|
ECRAM Electrochemical Synaptic Cell
Electrochemical Random-Access Memory (ECRAM) is a type of non-volatile memory (NVM) with multiple levels per cell (MLC) designed for deep learning analog acceleration. An ECRAM cell is a three-terminal device composed of a conductive channel, an insulating electrolyte, an ionic reservoir, and metal contacts. The resistance of the channel is modulated by ionic exchange at the interface between the channel and the electrolyte upon application of an electric field. The charge-transfer process allows both for state retention in the absence of applied power, and for programming of multiple distinct levels, both differentiating ECRAM operation from that of a field-effect transistor (FET). The write operation is deterministic and can result in symmetrical potentiation and depression, making ECRAM arrays attractive for acting as artificial synaptic weights in physical implementations of artificial neural networks (ANN). The technological challenges include open circuit potential (OC ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Non-volatile Memory
Non-volatile memory (NVM) or non-volatile storage is a type of computer memory that can retain stored information even after power is removed. In contrast, volatile memory needs constant power in order to retain data. Non-volatile memory typically refers to storage in semiconductor memory chips, which store data in floating-gate memory cells consisting of floating-gate MOSFETs ( metal–oxide–semiconductor field-effect transistors), including flash memory storage such as NAND flash and solid-state drives (SSD). Other examples of non-volatile memory include read-only memory (ROM), EPROM (erasable programmable ROM) and EEPROM (electrically erasable programmable ROM), ferroelectric RAM, most types of computer data storage devices (e.g. disk storage, hard disk drives, optical discs, floppy disks, and magnetic tape), and early computer storage methods such as punched tape and cards. Overview Non-volatile memory is typically used for the task of secondary storage ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Electrochromic Device
An electrochromic device (ECD) controls optical properties such as optical transmission, absorption, reflectance and/or emittance in a continual but reversible manner on application of voltage (electrochromism). This property enables an ECD to be used for applications like smart glass, electrochromic mirrors, and electrochromic display devices. History The history of electro-coloration goes back to 1704 when Diesbach discovered Prussian blue (hexacyanoferrate), which changes color from transparent to blue under oxidation of iron. In the 1930s, Kobosew and Nekrassow first noted electrochemical coloration in bulk tungsten oxide. While working at Balzers in Lichtenstein, T. Kraus provided a detailed description of the electrochemical coloration in a thin film of tungsten trioxide (WO3) on 30 July 1953. In 1969, S. K. Deb demonstrated electrochromic coloration in WO3 thin films. Deb observed electrochromic color by applying an electric field on the order of 104 Vcm−1 across WO3 thin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Nanosiemens
The siemens (symbol: S) is the unit of electric conductance, electric susceptance, and electric admittance in the International System of Units (SI). Conductance, susceptance, and admittance are the reciprocals of resistance, reactance, and impedance respectively; hence one siemens is redundantly equal to the reciprocal of one ohm () and is also referred to as the ''mho''. The 14th General Conference on Weights and Measures approved the addition of the siemens as a derived unit in 1971. The unit is named after Ernst Werner von Siemens. In English, the same word ''siemens'' is used both for the singular and plural. Like other SI units named after people, the symbol is capitalized but the name of the unit is not. For the siemens this is particularly important to distinguish it from the second, symbol (lower case) s. The related property, electrical conductivity, is measured in units of siemens per metre (S/m). Definition For an element conducting direct current, electrica ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Phase-change Memory
Phase-change memory (also known as PCM, PCME, PRAM, PCRAM, OUM (ovonic unified memory) and C-RAM or CRAM (chalcogenide RAM)) is a type of non-volatile random-access memory. PRAMs exploit the unique behaviour of chalcogenide glass. In PCM, heat produced by the passage of an electric current through a heating element generally made of titanium nitride is used to either quickly heat and quench the glass, making it amorphous, or to hold it in its crystallization temperature range for some time, thereby switching it to a crystalline state. PCM also has the ability to achieve a number of distinct intermediary states, thereby having the ability to hold multiple bits in a single cell, but the difficulties in programming cells in this way has prevented these capabilities from being implemented in other technologies (most notably flash memory) with the same capability. Recent research on PCM has been directed towards attempting to find viable material alternatives to the phase-change materia ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Resistive Random-access Memory
Resistive random-access memory (ReRAM or RRAM) is a type of non-volatile (NV) random-access (RAM) computer memory that works by changing the resistance across a dielectric solid-state material, often referred to as a memristor. ReRAM bears some similarities to conductive-bridging RAM (CBRAM) and phase-change memory (PCM). CBRAM involves one electrode providing ions that dissolve readily in an electrolyte material, while PCM involves generating sufficient Joule heating to effect amorphous-to-crystalline or crystalline-to-amorphous phase changes. By contrast, ReRAM involves generating defects in a thin oxide layer, known as oxygen vacancies (oxide bond locations where the oxygen has been removed), which can subsequently charge and drift under an electric field. The motion of oxygen ions and vacancies in the oxide would be analogous to the motion of electrons and holes in a semiconductor. Although ReRAM was initially seen as a replacement technology for flash memory, the cost an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Deep Neural Networks
Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. Deep-learning architectures such as deep neural networks, deep belief networks, deep reinforcement learning, recurrent neural networks, convolutional neural networks and Transformers have been applied to fields including computer vision, speech recognition, natural language processing, machine translation, bioinformatics, drug design, medical image analysis, climate science, material inspection and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance. Artificial neural networks (ANNs) were inspired by information processing and distributed communication nodes in biological systems. ANNs have various differences from biological brains. Specifically, artificial neu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ohm's Law
Ohm's law states that the current through a conductor between two points is directly proportional to the voltage across the two points. Introducing the constant of proportionality, the resistance, one arrives at the usual mathematical equation that describes this relationship: :I = \frac, where is the current through the conductor, ''V'' is the voltage measured ''across'' the conductor and ''R'' is the resistance of the conductor. More specifically, Ohm's law states that the ''R'' in this relation is constant, independent of the current. If the resistance is not constant, the previous equation cannot be called ''Ohm's law'', but it can still be used as a definition of static/DC resistance. Ohm's law is an empirical relation which accurately describes the conductivity of the vast majority of electrically conductive materials over many orders of magnitude of current. However some materials do not obey Ohm's law; these are called non-ohmic. The law was named after the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Kirchhoff's Circuit Laws
Kirchhoff's circuit laws are two equalities that deal with the current and potential difference (commonly known as voltage) in the lumped element model of electrical circuits. They were first described in 1845 by German physicist Gustav Kirchhoff. This generalized the work of Georg Ohm and preceded the work of James Clerk Maxwell. Widely used in electrical engineering, they are also called Kirchhoff's rules or simply Kirchhoff's laws. These laws can be applied in time and frequency domains and form the basis for network analysis. Both of Kirchhoff's laws can be understood as corollaries of Maxwell's equations in the low-frequency limit. They are accurate for DC circuits, and for AC circuits at frequencies where the wavelengths of electromagnetic radiation are very large compared to the circuits. Kirchhoff's current law This law, also called Kirchhoff's first law, or Kirchhoff's junction rule, states that, for any node (junction) in an electrical circuit, the sum of curr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Von Neumann Bottleneck
The von Neumann architecture — also known as the von Neumann model or Princeton architecture — is a computer architecture based on a 1945 description by John von Neumann, and by others, in the ''First Draft of a Report on the EDVAC''. The document describes a design architecture for an electronic digital computer with these components: * A processing unit with both an arithmetic logic unit and processor registers * A control unit that includes an instruction register and a program counter * Memory that stores data and instructions * External mass storage * Input and output mechanisms.. The term "von Neumann architecture" has evolved to refer to any stored-program computer in which an instruction fetch and a data operation cannot occur at the same time (since they share a common bus). This is referred to as the von Neumann bottleneck, which often limits the performance of the corresponding system. The design of a von Neumann architecture machine is simpler than in a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
In-memory Computing
In computer science, in-memory processing is an emerging technology for processing of data stored in an in-memory database. In-memory processing is one method of addressing the performance and power bottlenecks caused by the movement of data between the processor and the main memory. Older systems have been based on disk storage and relational databases using SQL query language, but these are increasingly regarded as inadequate to meet business intelligence (BI) needs. Because stored data is accessed much more quickly when it is placed in random-access memory (RAM) or flash memory, in-memory processing allows data to be analysed in real time, enabling faster reporting and decision-making in business. Disk-based Business Intelligence Data structures With disk-based technology, data is loaded on to the computer's hard disk in the form of multiple tables and multi-dimensional structures against which queries are run. Disk-based technologies are relational database management sy ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ECRAM Synapse In-memory Compute
Electrochemical Random-Access Memory (ECRAM) is a type of Non-volatile memory, non-volatile memory (NVM) with Multi-level cell, multiple levels per cell (MLC) designed for deep learning analog acceleration. An ECRAM cell is a three-terminal device composed of a conductive channel, an insulating electrolyte, an ionic reservoir, and metal contacts. The resistance of the channel is modulated by ionic exchange at the interface between the channel and the electrolyte upon application of an electric field. The charge-transfer process allows both for state retention in the absence of applied power, and for programming of multiple distinct levels, both differentiating ECRAM operation from that of a field-effect transistor, field-effect transistor (FET). The write operation is deterministic and can result in symmetrical potentiation and depression, making ECRAM arrays attractive for acting as artificial synaptic weights in physical implementations of artificial neural networks, artificial n ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
