of iNML technology. [ABSTRACT FROM AUTHOR]

NanoMagnet logic (NML) is among the emerging technologies that might replace CMOS in the next decades. According to its physical characteristics, to better exploit the potential of this technology—and of other similar ones—the use of parallel architectures with regular layout that avoid long interconnection signals is advised. Systolic arrays (SAs) are among these architectures, being composed of a grid of equal processing elements that are locally interconnected. However, they are usually implemented to execute only a small set of algorithms, and for this reason, throughout the years, they have not been an appealing solution for CMOS. To seriously analyze the potentials of NML, complex architectures must be conceived, and their physical implementation explored considering realistic technological constraints. With the increasing complexity of NML circuits, two issues, then, are noticed: 1) the need for a regular structure arises, that at the same time helps to reduce the intrinsic pipelining nature of NML and can be configured to be used for several applications without developing a dedicated design for each algorithm and 2) the capability to synthesize, place and route NML circuits is fundamental to demonstrate the feasibility of the architecture in two important conditions: efficiently managing the complexity of the design and sticking to the characteristics that are technologically feasible at the time of writing. In this paper, we address these issues presenting a new reconfigurable SA that can be programmed to execute different algorithms, and we provide two examples to show its working principle. Moreover, the array is synthesized and simulated with the aid of the first real tool for nanotechnology circuits that we have conceived, Torino Politecnico Nanotechnology tool. The joint contribution at both the architectural and physical design levels gives a relevant step forward to the state of the art in the demonstration of this emerging technology potential. [ABSTRACT FROM AUTHOR]

With the predicted end of CMOS scaling process, researchers started to study several alternative technologies. Among them NanoMagnet Logic (NML) offers advantages complementary to MOS transistors especially for its magnetic nature. Its intrinsic memory capability makes it suitable for zero stand-by power and logic-in-memory applications. NML requires a clock system that, if based on a magnetic field, highly increases the circuit dynamic power consumption. We have recently proposed a solution based on the magnetoelastic effect (ME-NML) [1] and on currently available fabrication processes, which drastically reduces dynamic power consumption. However, many questions still remain unanswered. Which kind of applications are best suited for this technology? How can we effectively design, analyze, and compare ME-NML circuits? Does it really offer advantages over state-of-the-art CMOS transistors? In this paper, we provide answers to all these questions and the results prove that this technology offers indeed extremely good performance. We have designed a Galois field multiplier with a systolic array structure to reduce interconnection overhead. We developed a new RTL model that allows us to easily describe and simulate circuits of any complexity, evaluating at the same time the performance and keeping into account technology constraints. We approach for the first time in the NML scenario the design of ME-NML circuits adopting the standard-cell method used in standard technologies and fulfill the design down to the physical level. The same circuit is designed also with NML technology based on magnetic fields and with a 28 nm low power CMOS bulk technology for comparison. The CMOS circuit is obtained through physical place&route with a commercial tool, providing, therefore, the most accurate comparison ever presented in literature. Power analysis shows that ME-NML circuits have a considerable advantage over both NML and state-of-the-art CMOS bulk technology. As a further by-product results clearly highlight which kind of architectures can better exploit the true potential of NML technology. [ABSTRACT FROM PUBLISHER]

Among emerging technologies nanomagnet logic (NML) has recently received particular attention. NML uses magnets as constitutive elements, and this leads to logic circuits where there is no need of an external power supply to maintain their logic state. As a consequence, a system with intrinsic memory and zero stand-by power consumption can be envisioned. Despite the interesting nature of NML, a fundamental open problem still calls for a solution that could really boost the NML technology: the clock system. It constrains the layout of circuits and leads to a potentially high dynamic power consumption if not carefully conceived. The first clock system developed was based on the generation of a magnetic field through an on-chip current. After that other types of NML, based on several different types of clock systems, were proposed to improve clocking. We present here our proposal for a new clock delivery method. We named this system “virtual clock.” It offers several important advantages over previous solutions. First, it notably simplifies the clock generation network, reducing the complexity of the fabrication process. It improves the efficiency of circuits layout, substantially reducing interconnections overhead and boosting the reliability of the majority voter. It enables the fabrication of in-plane NML circuits with two layers, while they were confined to one single layer up to now. Finally, it allows to globally reduce dynamic power consumption by considerably shrinking circuits area. Overall the “virtual clock” system that we propose represents an important step forward in the development of the NML technology. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

In past years the most common way to improve computers performance was to increase the clock frequency. In recent years this approach suffered the limits of technology scaling, therefore computers architectures are shifting toward the direction of parallel computing to further improve circuits performance. Not only GPU based architectures are spreading in consideration, but also Systolic Arrays are particularly suited for certain classes of algorithms. An important point in favor of Systolic Arrays is that, due to the regularity of their circuit layout, they are appealing when applied to many emerging and very promising technologies, like Quantum-dot Cellular Automata and nanoarrays based on Silicon NanoWire or on Carbon nanotube Field Effect Transistors. In this work we present a systematic method to improve Systolic Arrays performance exploiting Pipelining and Input Data Interleaving. We tackle the problem from a theoretical point of view first, and then we apply it to both CMOS technology and emerging technologies. On CMOS we demonstrate that it is possible to vastly improve the overall throughput of the circuit. By applying this technique to emerging technologies we show that it is possible to overcome some of their limitations greatly improving the throughput, making a considerable step forward toward the post-CMOS era. [ABSTRACT FROM AUTHOR]