Multiply–accumulate operationIn computing, especially digital signal processing, the multiply–accumulate (MAC) or multiply-add (MAD) operation is a common step that computes the product of two numbers and adds that product to an accumulator. The hardware unit that performs the operation is known as a multiplier–accumulator (MAC unit); the operation itself is also often called a MAC or a MAD operation. The MAC operation modifies an accumulator a: When done with floating point numbers, it might be performed with two roundings (typical in many DSPs), or with a single rounding.
Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
Neural networkA neural network can refer to a neural circuit of biological neurons (sometimes also called a biological neural network), a network of artificial neurons or nodes in the case of an artificial neural network. Artificial neural networks are used for solving artificial intelligence (AI) problems; they model connections of biological neurons as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed.
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
Mac ProMac Pro is a series of workstations and servers for professionals made by Apple Inc. since 2006. The Mac Pro, by some performance benchmarks, is the most powerful computer that Apple offers. It is one of four desktop computers in the current Mac lineup, sitting above the Mac Mini, iMac and Mac Studio. Introduced in August 2006, the Mac Pro was an Intel-based replacement for the Power Mac line and had two dual-core Xeon Woodcrest processors and a rectangular tower case carried over from the Power Mac G5.
Mac OS 9Mac OS 9 is the ninth and final major release of Apple's classic Mac OS operating system which was succeeded by Mac OS X (renamed to OS X in 2011 and macOS in 2016) in 2001. Introduced on October 23, 1999, it was promoted by Apple as "The Best Internet Operating System Ever", highlighting Sherlock 2's Internet search capabilities, integration with Apple's free online services known as iTools and improved Open Transport networking.
Binary multiplierA binary multiplier is an electronic circuit used in digital electronics, such as a computer, to multiply two binary numbers. A variety of techniques can be used to implement a digital multiplier. Most techniques involve computing the set of partial products, which are then summed together using binary adders. This process is similar to long multiplication, except that it uses a base-2 (binary) numeral system. Between 1947 and 1949 Arthur Alec Robinson worked for English Electric Ltd, as a student apprentice, and then as a development engineer.
Types of artificial neural networksThere are many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey between input (such as from the eyes or nerve endings in the hand), processing, and output from the brain (such as reacting to light, touch, or heat). The way neurons semantically communicate is an area of ongoing research.
Mac (computer)The Mac, short for Macintosh (its official name until 1999), is a family of personal computers designed and marketed by Apple Inc. The product lineup includes the MacBook Air and MacBook Pro laptops, as well as the iMac, Mac Mini, Mac Studio and Mac Pro desktops. Macs are sold with the macOS operating system. The first Mac was released in 1984, and was advertised with the highly acclaimed "1984" ad. After a period of initial success, the Mac languished in the 1990s until the 1996 acquisition of NeXT brought Steve Jobs back to Apple.
Mac MiniMac Mini (stylized as Mac mini) is a small form factor desktop computer developed and marketed by Apple Inc. , it is positioned between the consumer all-in-one iMac and the professional Mac Studio and Mac Pro as one of four current Mac desktop computers. Since launch, it has shipped without a display, keyboard, and mouse. The machine was initially branded as "BYODKM" (Bring Your Own Display, Keyboard, and Mouse) as a strategic pitch to encourage users to switch from Windows and Linux computers.
Half-precision floating-point formatIn computing, half precision (sometimes called FP16 or float16) is a binary floating-point computer number format that occupies 16 bits (two bytes in modern computers) in computer memory. It is intended for storage of floating-point values in applications where higher precision is not essential, in particular and neural networks. Almost all modern uses follow the IEEE 754-2008 standard, where the 16-bit base-2 format is referred to as binary16, and the exponent uses 5 bits.
Quadruple-precision floating-point formatIn computing, quadruple precision (or quad precision) is a binary floating point–based computer number format that occupies 16 bytes (128 bits) with precision at least twice the 53-bit double precision. This 128-bit quadruple precision is designed not only for applications requiring results in higher than double precision, but also, as a primary function, to allow the computation of double precision results more reliably and accurately by minimising overflow and round-off errors in intermediate calculations and scratch variables.
Extended precisionExtended precision refers to floating-point number formats that provide greater precision than the basic floating-point formats. Extended precision formats support a basic format by minimizing roundoff and overflow errors in intermediate values of expressions on the base format. In contrast to extended precision, arbitrary-precision arithmetic refers to implementations of much larger numeric types (with a storage count that usually is not a power of two) using special software (or, rarely, hardware).
Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Convolutional neural networkConvolutional neural network (CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections. For example, for each neuron in the fully-connected layer 10,000 weights would be required for processing an image sized 100 × 100 pixels.
Mac OS X TigerMac OS X Tiger (version 10.4) is the 5th major release of macOS, Apple's desktop and server operating system for Mac computers. Tiger was released to the public on April 29, 2005 for US$129.95 as the successor to Mac OS X 10.3 Panther. Included features were a fast searching system called Spotlight, a new version of the Safari web browser, Dashboard, a new 'Unified' theme, and improved support for 64-bit addressing on Power Mac G5s. Mac OS X 10.
Digital signal processorA digital signal processor (DSP) is a specialized microprocessor chip, with its architecture optimized for the operational needs of digital signal processing. DSPs are fabricated on MOS integrated circuit chips. They are widely used in audio signal processing, telecommunications, , radar, sonar and speech recognition systems, and in common consumer electronic devices such as mobile phones, disk drives and high-definition television (HDTV) products. The goal of a DSP is usually to measure, filter or compress continuous real-world analog signals.
Microprocessor chronologyThe first microprocessors were designed and manufactured in the 1970s. Intel's 4004 of 1971 is widely regarded as the first commercial microprocessor. Designers predominantly used MOSFET transistors with pMOS logic in the early 1970s, switching to nMOS logic after the mid-1970s. nMOS had the advantage that it could run on a single voltage, typically +5V, which simplified the power supply requirements and allowed it to be easily interfaced with the wide variety of +5V transistor-transistor logic (TTL) devices.
Computational neuroscienceComputational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, computer simulations, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system. Computational neuroscience employs computational simulations to validate and solve mathematical models, and so can be seen as a sub-field of theoretical neuroscience; however, the two fields are often synonymous.
AI acceleratorAn AI accelerator is a class of specialized hardware accelerator or computer system designed to accelerate artificial intelligence and machine learning applications, including artificial neural networks and machine vision. Typical applications include algorithms for robotics, Internet of Things, and other data-intensive or sensor-driven tasks. They are often manycore designs and generally focus on low-precision arithmetic, novel dataflow architectures or in-memory computing capability.
