Device for Data Storage and Processing, and Method Thereof

A device for data storage and processing includes: at least two input racetrack elements having a plurality of first magnetization regions; at least one output racetrack element having a plurality of second magnetization regions, wherein a magnetization vector is adapted to switch from a first direction to the opposite one, or vice versa, by way of a magnetic field of reduced intensity compared with a magnetic field required to produce a similar switching of a magnetization vector of the first magnetization region, wherein the input racetrack elements and output racetrack element are configured in such a way as to constitute at least one elementary logic gate, wherein at least two of the first magnetization regions are magnetically coupled to at least one of the second magnetization regions

Custom Memory Design for Logic-in-Memory: Drawbacks and Improvements over Conventional Memories

The speed of modern digital systems is severely limited by memory latency (the “Memory Wall” problem). Data exchange between Logic and Memory is also responsible for a large part of the system energy consumption. Logic-in-Memory (LiM) represents an attractive solution to this problem. By performing part of the computations directly inside the memory the system speed can be improved while reducing its energy consumption. LiM solutions that offer the major boost in performance are based on the modification of the memory cell. However, what is the cost of such modifications? How do these impact the memory array performance? In this work, this question is addressed by analysing a LiM memory array implementing an algorithm for the maximum/minimum value computation. The memory array is designed at physical level using the FreePDK 45nm CMOS process, with three memory cell variants, and its performance is compared to SRAM and CAM memories. Results highlight that read and write operations performance is worsened but in-memory operations result to be very efficient: a 55.26% reduction in the energy-delay product is measured for the AND operation with respect to the SRAM read one. Therefore, the LiM approach represents a very promising solution for low-density and high-performance memories

Parallel Computation in the Racetrack Memory

Racetrack memories are promising candidates for next-generation solid-state storage devices. Various racetrack memories have been proposed in the literature, skyrmion based or domain wall based. However, none of them show integrated computing capabilities. Here, we introduce a new domain wall based racetrack concept that can operate both as a memory and as a computing device. The computation is defined by changing locally the anisotropy of the film. Stray fields from nearby cells are exploited to implement reconfigurable logic gates. We demonstrate that the racetrack array can operate in parallel in every cell. This is achieved by an external out-of-plane Zeeman field applied to the array. As proof-of-principle, we verified the single computing cell and multiple connected cells operating in parallel by micromagnetic simulations. Logic NAND/NOR is implemented independently in every computing cell. This study provides the guidelines for the development and optimization of this family of logic gates

A Unified Approach for Performance Degradation Analysis from Transistor to Gate Level

In this paper, we present an extensive analysis of the performance degradation in MOSFET based circuits. The physical effects that we consider are the random dopant fluctuation (RDF), the oxide thickness fluctuation (OTF) and the Hot-carrier-Instability (HCI). The work that we propose is based on two main key points: First, the performance degradation is studied considering BULK, Silicon-On-Insulator (SOI) and Double Gate (DG) MOSFET technologies. The analysis considers technology nodes from 45nm to 11nm. For the HCI effect we consider also the time-dependent evolution of the parameters of the circuit. Second, the analysis is performed from transistor level to gate level. Models are used to evaluate the variation of transistors key parameters, and how these variation affects performance at gate level as well.The work here presented was obtained using TAMTAMS Web, an open and publicly available framework for analysis of circuits based on transistors. The use of TAMTAMS Web greatly increases the value of this work, given that the analysis can be easily extended and improved in both complexity and depth

Virtual Clocking for NanoMagnet Logic

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

P2Y1 receptor switches to neurons from glia in juvenile versus neonatal rat cerebellar cortex

<p>Abstract</p> <p>Background</p> <p>In the CNS, several P2 receptors for extracellular nucleotides are identified on neurons and glial cells to participate to neuron-neuron, glia-glia and glia-neuron communication.</p> <p>Results</p> <p>In this work, we describe the cellular and subcellular presence of metabotropic P2Y₁receptor in rat cerebellum at two distinct developmental ages, by means of immunofluorescence-confocal and electron microscopy as well as western blotting and direct membrane separation techniques. At postnatal day 21, we find that P2Y₁receptor in addition to Purkinje neurons, is abundant on neuronal specializations identified as noradrenergic by anatomical, morphological and biochemical features. P2Y₁receptor immunoreactivity colocalizes with dopamine β-hydroxylase, tyrosine hydroxylase, neurofilament light chain, synaptophysin and flotillin, but not with glial fibrillary acidic protein for astrocytes. P2Y₁receptor is found enriched in membrane microdomains such as lipid rafts, in cerebellar synaptic vesicles, and is moreover visualized on synaptic varicosities by electron microscopy analysis. When examined at postnatal day 7, P2Y₁receptor immunoreactivity is instead predominantly expressed only on Bergmann and astroglial cells, as shown by colocalization with glial fibrillary acidic protein rather then neuronal markers. At this age, we moreover identify that P2Y₁receptor-positive Bergmann fibers wrap up doublecortin-positive granule cells stretching along them, while migrating through the cerebellar layers.</p> <p>Conclusion</p> <p>Membrane components including purinergic receptors are already known to mediate cellular contact and aggregation in platelets. Our results suggesting a potential role for P2Y₁protein in cell junction/communication and development, are totally innovative for the CNS.</p

Skyrmion Logic-In-Memory Architecture for Maximum/Minimum Search

In modern computing systems there is the need to utilize a large amount of data in maintaining high efficiency. Limited memory bandwidth, coupled with the performance gap between memory and logic, impacts heavily on algorithms performance, increasing the overall time and energy required for computation. A possible approach to overcome such limitations is Logic-In-Memory (LIM). In this paper, we propose a LIM architecture based on a non-volatile skyrmion-based recetrack memory. The architecture can be used as a memory or can perform advanced logic functions on the stored data, for example searching for the maximum/minimum number. The circuit has been designed and validated using physical simulations for the memory array together with digital design tools for the control logic. The results highlight the small area of the proposed architecture and its good energy efficiency compared with a reference CMOS implementation

RISC-Vlim, a RISC-V Framework for Logic-in-Memory Architectures

Most modern CPU architectures are based on the von Neumann principle, where memory and processing units are separate entities. Although processing unit performance has improved over the years, memory capacity has not followed the same trend, creating a performance gap between them. This problem is known as the "memory wall" and severely limits the performance of a microprocessor. One of the most promising solutions is the "logic-in-memory" approach. It consists of merging memory and logic units, enabling data to be processed directly inside the memory itself. Here we propose an RISC-V framework that supports logic-in-memory operations. We substitute data memory with a circuit capable of storing data and of performing in-memory computation. The framework is based on a standard memory interface, so different logic-in-memory architectures can be inserted inside the microprocessor, based both on CMOS and emerging technologies. The main advantage of this framework is the possibility of comparing the performance of different logic-in-memory solutions on code execution. We demonstrate the effectiveness of the framework using a CMOS volatile memory and a memory based on a new emerging technology, racetrack logic. The results demonstrate an improvement in algorithm execution speed and a reduction in energy consumption

NS-GAAFET Compact Modeling: Technological Challenges in Sub-3-nm Circuit Performance

NanoSheet-Gate-All-Around-FETs (NS-GAAFETs) are commonly recognized as the future technology to push the digital node scaling into the sub-3 nm range. NS-GAAFETs are expected to replace FinFETs in a few years, as they provide highly electrostatic gate control thanks to the GAA structure, with four sides of the NS channel entirely enveloped by the gate. At the same time, the NS rectangular cross-section is demonstrated to be effective in its driving strength thanks to its high saturation current, tunable through the NS width used as a design parameter. In this work, we develop a NS-GAAFET compact model and we use it to link peculiar single-device parameters to digital circuit performance. In particular, we use the well-known BSIM-CMG core solver for multigate transistors as a starting point and develop an ad hocresistive and capacitive network to model the NS-GAAFET geometrical and physical structure. Then, we employ the developed model to design and optimize a digital inverter and a five-stage ring oscillator, which we use as a performance benchmark for the NS-GAAFET technology. Through Cadence Virtuoso SPICE simulations, we investigate the digital NS-GAAFET performance for both high-performance and low-power nodes, according to the average future node present in the International Roadmap for Devices and Systems. We focus our analysis on the main different technological parameters with regard to FinFET, i.e., the inner and outer spacers. Our results highlight that in future technological nodes, the choice of alternative low-K dielectric materials for the NS spacers will assume increasing importance, being as relevant, or even more relevant, than photolithographic alignment and resolution at the sub-nm scale