An AI accelerator is a class of specialized
hardware accelerator
Hardware acceleration is the use of computer hardware designed to perform specific functions more efficiently when compared to software running on a general-purpose central processing unit (CPU). Any function (mathematics), transformation of d ...
or computer system designed to accelerate
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 re ...
and
machine learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence.
Machine ...
applications, including
artificial neural network
Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains.
An ANN is based on a collection of connected unit ...
s and
machine vision
Machine vision (MV) is the technology and methods used to provide imaging-based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine vision refers to m ...
. Typical applications include algorithms for
robotics
Robotics is an interdisciplinary branch of computer science and engineering. Robotics involves design, construction, operation, and use of robots. The goal of robotics is to design machines that can help and assist humans. Robotics integrat ...
,
internet of things
The Internet of things (IoT) describes physical objects (or groups of such objects) with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other comm ...
, and other
data
In the pursuit of knowledge, data (; ) is a collection of discrete values that convey information, describing quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted ...
-intensive or sensor-driven tasks. They are often
manycore
Manycore processors are special kinds of multi-core processors designed for a high degree of parallel processing, containing numerous simpler, independent processor cores (from a few tens of cores to thousands or more). Manycore processors are use ...
designs and generally focus on
low-precision arithmetic, novel
dataflow architecture
Dataflow architecture is a dataflow-based computer architecture that directly contrasts the traditional von Neumann architecture or control flow architecture. Dataflow architectures have no program counter, in concept: the executability and executi ...
s or
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 bet ...
capability. , a typical AI
integrated circuit
An integrated circuit or monolithic integrated circuit (also referred to as an IC, a chip, or a microchip) is a set of electronic circuits on one small flat piece (or "chip") of semiconductor material, usually silicon. Large numbers of tiny ...
chip
contains billions of
MOSFET
The metal–oxide–semiconductor field-effect transistor (MOSFET, MOS-FET, or MOS FET) is a type of field-effect transistor (FET), most commonly fabricated by the controlled oxidation of silicon. It has an insulated gate, the voltage of which d ...
transistors.
A number of vendor-specific terms exist for devices in this category, and it is an
emerging technology
Emerging technologies are technologies whose development, practical applications, or both are still largely unrealized. These technologies are generally new but also include older technologies finding new applications. Emerging technologies ar ...
without a
dominant design Dominant design is a technology management concept introduced by James M. Utterback and William J. Abernathy in 1975, identifying key technological features that become a de facto standard. A dominant design is the one that wins the allegiance of t ...
.
History
Computer systems have frequently complemented the
CPU with special-purpose accelerators for specialized tasks, known as
coprocessor
A coprocessor is a computer processor used to supplement the functions of the primary processor (the CPU). Operations performed by the coprocessor may be floating-point arithmetic, graphics, signal processing, string processing, cryptography o ...
s. Notable
application-specific hardware units include
video card
A graphics card (also called a video card, display card, graphics adapter, VGA card/VGA, video adapter, display adapter, or mistakenly GPU) is an expansion card which generates a feed of output images to a display device, such as a computer moni ...
s for
graphic
Graphics () are visual images or designs on some surface, such as a wall, canvas, screen, paper, or stone, to inform, illustrate, or entertain. In contemporary usage, it includes a pictorial representation of data, as in design and manufacture, ...
s,
sound card
A sound card (also known as an audio card) is an internal expansion card that provides input and output of audio signals to and from a computer under the control of computer programs. The term ''sound card'' is also applied to external audio i ...
s,
graphics processing unit
A graphics processing unit (GPU) is a specialized electronic circuit designed to manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. GPUs are used in embedded systems, mobi ...
s and
digital signal processor
A 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 si ...
s. As
deep learning
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.
De ...
and
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 re ...
workloads rose in prominence in the 2010s, specialized hardware units were developed or adapted from existing products to
accelerate
In mechanics, acceleration is the rate of change of the velocity of an object with respect to time. Accelerations are vector quantities (in that they have magnitude and direction). The orientation of an object's acceleration is given by the ...
these tasks.
Early attempts
First attempts like
Intel
Intel Corporation is an American multinational corporation and technology company headquartered in Santa Clara, California. It is the world's largest semiconductor chip manufacturer by revenue, and is one of the developers of the x86 seri ...
's ETANN 80170NX incorporated analog circuits to compute neural functions. Later all-digital chips like the Nestor/Intel
Ni1000
The Ni1000 is an artificial neural network chip developed by Nestor Corporation and Intel. It is Intel's second-generation neural network chip but first all digital. The chip is aimed at image analysis applications, contains more than 3 million tra ...
followed. As early as 1993,
digital signal processor
A 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 si ...
s were used as neural network accelerators to accelerate
optical character recognition
Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scen ...
software. In the 1990s, there were also attempts to create parallel high-throughput systems for workstations aimed at various applications, including neural network simulations.
[This presentation covers a past attempt at neural net accelerators, notes the similarity to the modern SLI GPGPU processor setup, and argues that general purpose vector accelerators are the way forward (in relation to RISC-V hwacha project. Argues that NN's are just dense and sparse matrices, one of several recurring algorithms)] FPGA
A field-programmable gate array (FPGA) is an integrated circuit designed to be configured by a customer or a designer after manufacturinghence the term '' field-programmable''. The FPGA configuration is generally specified using a hardware de ...
-based accelerators were also first explored in the 1990s for both inference
and training.
Smartphone
A smartphone is a portable computer device that combines mobile telephone and computing functions into one unit. They are distinguished from feature phones by their stronger hardware capabilities and extensive mobile operating systems, whic ...
s began incorporating AI accelerators starting with the
Qualcomm
Qualcomm () is an American multinational corporation headquartered in San Diego, California, and incorporated in Delaware. It creates semiconductors, software, and services related to wireless technology. It owns patents critical to the 5G, 4 ...
Snapdragon 820 in 2015.
Heterogeneous computing
Heterogeneous computing
Heterogeneous computing refers to systems that use more than one kind of processor or cores. These systems gain performance or energy efficiency not just by adding the same type of processors, but by adding dissimilar coprocessors, usually incorp ...
refers to incorporating a number of specialized processors in a single system, or even a single chip, each optimized for a specific type of task. Architectures such as the
Cell microprocessor
Cell is a multi-core microprocessor microarchitecture that combines a general-purpose PowerPC core of modest performance with streamlined coprocessing elements which greatly accelerate multimedia and vector processing applications, as well as m ...
have features significantly overlapping with AI accelerators including: support for packed low precision arithmetic,
dataflow architecture
Dataflow architecture is a dataflow-based computer architecture that directly contrasts the traditional von Neumann architecture or control flow architecture. Dataflow architectures have no program counter, in concept: the executability and executi ...
, and prioritizing 'throughput' over latency. The Cell microprocessor was subsequently applied to a number of tasks including AI.
In the 2000s,
CPUs also gained increasingly wide
SIMD
Single instruction, multiple data (SIMD) is a type of parallel processing in Flynn's taxonomy. SIMD can be internal (part of the hardware design) and it can be directly accessible through an instruction set architecture (ISA), but it should ...
units, driven by video and gaming workloads; as well as support for packed low-precision
data type
In computer science and computer programming, a data type (or simply type) is a set of possible values and a set of allowed operations on it. A data type tells the compiler or interpreter how the programmer intends to use the data. Most progra ...
s. Due to increasing performance of CPUs, they are also being used for running AI workloads. CPUs are superior for
DNNs with small or medium-scale parallelism, for sparse DNNs and in low-batch-size scenarios.
Use of GPU
Graphics processing unit
A graphics processing unit (GPU) is a specialized electronic circuit designed to manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. GPUs are used in embedded systems, mobi ...
s or GPUs are specialized hardware for the manipulation of images and calculation of local image properties. The mathematical basis of neural networks and
image manipulation
Image editing encompasses the processes of altering images, whether they are digital photographs, traditional photo-chemical photographs, or illustrations. Traditional analog image editing is known as photo retouching, using tools such as ...
are similar,
embarrassingly parallel
In parallel computing, an embarrassingly parallel workload or problem (also called embarrassingly parallelizable, perfectly parallel, delightfully parallel or pleasingly parallel) is one where little or no effort is needed to separate the problem i ...
tasks involving matrices, leading GPUs to become increasingly used for machine learning tasks. , GPUs are popular for AI work, and they continue to evolve in a direction to facilitate deep learning, both for training and inference in devices such as
self-driving car
A self-driving car, also known as an autonomous car, driver-less car, or robotic car (robo-car), is a car that is capable of traveling without human input.Xie, S.; Hu, J.; Bhowmick, P.; Ding, Z.; Arvin, F.,Distributed Motion Planning for S ...
s. GPU developers such as Nvidia
NVLink
NVLink is a wire-based serial multi-lane near-range communications link developed by Nvidia. Unlike PCI Express, a device can consist of multiple NVLinks, and devices use mesh networking to communicate instead of a central hub. The protocol was f ...
are developing additional connective capability for the kind of dataflow workloads AI benefits from. As GPUs have been increasingly applied to AI acceleration, GPU manufacturers have incorporated
neural network
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological ...
-
specific
Specific may refer to:
* Specificity (disambiguation)
* Specific, a cure or therapy for a specific illness
Law
* Specific deterrence, focussed on an individual
* Specific finding, intermediate verdict used by a jury in determining the fina ...
hardware to further accelerate these tasks.
Tensor
cores are intended to speed up the training of neural networks.
Use of FPGAs
Deep learning frameworks are still evolving, making it hard to design custom hardware.
Reconfigurable devices such as
field-programmable gate array
A field-programmable gate array (FPGA) is an integrated circuit designed to be configured by a customer or a designer after manufacturinghence the term '' field-programmable''. The FPGA configuration is generally specified using a hardware d ...
s (FPGA) make it easier to evolve hardware, frameworks, and software
alongside each other.
Microsoft has used FPGA chips to accelerate inference.
Emergence of dedicated AI accelerator ASICs
While GPUs and FPGAs perform far better than CPUs for AI-related tasks, a factor of up to 10 in efficiency may be gained with a more specific design, via an
application-specific integrated circuit
An application-specific integrated circuit (ASIC ) is an integrated circuit (IC) chip customized for a particular use, rather than intended for general-purpose use, such as a chip designed to run in a digital voice recorder or a high-efficie ...
(ASIC). These accelerators employ strategies such as optimized
memory use and the use of
lower precision arithmetic to accelerate calculation and increase
throughput
Network throughput (or just throughput, when in context) refers to the rate of message delivery over a communication channel, such as Ethernet or packet radio, in a communication network. The data that these messages contain may be delivered ov ...
of computation.
Some adopted low-precision
floating-point formats used AI acceleration are
half-precision
In computing, half precision (sometimes called FP16) 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 w ...
and the
bfloat16 floating-point format
The bfloat16 (Brain Floating Point) floating-point format is a computer number format occupying 16 bits in computer memory; it represents a wide dynamic range of numeric values by using a floating radix point. This format is a truncated (16-b ...
.
Companies such as Google, Qualcomm, Amazon, Apple, Facebook, AMD and Samsung are all designing their own AI ASICs.
Cerebras Systems has also built a dedicated AI accelerator based on the largest processor in the industry, the second-generation Wafer Scale Engine (WSE-2), to support deep learning workloads.
In-memory computing architectures
In June 2017,
IBM researchers announced an architecture in contrast to the
Von Neumann architecture
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 ...
based on
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 bet ...
and
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 pr ...
arrays applied to temporal
correlation
In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. Although in the broadest sense, "correlation" may indicate any type of association, in statistics ...
detection, intending to generalize the approach to
heterogeneous computing
Heterogeneous computing refers to systems that use more than one kind of processor or cores. These systems gain performance or energy efficiency not just by adding the same type of processors, but by adding dissimilar coprocessors, usually incorp ...
and
massively parallel
Massively parallel is the term for using a large number of computer processors (or separate computers) to simultaneously perform a set of coordinated computations in parallel. GPUs are massively parallel architecture with tens of thousands of t ...
systems. In October 2018, IBM researchers announced an architecture based on
in-memory processing
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 be ...
and
modeled on the human brain's synaptic network to accelerate
deep neural network
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.
De ...
s. The system is based on
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 pr ...
arrays.
In-memory computing with analog resistive memories
In 2019, researchers from Politecnico di Milano found a way to solve systems of linear equations in a few tens of nanoseconds via a single operation. Their algorithm is based on
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 bet ...
with analog resistive memories which performs with high efficiencies of time and energy, via conducting
matrix–vector multiplication
In mathematics, particularly in linear algebra, matrix multiplication is a binary operation that produces a matrix (mathematics), matrix from two matrices. For matrix multiplication, the number of columns in the first matrix must be equal to the n ...
in one step using Ohm's law and Kirchhoff's law. The researchers showed that a feedback circuit with cross-point resistive memories can solve algebraic problems such as systems of linear equations, matrix eigenvectors, and differential equations in just one step. Such an approach improves computational times drastically in comparison with digital algorithms.
Atomically thin semiconductors
In 2020, Marega et al. published experiments with a large-area active channel material for developing logic-in-memory devices and circuits based on
floating-gate
The floating-gate MOSFET (FGMOS), also known as a floating-gate MOS transistor or floating-gate transistor, is a type of metal–oxide–semiconductor field-effect transistor (MOSFET) where the gate is electrically isolated, creating a floating no ...
field-effect transistor
The field-effect transistor (FET) is a type of transistor that uses an electric field to control the flow of current in a semiconductor. FETs (JFETs or MOSFETs) are devices with three terminals: ''source'', ''gate'', and ''drain''. FETs contro ...
s (FGFETs).
Such atomically thin
semiconductor
A semiconductor is a material which has an electrical resistivity and conductivity, electrical conductivity value falling between that of a electrical conductor, conductor, such as copper, and an insulator (electricity), insulator, such as glas ...
s are considered promising for energy-efficient
machine learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence.
Machine ...
applications, where the same basic device structure is used for both logic operations and data storage. The authors used two-dimensional materials such as semiconducting
molybdenum disulfide
Molybdenum disulfide (or moly) is an inorganic compound composed of molybdenum and sulfur. Its chemical formula is .
The compound is classified as a transition metal dichalcogenide. It is a silvery black solid that occurs as the mineral molybdenit ...
.
Integrated photonic tensor core
In 2021, J. Feldmann et al. proposed an integrated
photonic
Photonics is a branch of optics that involves the application of generation, detection, and manipulation of light in form of photons through emission, transmission, modulation, signal processing, switching, amplification, and sensing. Though ...
hardware accelerator
Hardware acceleration is the use of computer hardware designed to perform specific functions more efficiently when compared to software running on a general-purpose central processing unit (CPU). Any function (mathematics), transformation of d ...
for parallel convolutional processing.
The authors identify two key advantages of integrated photonics over its electronic counterparts: (1) massively parallel data transfer through
wavelength
In physics, the wavelength is the spatial period of a periodic wave—the distance over which the wave's shape repeats.
It is the distance between consecutive corresponding points of the same phase on the wave, such as two adjacent crests, tro ...
division
multiplexing
In telecommunications and computer networking, multiplexing (sometimes contracted to muxing) is a method by which multiple analog or digital signals are combined into one signal over a shared medium. The aim is to share a scarce resource - a ...
in conjunction with
frequency comb In optics, a frequency comb is a laser source whose spectrum consists of a series of discrete, equally spaced frequency lines. Frequency combs can be generated by a number of mechanisms, including periodic modulation (in amplitude and/or phase) of a ...
s, and (2) extremely high data modulation speeds.
Their system can execute trillions of multiply-accumulate operations per second, indicating the potential of
integrated photonics
Photonics is a branch of optics that involves the application of generation, detection, and manipulation of light in form of photons through emission, transmission, modulation, signal processing, switching, amplification, and sensing. Though ...
in data-heavy AI applications.
Nomenclature
As of 2016, the field is still in flux and vendors are pushing their own marketing term for what amounts to an "AI accelerator", in the hope that their designs and
APIs will become the
dominant design Dominant design is a technology management concept introduced by James M. Utterback and William J. Abernathy in 1975, identifying key technological features that become a de facto standard. A dominant design is the one that wins the allegiance of t ...
. There is no consensus on the boundary between these devices, nor the exact form they will take; however several examples clearly aim to fill this new space, with a fair amount of overlap in capabilities.
In the past when consumer
graphics accelerator
A graphics processing unit (GPU) is a specialized electronic circuit designed to manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. GPUs are used in embedded systems, mobil ...
s emerged, the industry eventually adopted
Nvidia
Nvidia CorporationOfficially written as NVIDIA and stylized in its logo as VIDIA with the lowercase "n" the same height as the uppercase "VIDIA"; formerly stylized as VIDIA with a large italicized lowercase "n" on products from the mid 1990s to ...
's self-assigned term, "the GPU", as the collective noun for "graphics accelerators", which had taken many forms before settling on an overall
pipeline
Pipeline may refer to:
Electronics, computers and computing
* Pipeline (computing), a chain of data-processing stages or a CPU optimization found on
** Instruction pipelining, a technique for implementing instruction-level parallelism within a s ...
implementing a model presented by
Direct3D
Direct3D is a graphics application programming interface (API) for Microsoft Windows. Part of DirectX, Direct3D is used to render three-dimensional graphics in applications where performance is important, such as games. Direct3D uses hardware a ...
.
Potential applications
*
Agricultural robot
An agricultural robot is a robot deployed for agriculture, agricultural purposes. The main area of application of robots in agriculture today is at the harvesting (agriculture), harvesting stage. Emerging applications of robots or Drone (robotic ...
s, for example herbicide-free weed control.
*
Autonomous vehicles
Vehicular automation involves the use of mechatronics, artificial intelligence, and multi-agent systems to assist the operator of a vehicle (car, aircraft, watercraft, or otherwise).Hu, J.; Bhowmick, P.; Lanzon, A.,Group Coordinated Control o ...
: Nvidia has targeted their
Drive PX-series
Nvidia Drive is a computer platform by Nvidia, aimed at providing autonomous car and driver assistance functionality powered by deep learning. The platform was introduced at the Consumer Electronics Show (CES) in Las Vegas in January 2015. An enhan ...
boards at this application.
*
Computer-aided diagnosis
Computer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist doctors in the interpretation of medical imaging, medical images. Imaging techniques in X-ray, MRI, Endoscopy, and ultrasound diagnostics yield ...
*
Industrial robot
An industrial robot is a robot system used for manufacturing. Industrial robots are automated, programmable and capable of movement on three or more axes.
Typical applications of robots include welding, painting, assembly, disassembly, pick a ...
s, increasing the range of tasks that can be automated, by adding adaptability to variable situations.
*
Machine translation
Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-aided human translation or interactive translation), is a sub-field of computational linguistics that investigates t ...
*
Military robot
Military robots are autonomous robots or remote-controlled mobile robots designed for military applications, from transport to search & rescue and attack.
Some such systems are currently in use, and many are under development.
History
Broad ...
s
*
Natural language processing
Natural language processing (NLP) is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to pro ...
*
Search engine
A search engine is a software system designed to carry out web searches. They search the World Wide Web in a systematic way for particular information specified in a textual web search query. The search results are generally presented in a ...
s, increasing the
energy efficiency
Energy efficiency may refer to:
* Energy efficiency (physics), the ratio between the useful output and input of an energy conversion process
** Electrical efficiency, useful power output per electrical power consumed
** Mechanical efficiency, a ra ...
of
data center
A data center (American English) or data centre (British English)See spelling differences. is a building, a dedicated space within a building, or a group of buildings used to house computer systems and associated components, such as telecommunic ...
s and ability to use increasingly advanced
queries.
*
Unmanned aerial vehicle
An unmanned aerial vehicle (UAV), commonly known as a drone, is an aircraft without any human pilot, crew, or passengers on board. UAVs are a component of an unmanned aircraft system (UAS), which includes adding a ground-based controller ...
s, e.g. navigation systems, e.g. the
Movidius Myriad 2
Movidius is a company based in San Mateo, California, that designs specialised low-power processor chips for computer vision. The company was acquired by Intel in September 2016.
Company history
Movidius was co-founded in Dublin in 2005, by S ...
has been demonstrated successfully guiding autonomous drones.
*
Voice user interface
A voice-user interface (VUI) makes spoken human interaction with computers possible, using speech recognition to understand spoken commands and answer questions, and typically text to speech to play a reply. A voice command device is a device con ...
, e.g. in mobile phones, a target for Qualcomm
Zeroth
0th or zeroth may refer to:
Mathematics, science and technology
* 0th or zeroth, an ordinal for the number zero
* 0th dimension, a topological space
* 0th element, of a data structure in computer science
* Zeroth (software), deep learning softw ...
.
See also
*
Cognitive computer
*
Deep learning processor
*
Neuromorphic engineering
Neuromorphic engineering, also known as neuromorphic computing, is the use of electronic circuits to mimic neuro-biological architectures present in the nervous system. A neuromorphic computer/chip is any device that uses physical artificial ne ...
*
Optical neural network
An optical neural network is a physical implementation of an artificial neural network with photonics, optical components. Early optical neural networks used a photorefractive Volume hologram to interconnect arrays of input neurons to arrays of o ...
*
Physical neural network
References
External links
Nvidia Puts The Accelerator To The Metal With Pascal.htm The Next Platform
Eyeriss Project MIT
*https://alphaics.ai/
{{Hardware acceleration
Application-specific integrated circuits
Coprocessors
Computer optimization
Gate arrays