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#alternate Edit this page Wikipedia (en)
Graphics processing unit
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Specialized electronic circuit; graphics accelerator
"GPU" redirects here. For other uses, see GPU (disambiguation).
For an expansion card that contains a graphics processing unit, see
graphics card.
Components of a GPU
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, mobile phones, personal computers,
workstations, and game consoles.
Modern GPUs are efficient at manipulating computer graphics and image
processing. Their parallel structure makes them more efficient than
general-purpose central processing units (CPUs) for algorithms that
process large blocks of data in parallel. In a personal computer, a GPU
can be present on a video card or embedded on the motherboard. In some
CPUs, they are embedded on the CPU die.^[1]
In the 1970s, the term "GPU" originally stood for graphics processor
unit and described a programmable processing unit independently working
from the CPU and responsible for graphics manipulation and
output.^[2]^[3] Later, in 1994, Sony used the term (now standing for
graphics processing unit) in reference to the PlayStation console's
Toshiba-designed Sony GPU in 1994.^[4] The term was popularized by
Nvidia in 1999, who marketed the GeForce 256 as "the world's first
GPU".^[5] It was presented as a "single-chip processor with integrated
transform, lighting, triangle setup/clipping, and rendering
engines".^[6] Rival ATI Technologies coined the term "visual processing
unit" or VPU with the release of the Radeon 9700 in 2002.^[7]
[ ]
Contents
* 1 History
+ 1.1 1970s
+ 1.2 1980s
+ 1.3 1990s
+ 1.4 2000 to 2010
+ 1.5 2010 to present
+ 1.6 GPU companies
* 2 Computational functions
+ 2.1 GPU accelerated video decoding and encoding
o 2.1.1 Video decoding processes that can be accelerated
* 3 GPU forms
+ 3.1 Terminology
o 3.1.1 Usage specific GPU
+ 3.2 Dedicated graphics cards
+ 3.3 Integrated graphics processing unit
+ 3.4 Hybrid graphics processing
+ 3.5 Stream processing and general purpose GPUs (GPGPU)
+ 3.6 External GPU (eGPU)
* 4 Sales
* 5 See also
+ 5.1 Hardware
+ 5.2 APIs
+ 5.3 Applications
* 6 References
* 7 External links
History[edit]
See also: Video display controller, List of home computers by video
hardware, and Sprite (computer graphics)
1970s[edit]
Arcade system boards have been using specialized graphics circuits
since the 1970s. In early video game hardware, the RAM for frame
buffers was expensive, so video chips composited data together as the
display was being scanned out on the monitor.^[8]
A specialized barrel shifter circuit was used to help the CPU animate
the framebuffer graphics for various 1970s arcade games from Midway and
Taito, such as Gun Fight (1975), Sea Wolf (1976) and Space Invaders
(1978).^[9]^[10]^[11] The Namco Galaxian arcade system in 1979 used
specialized graphics hardware supporting RGB color, multi-colored
sprites and tilemap backgrounds.^[12] The Galaxian hardware was widely
used during the golden age of arcade video games, by game companies
such as Namco, Centuri, Gremlin, Irem, Konami, Midway, Nichibutsu, Sega
and Taito.^[13]^[14]
Atari ANTIC microprocessor on an Atari 130XE motherboard
In the home market, the Atari 2600 in 1977 used a video shifter called
the Television Interface Adaptor.^[15] The Atari 8-bit computers (1979)
had ANTIC, a video processor which interpreted instructions describing
a "display list"--the way the scan lines map to specific bitmapped or
character modes and where the memory is stored (so there did not need
to be a contiguous frame buffer).^[16] 6502 machine code subroutines
could be triggered on scan lines by setting a bit on a display list
instruction.^[17] ANTIC also supported smooth vertical and horizontal
scrolling independent of the CPU.^[18]
1980s[edit]
NEC mPD7220A
The NEC uPD7220 was the first implementation of a PC graphics display
processor as a single Large Scale Integration (LSI) integrated circuit
chip, enabling the design of low-cost, high-performance video graphics
cards such as those from Number Nine Visual Technology. It became the
best-known GPU up until the mid-1980s.^[19] It was the first fully
integrated VLSI (very large-scale integration)
metal-oxide-semiconductor (NMOS) graphics display processor for PCs,
supported up to 1024x1024 resolution, and laid the foundations for the
emerging PC graphics market. It was used in a number of graphics cards
and was licensed for clones such as the Intel 82720, the first of
Intel's graphics processing units.^[20] The Williams Electronics arcade
games Robotron 2084, Joust, Sinistar, and Bubbles, all released in
1982, contain custom blitter chips for operating on 16-color
bitmaps.^[21]^[22]
In 1984, Hitachi released ARTC HD63484, the first major CMOS graphics
processor for PC. The ARTC was capable of displaying up to 4K
resolution when in monochrome mode, and it was used in a number of PC
graphics cards and terminals during the late 1980s.^[23] In 1985, the
Commodore Amiga featured a custom graphics chip, with a blitter unit
accelerating bitmap manipulation, line draw, and area fill functions.
Also included is a coprocessor with its own simple instruction set,
capable of manipulating graphics hardware registers in sync with the
video beam (e.g. for per-scanline palette switches, sprite
multiplexing, and hardware windowing), or driving the blitter. In 1986,
Texas Instruments released the TMS34010, the first fully programmable
graphics processor.^[24] It could run general-purpose code, but it had
a graphics-oriented instruction set. During 1990-1992, this chip became
the basis of the Texas Instruments Graphics Architecture ("TIGA")
Windows accelerator cards.
The IBM 8514 Micro Channel adapter, with memory add-on.
In 1987, the IBM 8514 graphics system was released as one of^[vague]
the first video cards for IBM PC compatibles to implement
fixed-function 2D primitives in electronic hardware. Sharp's X68000,
released in 1987, used a custom graphics chipset^[25] with a 65,536
color palette and hardware support for sprites, scrolling, and multiple
playfields,^[26] eventually serving as a development machine for
Capcom's CP System arcade board. Fujitsu later competed with the FM
Towns computer, released in 1989 with support for a full 16,777,216
color palette.^[27] In 1988, the first dedicated polygonal 3D graphics
boards were introduced in arcades with the Namco System 21^[28] and
Taito Air System.^[29]
VGA section on the motherboard in IBM PS/55
IBM's proprietary Video Graphics Array (VGA) display standard was
introduced in 1987, with a maximum resolution of 640 *480 pixels. In
November 1988, NEC Home Electronics announced its creation of the Video
Electronics Standards Association (VESA) to develop and promote a Super
VGA (SVGA) computer display standard as a successor to IBM's
proprietary VGA display standard. Super VGA enabled graphics display
resolutions up to 800 *600 pixels, a 36% increase.^[30]
1990s[edit]
Tseng Labs ET4000/W32p
S3 Graphics ViRGE
Voodoo3 2000 AGP card
In 1991, S3 Graphics introduced the S3 86C911, which its designers
named after the Porsche 911 as an indication of the performance
increase it promised.^[31] The 86C911 spawned a host of imitators: by
1995, all major PC graphics chip makers had added 2D acceleration
support to their chips.^[32]^[33] By this time, fixed-function Windows
accelerators had surpassed expensive general-purpose graphics
coprocessors in Windows performance, and these coprocessors faded away
from the PC market.
Throughout the 1990s, 2D GUI acceleration continued to evolve. As
manufacturing capabilities improved, so did the level of integration of
graphics chips. Additional application programming interfaces (APIs)
arrived for a variety of tasks, such as Microsoft's WinG graphics
library for Windows 3.x, and their later DirectDraw interface for
hardware acceleration of 2D games within Windows 95 and later.
In the early- and mid-1990s, real-time 3D graphics were becoming
increasingly common in arcade, computer, and console games, which led
to increasing public demand for hardware-accelerated 3D graphics. Early
examples of mass-market 3D graphics hardware can be found in arcade
system boards such as the Sega Model 1, Namco System 22, and Sega Model
2, and the fifth-generation video game consoles such as the Saturn,
PlayStation and Nintendo 64. Arcade systems such as the Sega Model 2
and SGI Onyx-based Namco Magic Edge Hornet Simulator in 1993 were
capable of hardware T&L (transform, clipping, and lighting) years
before appearing in consumer graphics cards.^[34]^[35] Some systems
used DSPs to accelerate transformations. Fujitsu, which worked on the
Sega Model 2 arcade system,^[36] began working on integrating T&L into
a single LSI solution for use in home computers in 1995;^[37]^[38] the
Fujitsu Pinolite, the first 3D geometry processor for personal
computers, released in 1997.^[39] The first hardware T&L GPU on home
video game consoles was the Nintendo 64's Reality Coprocessor, released
in 1996.^[40] In 1997, Mitsubishi released the 3Dpro/2MP, a fully
featured GPU capable of transformation and lighting, for workstations
and Windows NT desktops;^[41] ATi utilized it for their FireGL 4000
graphics card, released in 1997.^[42]
The term "GPU" was coined by Sony in reference to the 32-bit Sony GPU
(designed by Toshiba) in the PlayStation video game console, released
in 1994.^[4]
In the PC world, notable failed first tries for low-cost 3D graphics
chips were the S3 ViRGE, ATI Rage, and Matrox Mystique. These chips
were essentially previous-generation 2D accelerators with 3D features
bolted on. Many were even pin-compatible with the earlier-generation
chips for ease of implementation and minimal cost. Initially,
performance 3D graphics were possible only with discrete boards
dedicated to accelerating 3D functions (and lacking 2D GUI acceleration
entirely) such as the PowerVR and the 3dfx Voodoo. However, as
manufacturing technology continued to progress, video, 2D GUI
acceleration and 3D functionality were all integrated into one chip.
Rendition's Verite chipsets were among the first to do this well enough
to be worthy of note. In 1997, Rendition went a step further by
collaborating with Hercules and Fujitsu on a "Thriller Conspiracy"
project which combined a Fujitsu FXG-1 Pinolite geometry processor with
a Verite V2200 core to create a graphics card with a full T&L engine
years before Nvidia's GeForce 256. This card, designed to reduce the
load placed upon the system's CPU, never made it to market.^[citation
needed]
OpenGL appeared in the early '90s as a professional graphics API, but
originally suffered from performance issues which allowed the Glide API
to step in and become a dominant force on the PC in the late '90s.^[43]
However, these issues were quickly overcome and the Glide API fell by
the wayside. Software implementations of OpenGL were common during this
time, although the influence of OpenGL eventually led to widespread
hardware support. Over time, a parity emerged between features offered
in hardware and those offered in OpenGL. DirectX became popular among
Windows game developers during the late 90s. Unlike OpenGL, Microsoft
insisted on providing strict one-to-one support of hardware. The
approach made DirectX less popular as a standalone graphics API
initially, since many GPUs provided their own specific features, which
existing OpenGL applications were already able to benefit from, leaving
DirectX often one generation behind. (See: Comparison of OpenGL and
Direct3D.)
Over time, Microsoft began to work more closely with hardware
developers and started to target the releases of DirectX to coincide
with those of the supporting graphics hardware. Direct3D 5.0 was the
first version of the burgeoning API to gain widespread adoption in the
gaming market, and it competed directly with many
more-hardware-specific, often proprietary graphics libraries, while
OpenGL maintained a strong following. Direct3D 7.0 introduced support
for hardware-accelerated transform and lighting (T&L) for Direct3D,
while OpenGL had this capability already exposed from its inception. 3D
accelerator cards moved beyond being just simple rasterizers to add
another significant hardware stage to the 3D rendering pipeline. The
Nvidia GeForce 256 (also known as NV10) was the first consumer-level
card released on the market with hardware-accelerated T&L, while
professional 3D cards already had this capability. Hardware transform
and lighting, both already existing features of OpenGL, came to
consumer-level hardware in the '90s and set the precedent for later
pixel shader and vertex shader units which were far more flexible and
programmable.
2000 to 2010[edit]
Nvidia was first to produce a chip capable of programmable shading; the
GeForce 3 (code named NV20). Each pixel could now be processed by a
short "program" that could include additional image textures as inputs,
and each geometric vertex could likewise be processed by a short
program before it was projected onto the screen. Used in the Xbox
console, it competed with the PlayStation 2, which used a custom vector
unit for hardware accelerated vertex processing (commonly referred to
as VU0/VU1). The earliest incarnations of shader execution engines used
in Xbox were not general purpose and could not execute arbitrary pixel
code. Vertices and pixels were processed by different units which had
their own resources with pixel shaders having much tighter constraints
(being as they are executed at much higher frequencies than with
vertices). Pixel shading engines were actually more akin to a highly
customizable function block and didn't really "run" a program. Many of
these disparities between vertex and pixel shading were not addressed
until much later with the Unified Shader Model.
By October 2002, with the introduction of the ATI Radeon 9700 (also
known as R300), the world's first Direct3D 9.0 accelerator, pixel and
vertex shaders could implement looping and lengthy floating point math,
and were quickly becoming as flexible as CPUs, yet orders of magnitude
faster for image-array operations. Pixel shading is often used for bump
mapping, which adds texture, to make an object look shiny, dull, rough,
or even round or extruded.^[44]
With the introduction of the Nvidia GeForce 8 series, and then new
generic stream processing unit GPUs became a more generalized computing
devices. Today, parallel GPUs have begun making computational inroads
against the CPU, and a subfield of research, dubbed GPU Computing or
GPGPU for General Purpose Computing on GPU, has found its way into
fields as diverse as machine learning,^[45] oil exploration, scientific
image processing, linear algebra,^[46] statistics,^[47] 3D
reconstruction and even stock options pricing determination. GPGPU at
the time was the precursor to what is now called a compute shader (e.g.
CUDA, OpenCL, DirectCompute) and actually abused the hardware to a
degree by treating the data passed to algorithms as texture maps and
executing algorithms by drawing a triangle or quad with an appropriate
pixel shader. This obviously entails some overheads since units like
the Scan Converter are involved where they aren't really needed (nor
are triangle manipulations even a concern--except to invoke the pixel
shader).
Nvidia's CUDA platform, first introduced in 2007,^[48] was the earliest
widely adopted programming model for GPU computing. More recently
OpenCL has become broadly supported. OpenCL is an open standard defined
by the Khronos Group which allows for the development of code for both
GPUs and CPUs with an emphasis on portability.^[49] OpenCL solutions
are supported by Intel, AMD, Nvidia, and ARM, and according to a recent
report by Evan's Data, OpenCL is the GPGPU development platform most
widely used by developers in both the US and Asia Pacific.^[citation
needed]
2010 to present[edit]
In 2010, Nvidia began a partnership with Audi to power their cars'
dashboards, using the Tegra GPUs to provide increased functionality to
cars' navigation and entertainment systems.^[50] Advances in GPU
technology in cars has helped push self-driving technology.^[51] AMD's
Radeon HD 6000 Series cards were released in 2010 and in 2011, AMD
released their 6000M Series discrete GPUs to be used in mobile
devices.^[52] The Kepler line of graphics cards by Nvidia came out in
2012 and were used in the Nvidia's 600 and 700 series cards. A feature
in this new GPU microarchitecture included GPU boost, a technology that
adjusts the clock-speed of a video card to increase or decrease it
according to its power draw.^[53] The Kepler microarchitecture was
manufactured on the 28 nm process.
The PS4 and Xbox One were released in 2013, they both use GPUs based on
AMD's Radeon HD 7850 and 7790.^[54] Nvidia's Kepler line of GPUs was
followed by the Maxwell line, manufactured on the same process. 28 nm
chips by Nvidia were manufactured by TSMC, the Taiwan Semiconductor
Manufacturing Company, that was manufacturing using the 28 nm process
at the time. Compared to the 40 nm technology from the past, this new
manufacturing process allowed a 20 percent boost in performance while
drawing less power.^[55]^[56] Virtual reality headsets have very high
system requirements. VR headset manufacturers recommended the GTX 970
and the R9 290X or better at the time of their release.^[57]^[58]
Pascal is the next generation of consumer graphics cards by Nvidia
released in 2016. The GeForce 10 series of cards are under this
generation of graphics cards. They are made using the 16 nm
manufacturing process which improves upon previous
microarchitectures.^[59] Nvidia has released one non-consumer card
under the new Volta architecture, the Titan V. Changes from the Titan
XP, Pascal's high-end card, include an increase in the number of CUDA
cores, the addition of tensor cores, and HBM2. Tensor cores are cores
specially designed for deep learning, while high-bandwidth memory is
on-die, stacked, lower-clocked memory that offers an extremely wide
memory bus that is useful for the Titan V's intended purpose. To
emphasize that the Titan V is not a gaming card, Nvidia removed the
"GeForce GTX" suffix it adds to consumer gaming cards.
On August 20, 2018, Nvidia launched the RTX 20 series GPUs that add
ray-tracing cores to GPUs, improving their performance on lighting
effects.^[60] Polaris 11 and Polaris 10 GPUs from AMD are fabricated by
a 14-nanometer process. Their release results in a substantial increase
in the performance per watt of AMD video cards.^[61] AMD has also
released the Vega GPUs series for the high end market as a competitor
to Nvidia's high end Pascal cards, also featuring HBM2 like the Titan
V.
In 2019, AMD released the successor to their Graphics Core Next (GCN)
microarchitecture/instruction set. Dubbed as RDNA, the first product
lineup featuring the first generation of RDNA was the Radeon RX 5000
series of video cards, which later launched on July 7, 2019.^[62]
Later, the company announced that the successor to the RDNA
microarchitecture would be a refresh. Dubbed as RDNA 2, the new
microarchitecture was reportedly scheduled for release in Q4 2020.^[63]
AMD unveiled the Radeon RX 6000 series, its next-gen RDNA 2 graphics
cards with support for hardware-accelerated ray tracing at an online
event on October 28, 2020.^[64]^[65] The lineup initially consists of
the RX 6800, RX 6800 XT and RX 6900 XT.^[66]^[67] The RX 6800 and 6800
XT launched on November 18, 2020, with the RX 6900 XT being released on
December 8, 2020.^[68] The RX 6700 XT, which is based on Navi 22, was
launched on March 18, 2021.^[69]^[70]^[71]
The PlayStation 5 and Xbox Series X and Series S were released in 2020,
they both use GPUs based on the RDNA 2 microarchitecture with
proprietary tweaks and different GPU configurations in each system's
implementation.^[72]^[73]^[74]
GPU companies[edit]
Many companies have produced GPUs under a number of brand names. In
2009, Intel, Nvidia and AMD/ATI were the market share leaders, with
49.4%, 27.8% and 20.6% market share respectively. However, those
numbers include Intel's integrated graphics solutions as GPUs. Not
counting those, Nvidia and AMD control nearly 100% of the market as of
2018. Their respective market shares are 66% and 33%.^[75] In addition,
Matrox^[76] produces GPUs. Modern smartphones also use mostly Adreno
GPUs from Qualcomm, PowerVR GPUs from Imagination Technologies and Mali
GPUs from ARM.
Computational functions[edit]
Modern GPUs use most of their transistors to do calculations related to
3D computer graphics. In addition to the 3D hardware, today's GPUs
include basic 2D acceleration and framebuffer capabilities (usually
with a VGA compatibility mode). Newer cards such as AMD/ATI
HD5000-HD7000 even lack dedicated 2D acceleration; it has to be
emulated by 3D hardware. GPUs were initially used to accelerate the
memory-intensive work of texture mapping and rendering polygons, later
adding units to accelerate geometric calculations such as the rotation
and translation of vertices into different coordinate systems. Recent
developments in GPUs include support for programmable shaders which can
manipulate vertices and textures with many of the same operations
supported by CPUs, oversampling and interpolation techniques to reduce
aliasing, and very high-precision color spaces. Given that most of
these computations involve matrix and vector operations, engineers and
scientists have increasingly studied the use of GPUs for non-graphical
calculations; they are especially suited to other embarrassingly
parallel problems.
Several factors of the GPU's construction enter into the performance of
the card for real-time rendering. Common factors can include the size
of the connector pathways in the semiconductor device fabrication, the
clock signal frequency, and the number and size of various on-chip
memory caches. Additionally, the number of Streaming Multiprocessors
(SM) for NVidia GPUs, or Compute Units (CU) for AMD GPUs, which
describe the number of core on-silicon processor units within the GPU
chip that perform the core calculations, typically working in parallel
with other SM/CUs on the GPU. Performance of GPUs are typically
measured in floating point operations per second or FLOPS, with GPUs in
the 2010s and 2020s typically delivering performance measured in
teraflops (TFLOPS). This is an estimated performance measure as other
factors can impact the actual display rate.^[77]
With the emergence of deep learning, the importance of GPUs has
increased. In research done by Indigo, it was found that while training
deep learning neural networks, GPUs can be 250 times faster than CPUs.
There has been some level of competition in this area with ASICs, most
prominently the Tensor Processing Unit (TPU) made by Google. However,
ASICs require changes to existing code and GPUs are still very popular.
GPU accelerated video decoding and encoding[edit]
The ATI HD5470 GPU (above) features UVD 2.1 which enables it to decode
AVC and VC-1 video formats
Most GPUs made since 1995 support the YUV color space and hardware
overlays, important for digital video playback, and many GPUs made
since 2000 also support MPEG primitives such as motion compensation and
iDCT. This process of hardware accelerated video decoding, where
portions of the video decoding process and video post-processing are
offloaded to the GPU hardware, is commonly referred to as "GPU
accelerated video decoding", "GPU assisted video decoding", "GPU
hardware accelerated video decoding" or "GPU hardware assisted video
decoding".
More recent graphics cards even decode high-definition video on the
card, offloading the central processing unit. The most common APIs for
GPU accelerated video decoding are DxVA for Microsoft Windows operating
system and VDPAU, VAAPI, XvMC, and XvBA for Linux-based and UNIX-like
operating systems. All except XvMC are capable of decoding videos
encoded with MPEG-1, MPEG-2, MPEG-4 ASP (MPEG-4 Part 2), MPEG-4 AVC
(H.264 / DivX 6), VC-1, WMV3/WMV9, Xvid / OpenDivX (DivX 4), and DivX 5
codecs, while XvMC is only capable of decoding MPEG-1 and MPEG-2.
There are several dedicated hardware video decoding and encoding
solutions.
Video decoding processes that can be accelerated[edit]
The video decoding processes that can be accelerated by today's modern
GPU hardware are:
* Motion compensation (mocomp)
* Inverse discrete cosine transform (iDCT)
+ Inverse telecine 3:2 and 2:2 pull-down correction
* Inverse modified discrete cosine transform (iMDCT)
* In-loop deblocking filter
* Intra-frame prediction
* Inverse quantization (IQ)
* Variable-length decoding (VLD), more commonly known as slice-level
acceleration
* Spatial-temporal deinterlacing and automatic interlace/progressive
source detection
* Bitstream processing (Context-adaptive variable-length
coding/Context-adaptive binary arithmetic coding) and perfect pixel
positioning.
The above operations also have applications in video editing, encoding
and transcoding
GPU forms[edit]
Terminology[edit]
In personal computers, there are two main forms of GPUs. Each has many
synonyms:^[78]
* Dedicated graphics card - also called discrete.
* Integrated graphics - also called: shared graphics solutions,
integrated graphics processors (IGP), or unified memory
architecture (UMA).
Usage specific GPU[edit]
Most GPUs are designed for a specific usage, real-time 3D graphics or
other mass calculations:
1. Gaming
+ GeForce GTX, RTX
+ Nvidia Titan
+ Radeon HD, R5, R7, R9, RX, Vega and Navi series
+ Radeon VII
2. Cloud Gaming
+ Nvidia GRID
+ Radeon Sky
3. Workstation
+ Nvidia Quadro
+ Nvidia RTX
+ AMD FirePro
+ AMD Radeon Pro
+ Intel Arc Pro
4. Cloud Workstation
+ Nvidia Tesla
+ AMD FireStream
5. Artificial Intelligence training and Cloud
+ Nvidia Tesla
+ AMD Radeon Instinct
6. Automated/Driverless car
+ Nvidia Drive PX
Dedicated graphics cards[edit]
Main article: Video card
The GPUs of the most powerful class typically interface with the
motherboard by means of an expansion slot such as PCI Express (PCIe) or
Accelerated Graphics Port (AGP) and can usually be replaced or upgraded
with relative ease, assuming the motherboard is capable of supporting
the upgrade. A few graphics cards still use Peripheral Component
Interconnect (PCI) slots, but their bandwidth is so limited that they
are generally used only when a PCIe or AGP slot is not available.
A dedicated GPU is not necessarily removable, nor does it necessarily
interface with the motherboard in a standard fashion. The term
"dedicated" refers to the fact that dedicated graphics cards have RAM
that is dedicated to the card's use, not to the fact that most
dedicated GPUs are removable. Further, this RAM is usually specially
selected for the expected serial workload of the graphics card (see
GDDR). Sometimes, systems with dedicated, discrete GPUs were called
"DIS" systems,^[79] as opposed to "UMA" systems (see next section).
Dedicated GPUs for portable computers are most commonly interfaced
through a non-standard and often proprietary slot due to size and
weight constraints. Such ports may still be considered PCIe or AGP in
terms of their logical host interface, even if they are not physically
interchangeable with their counterparts.
Technologies such as SLI and NVLink by Nvidia and CrossFire by AMD
allow multiple GPUs to draw images simultaneously for a single screen,
increasing the processing power available for graphics. These
technologies, however, are increasingly uncommon, as most games do not
fully utilize multiple GPUs, as most users cannot afford
them.^[80]^[81]^[82] Multiple GPUs are still used on supercomputers
(like in Summit), on workstations to accelerate video (processing
multiple videos at once)^[83]^[84]^[85]^[86] and 3D
rendering,^[87]^[88]^[89]^[90]^[91] for VFX^[92]^[93] and for
simulations,^[94] and in AI to expedite training, as is the case with
Nvidia's lineup of DGX workstations and servers and Tesla GPUs and
Intel's upcoming Ponte Vecchio GPUs.
Integrated graphics processing unit[edit]
The position of an integrated GPU in a northbridge/southbridge system
layout
An ASRock motherboard with integrated graphics, which has HDMI, VGA and
DVI outs.
Integrated graphics processing unit (IGPU), Integrated graphics, shared
graphics solutions, integrated graphics processors (IGP) or unified
memory architecture (UMA) utilize a portion of a computer's system RAM
rather than dedicated graphics memory. IGPs can be integrated onto the
motherboard as part of the (northbridge) chipset,^[95] or on the same
die (integrated circuit) with the CPU (like AMD APU or Intel HD
Graphics). On certain motherboards,^[96] AMD's IGPs can use dedicated
sideport^[clarification needed] memory. This is a separate fixed block
of high performance memory that is dedicated for use by the GPU. In
early 2007, computers with integrated graphics account for about 90% of
all PC shipments.^[97]^[needs update] They are less costly to implement
than dedicated graphics processing, but tend to be less capable.
Historically, integrated processing was considered unfit to play 3D
games or run graphically intensive programs but could run less
intensive programs such as Adobe Flash. Examples of such IGPs would be
offerings from SiS and VIA circa 2004.^[98] However, modern integrated
graphics processors such as AMD Accelerated Processing Unit and Intel
Graphics Technology (HD, UHD, Iris, Iris Pro, Iris Plus, and Xe-LP) are
more than capable of handling 2D graphics or low stress 3D graphics.
Since the GPU computations are extremely memory-intensive, integrated
processing may find itself competing with the CPU for the relatively
slow system RAM, as it has minimal or no dedicated video memory. IGPs
can have up to 29.856 GB/s of memory bandwidth from system RAM, whereas
a graphics card may have up to 264 GB/s of bandwidth between its RAM
and GPU core. This memory bus bandwidth can limit the performance of
the GPU, though multi-channel memory can mitigate this deficiency.^[99]
Older integrated graphics chipsets lacked hardware transform and
lighting, but newer ones include it.^[100]^[101]
Hybrid graphics processing[edit]
This newer class of GPUs competes with integrated graphics in the
low-end desktop and notebook markets. The most common implementations
of this are ATI's HyperMemory and Nvidia's TurboCache.
Hybrid graphics cards are somewhat more expensive than integrated
graphics, but much less expensive than dedicated graphics cards. These
share memory with the system and have a small dedicated memory cache,
to make up for the high latency of the system RAM. Technologies within
PCI Express can make this possible. While these solutions are sometimes
advertised as having as much as 768 MB of RAM, this refers to how much
can be shared with the system memory.
Stream processing and general purpose GPUs (GPGPU)[edit]
Main articles: GPGPU and Stream processing
It is becoming increasingly common to use a general purpose graphics
processing unit (GPGPU) as a modified form of stream processor (or a
vector processor), running compute kernels. This concept turns the
massive computational power of a modern graphics accelerator's shader
pipeline into general-purpose computing power, as opposed to being
hardwired solely to do graphical operations. In certain applications
requiring massive vector operations, this can yield several orders of
magnitude higher performance than a conventional CPU. The two largest
discrete (see "Dedicated graphics cards" above) GPU designers, AMD and
Nvidia, are beginning to pursue this approach with an array of
applications. Both Nvidia and AMD have teamed with Stanford University
to create a GPU-based client for the Folding@home distributed computing
project, for protein folding calculations. In certain circumstances,
the GPU calculates forty times faster than the CPUs traditionally used
by such applications.^[102]^[103]
GPGPU can be used for many types of embarrassingly parallel tasks
including ray tracing. They are generally suited to high-throughput
type computations that exhibit data-parallelism to exploit the wide
vector width SIMD architecture of the GPU.
Furthermore, GPU-based high performance computers are starting to play
a significant role in large-scale modelling. Three of the 10 most
powerful supercomputers in the world take advantage of GPU
acceleration.^[104]
GPUs support API extensions to the C programming language such as
OpenCL and OpenMP. Furthermore, each GPU vendor introduced its own API
which only works with their cards, AMD APP SDK and CUDA from AMD and
Nvidia, respectively. These technologies allow specified functions
called compute kernels from a normal C program to run on the GPU's
stream processors. This makes it possible for C programs to take
advantage of a GPU's ability to operate on large buffers in parallel,
while still using the CPU when appropriate. CUDA is also the first API
to allow CPU-based applications to directly access the resources of a
GPU for more general purpose computing without the limitations of using
a graphics API.^[citation needed]
Since 2005 there has been interest in using the performance offered by
GPUs for evolutionary computation in general, and for accelerating the
fitness evaluation in genetic programming in particular. Most
approaches compile linear or tree programs on the host PC and transfer
the executable to the GPU to be run. Typically the performance
advantage is only obtained by running the single active program
simultaneously on many example problems in parallel, using the GPU's
SIMD architecture.^[105]^[106] However, substantial acceleration can
also be obtained by not compiling the programs, and instead
transferring them to the GPU, to be interpreted there.^[107]^[108]
Acceleration can then be obtained by either interpreting multiple
programs simultaneously, simultaneously running multiple example
problems, or combinations of both. A modern GPU can readily
simultaneously interpret hundreds of thousands of very small programs.
Some modern workstation GPUs, such as the Nvidia Quadro workstation
cards using the Volta and Turing architectures, feature dedicating
processing cores for tensor-based deep learning applications. In
Nvidia's current series of GPUs these cores are called Tensor
Cores.^[109] These GPUs usually have significant FLOPS performance
increases, utilizing 4x4 matrix multiplication and division, resulting
in hardware performance up to 128 TFLOPS in some applications.^[110]
These tensor cores are also supposed to appear in consumer cards
running the Turing architecture, and possibly in the Navi series of
consumer cards from AMD.^[111]
External GPU (eGPU)[edit]
An external GPU is a graphics processor located outside of the housing
of the computer, similar to a large external hard drive. External
graphics processors are sometimes used with laptop computers. Laptops
might have a substantial amount of RAM and a sufficiently powerful
central processing unit (CPU), but often lack a powerful graphics
processor, and instead have a less powerful but more energy-efficient
on-board graphics chip. On-board graphics chips are often not powerful
enough for playing video games, or for other graphically intensive
tasks, such as editing video or 3D animation/rendering.
Therefore, it is desirable to be able to attach a GPU to some external
bus of a notebook. PCI Express is the only bus used for this purpose.
The port may be, for example, an ExpressCard or mPCIe port (PCIe *1, up
to 5 or 2.5 Gbit/s respectively) or a Thunderbolt 1, 2, or 3 port (PCIe
*4, up to 10, 20, or 40 Gbit/s respectively). Those ports are only
available on certain notebook systems.^[112]^[113] eGPU enclosures
include their own power supply (PSU), because powerful GPUs can easily
consume hundreds of watts.^[114]
Official vendor support for external GPUs has gained traction
recently. One notable milestone was Apple's decision to officially
support external GPUs with MacOS High Sierra 10.13.4.^[115] There are
also several major hardware vendors (HP, Alienware, Razer) releasing
Thunderbolt 3 eGPU enclosures.^[116]^[117]^[118] This support has
continued to fuel eGPU implementations by enthusiasts.^[119]
Sales[edit]
In 2013, 438.3 million GPUs were shipped globally and the forecast for
2014 was 414.2 million.^[120]
See also[edit]
* Texture mapping unit (TMU)
* Render output unit (ROP)
* Brute force attack
* Computer hardware
* Computer monitor
* GPU cache
* GPU virtualization
* Manycore processor
* Physics processing unit (PPU)
* Tensor processing unit (TPU)
* Ray-tracing hardware
* Software rendering
* Vision processing unit (VPU)
* Vector processor
* Video card
* Video display controller
* Video game console
* AI accelerator
* GPU Vector Processor internal features
Hardware[edit]
* List of AMD graphics processing units
* List of Nvidia graphics processing units
* List of Intel graphics processing units
* Intel GMA
* Larrabee
* Nvidia PureVideo - the bit-stream technology from Nvidia used in
their graphics chips to accelerate video decoding on hardware GPU
with DXVA.
* SoC
* UVD (Unified Video Decoder) - the video decoding bit-stream
technology from ATI to support hardware (GPU) decode with DXVA
APIs[edit]
* OpenGL API
* DirectX Video Acceleration (DxVA) API for Microsoft Windows
operating-system.
* Mantle (API)
* Vulkan (API)
* Video Acceleration API (VA API)
* VDPAU (Video Decode and Presentation API for Unix)
* X-Video Bitstream Acceleration (XvBA), the X11 equivalent of DXVA
for MPEG-2, H.264, and VC-1
* X-Video Motion Compensation - the X11 equivalent for MPEG-2 video
codec only
Applications[edit]
* GPU cluster
* Mathematica - includes built-in support for CUDA and OpenCL GPU
execution
* Molecular modeling on GPU
* Deeplearning4j - open-source, distributed deep learning for Java
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External links[edit]
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* NVIDIA - What is GPU computing?
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