GeForce 400 series

GeForce 400 series
	Nvidia GeForce GTX 480 Point of View
Release date	April 12, 2010;14 years ago
Codename	GF10x
Architecture	Fermi
Models	GeForce series GeForce GT series; GeForce GTS series; GeForce GTX series;
Transistors	260M 40 nm (GT218 - GeForce 405 only) 585M 40 nm (GF108); 1.170M 40 nm (GF106); 1.950M 40 nm (GF104); 1.950M 40 nm (GF114); 3.200M 40 nm (GF100);
Cards
Entry-level	GT 420; GT 430
Mid-range	GT 440; GTS 450; GTX 460; GTX 465
High-end	GTX 470; GTX 480
API support
DirectX	Direct3D 12.0 (feature level 11_0); Direct3D 11.1 (feature level 10_1, GeForce 405 only) ; Shader Model 5.1 ; Shader Model 4.1 (GeForce 405 only)
OpenCL	OpenCL 1.1
OpenGL	OpenGL 4.6
History
Predecessor	GeForce 200 series
Successor	GeForce 500 series
Support status
	Unsupported

Last updated November 03, 2024

The GeForce 400 series is a series of graphics processing units developed by Nvidia, serving as the introduction of the Fermi microarchitecture. Its release was originally slated in November 2009,^[2] however, after delays, it was released on March 26, 2010, with availability following in April 2010.

Architecture

Nvidia described the Fermi microarchitecture as the next major step in its line of GPUs following the Tesla microarchitecture used since the G80. The GF100, the first Fermi-architecture product, is large: 512 stream processors, in sixteen groups of 32, and 3.0 billion transistors, manufactured by TSMC in a 40 nm process. It is Nvidia's first chip to support OpenGL 4.0 and Direct3D 11. No products with a fully enabled GF100 GPU were ever sold. The GTX 480 had one streaming multiprocessor disabled. The GTX 470 had two streaming multiprocessors and one memory controller disabled. The GTX 465 had five streaming multiprocessors and two memory controllers disabled. Consumer GeForce cards came with 256MB attached to each of the enabled GDDR5 memory controllers, for a total of 1.5, 1.25 or 1.0GB; the Tesla C2050 had 512MB on each of six controllers, and the Tesla C2070 had 1024MB per controller. Both the Tesla cards had fourteen active groups of stream processors.

The chips found in the high performance Tesla branding feature memory with optional ECC and the ability to perform one double-precision floating-point operation per cycle per core; the consumer GeForce cards are artificially driver restricted to one DP operation per four cycles. With these features, combined with support for Visual Studio and C++, Nvidia targeted professional and commercial markets, as well as use in high performance computing.

Fermi is named after Italian physicist Enrico Fermi.

Current limitations and trade-offs

The quantity of on-board SRAM per ALU actually decreased proportionally compared to the previous G200 generation, despite the increase of the L2 cache from 256kB per 240 ALUs to 768kB per 512 ALUs, since Fermi has only 32768 registers per 32 ALUs (vs. 16384 per 8 ALUs), only 48kB of shared memory per 32 ALUs (vs. 16kB per 8 ALUs), and only 16kB of cache per 32 ALUs (vs. 8kB constant cache per 8 ALUs + 24kB texture cache per 24 ALUs). Parameters such as the number of registers can be found in the CUDA Compute Capability Comparison Table in the reference manual.^[3]

History

On September 30, 2009, Nvidia released a white paper describing the architecture:^[4] the chip features 16 'Streaming Multiprocessors' each with 32 'CUDA Cores' capable of one single-precision operation per cycle or one double-precision operation every other cycle, a 40-bit virtual address space which allows the host's memory to be mapped into the chip's address space, meaning that there is only one kind of pointer and making C++ support significantly easier, and a 384-bit wide GDDR5 memory interface. As with the G80 and GT200, threads are scheduled in 'warps', sets of 32 threads each running on a single shader core. While the GT200 had 16 KB 'shared memory' associated with each shader cluster, and required data to be read through the texturing units if a cache was needed, GF100 has 64 KB of memory associated with each cluster, which can be used either as a 48 KB cache plus 16 KB of shared memory, or as a 16 KB cache plus 48 KB of shared memory, along with a 768 KB L2 cache shared by all 16 clusters.

The white paper describes the chip much more as a general purpose processor for workloads encompassing tens of thousands of threads - reminiscent of the Tera MTA architecture, though without that machine's support for very efficient random memory access - than as a graphics processor.

Many users reported high temperatures and power consumption while receiving correspondingly poor performance improves in the GeForce 400 series Fermi GPUs when compared to rival competitor AMD's Radeon HD 5000 series - leading AMD to create and release a promotional video "The Misunderstanding"^[5] to poke fun at the issue. In the video, a police unit is seen commencing a raid on a house with a large thermal profile, indicating a grow operation. However, upon entering the home it is apparent that the source of the high temperature is a Fermi GPU.^[6]^[7] It became a common joke that one could fry an egg on a Fermi GPU at full load.^[8]

Products

¹ SPs - Shader Processors - Unified Shaders: Texture mapping units: Render output units
² Each Streaming Multiprocessor (SM) in the GPU of GF100 architecture contains 32 SPs and 4 SFUs. Each Streaming Multiprocessor (SM) in the GPU of GF104/106/108 architecture contains 48 SPs and 8 SFUs. Each SP can fulfil 2 single precision fused multiply–add (FMA) operations per cycle. Each SFU can fulfil four SF operations per cycle. One FMA operation counts for two floating point operations. So the theoretical single precision peak performance, with shader count [n] and shader frequency [f, GHz], can be estimated by the following, FLOPS_sp ≈ f × n × 2 (FMA). Total Processing Power: for GF100 FLOPS_sp ≈ f × m ×(32 SPs × 2(FMA) + 4 × 4 SFUs) and for GF104/106/108 FLOPS_sp ≈ f × m × (48 SPs × 2(FMA) + 4 × 8 SFUs) or for GF100 FLOPS_sp ≈ f × n × 2.5 and for GF104/106/108 FLOPS_sp ≈ f × n × 8 / 3.^[9]

SP - Shader Processor (Unified Shader, CUDA Core), SFU - Special Function Unit, SM - Streaming Multiprocessor.

³ Each SM in the GF100 contains 4 texture filtering units for every texture address unit. The complete GF100 die contains 64 texture address units and 256 texture filtering units^[10] Each SM in the GF104/106/108 architecture contains 8 texture filtering units for every texture address unit. The complete GF104 die contains 64 texture address units and 512 texture filtering units, the complete GF106 die contains 32 texture address units and 256 texture filtering units and the complete GF108 die contains 16 texture address units and 128 texture filtering units.^[11]

All products are produced on a 40 nm fabrication process. All products support Direct3D 12.0 on a feature level 11_0, OpenGL 4.6 and OpenCL 1.1. The only exception is the GeForce 405, an OEM-only card, which is based on the GT218 (Tesla) core only supporting DirectX 11.1 with feature level 10_1, OpenGL 3.3 and no OpenCL support, and is the only card in the GeForce 400 range not based on the Fermi microarchitecture. By the parameters, the GeForce 405 is identical to the GeForce 310, also an OEM only card, which is itself based on the GeForce 210. All products have a single DB15 VGA connector on a full height and full length card, except as listed otherwise.

On November 8, 2010, Nvidia released the GF110 chip, along with the GTX 580 (480's replacement). It is a redesigned GF100 chip, which uses significantly less power. This allowed Nvidia to enable all 16 SMs (all 16 cores), which was previously impossible on the GF100 "Nvidia GeForce GTX 580". Various features of the GF100 architecture were only available on the more expensive Quadro and Tesla series of cards.^[12] For the GeForce consumer products, double precision performance is a quarter of that of the "full" Fermi architecture. Error checking and correcting memory (ECC) also does not operate on consumer cards.^[13] The GF100 cards provide Compute Capability 2.0, while the GF104/106/108 cards provide Compute Capability 2.1.

Discontinued support

Nvidia announced that after Release 390 drivers, it will no longer release 32-bit drivers for 32-bit operating systems.^[14]

Nvidia announced in April 2018 that Fermi will move to legacy driver support status and be maintained until January 2019.^[15]

Chipset table

Model	Launch	Code name	Fab (nm)	Transistors (million)	Die size (mm²)	SM count	Core config^{[lower-alpha 1]}^{[lower-alpha 2]}	Clock rate			Fillrate		Memory configuration				Supported API version				Processing power (GFLOPS)^{[lower-alpha 3]}		TDP (Watts)^{[lower-alpha 4]}	Release Price (USD)
Model	Launch	Code name	Fab (nm)	Transistors (million)	Die size (mm²)	SM count	Core config^{[lower-alpha 1]}^{[lower-alpha 2]}	Core (MHz)	Shader (MHz)	Memory (MHz)	Pixel (GP/s)	Texture (GT/s)	Size (MB)	Bandwidth (GB/s)	DRAM type	Bus width (bit)	Vulkan	Direct3D	OpenGL	OpenCL ^{[lower-alpha 5]}	Single precision	Double precision	TDP (Watts)^{[lower-alpha 4]}	Release Price (USD)
GeForce 405^{[lower-alpha 6]}	September 16, 2011	GT216 GT218	40 nm	486 260	100 57	1	48:16:8 16:8:4	475 589	1100 1402	800 790	3.8 2.36	7.6 4.71	512 1024	12.6	DDR3	64	n/a^[18]	11.1 (FL 10_1)	3.3	1.1	105.6 44.86	Unknown	30.5	OEM
GeForce GT 420	September 3, 2010	GF108	TSMC 40 nm	585	116	1	48:4:4	700	1400	1800	2.8	2.8	512	28.8	GDDR3	128		12 (FL 11_0)	4.6	1.1	134.4	Unknown	50
GeForce GT 430	October 11, 2010	GF108 GF108-300-A1				2	96:16:4			1600 1800		11.2	512	25.6 28.8		128				1.2	268.8	Unknown	60
										1800			512 1024 2048	28.8		128				1.1	268.8	Unknown	49	$79
										1300			512 1024 2048	10.4		64					268.8	Unknown	49	$79
GeForce GT 440	February 1, 2011	GF108						810	1620	1800 3200	3.2	12.9	512 1024	28.8 51.2	GDDR3 GDDR5	128					311.04	Unknown	65	$100
GeForce GT 440	October 11, 2010	GF106		1170	238	3	144:24:24	594	1189	1600 1800	4.86	19.44	1536 3072	43.2	DDR3	192					342.43	Unknown	56	OEM
GeForce GTS 450	October 11, 2010	GF106				3	144:24:24	790	1580	4000	4.7	18.9	1536	96.0	GDDR5	192					455.04	Unknown	106	OEM
GeForce GTS 450	September 13, 2010 March 15, 2011	GF106-250 GF116-200				4	192:32:16	783	1566	1200-1600 (GDDR3) 3608 (GDDR5)	6.2	25.0	512 1024	57.7		128					601.34	Unknown	106	$129
GeForce GTX 460 SE	November 15, 2010	GF104-225-A1		1950	332	6	288:48:32	650	1300	3400	7.8	31.2	1024	108.8		256					748.8	Unknown	150	$160
GeForce GTX 460	October 11, 2010	GF104				7	336:56:32	650	1300	3400	9.1	36.4	1024	108.8		256					873.6	Unknown		OEM
	July 12, 2010	GF104-300-KB-A1					336:56:24	675	1350	3600	9.4	37.8	768	86.4		192					907.2	Unknown		$199
	July 12, 2010	GF104-300-KB-A1					336:56:32	675	1350	3600	9.4	37.8	1024 2048	115.2		256					907.2	Unknown	160	$229
	September 24, 2011	GF114					336:56:24	779	1557	4008	10.9	43.6	1024	96.2		192					1045.6	Unknown	160	$199
GeForce GTX 465	May 31, 2010	GF100-030-A3		3000^[19]	529	11	352:44:32	608	1215	3206	13.3	26.7	1024	102.7		256				1.2	855.36	106.92	200^{[lower-alpha 4]}	$279
GeForce GTX 470	March 26, 2010	GF100-275-A3				14	448:56:40	608	1215	3348	17.0	34.0	1280	133.9		320					1088.64	136.08	215^{[lower-alpha 4]}	$349
GeForce GTX 480	March 26, 2010	GF100-375-A3				15	480:60:48	701	1401	3696	21.0	42.0	1536	177.4		384					1344.96	168.12	250^{[lower-alpha 4]}	$499
Model	Launch	Code name	Fab (nm)	Transistors (million)	Die size (mm²)	SM count	Core config^{[lower-alpha 1]}^{[lower-alpha 2]}	Clock rate			Fillrate		Memory configuration				Supported API version				Processing power (GFLOPS)^{[lower-alpha 3]}		TDP (Watts)^{[lower-alpha 4]}	Release Price (USD)
Model	Launch	Code name	Fab (nm)	Transistors (million)	Die size (mm²)	SM count	Core config^{[lower-alpha 1]}^{[lower-alpha 2]}	Core (MHz)	Shader (MHz)	Memory (MHz)	Pixel (GP/s)	Texture (GT/s)	Size (MB)	Bandwidth (GB/s)	DRAM type	Bus width (bit)	Vulkan	Direct3D	OpenGL	OpenCL ^{[lower-alpha 5]}	Single precision	Double precision	TDP (Watts)^{[lower-alpha 4]}	Release Price (USD)

1 2 Unified shaders: texture mapping units: render output units
1 2 Each SM in the GF100 contains 4 texture filtering units for every texture address unit. The complete GF100 die contains 64 texture address units and 256 texture filtering units.^[10] Each SM in the GF104/106/108 architecture contains 8 texture filtering units for every texture address unit but has doubled both addressing and filtering units. The complete GF104 die also contains 64 texture address units and 512 texture filtering units despite the halved SM count, the complete GF106 die contains 32 texture address units and 256 texture filtering units and the complete GF108 die contains 16 texture address units and 128 texture filtering units.^[16]
1 2 To calculate the processing power see Fermi (microarchitecture)#Performance.
1 2 3 4 5 Note that while GTX 460's TDP is comparable to that of AMD's HD5000 series, GF100-based cards (GTX 480/470/465) are rated much lower but pull significantly more power, e.g. GTX 480 with 250W TDP consumes More power than an HD 5970 with 297W TDP.^[17]
1 2 The 400 series is the only non-OEM family from GeForce 9 to 700 series not to include an official dual-GPU system. However, on March 18, 2011, EVGA released the first single-PCB card with dual 460s on board. The card came with 2048 MB of memory at 3600 MHz and 672 shader processors at 1400 MHz and was offered at the MSRP of $429.
↑ The GeForce 405 card is a rebranded GeForce 310 which itself is a rebranded GeForce 210.

Gallery

Palit GeForce GTX460
NVIDIA GeForce GTX 480 Founders Edition

Notes

David Kanter (September 30, 2009). "Inside Fermi: Nvidia's HPC Push". realworldtech.com. Retrieved December 16, 2010.

Related Research Articles

GeForce is a brand of graphics processing units (GPUs) designed by Nvidia and marketed for the performance market. As of the GeForce 40 series, there have been eighteen iterations of the design. The first GeForce products were discrete GPUs designed for add-on graphics boards, intended for the high-margin PC gaming market, and later diversification of the product line covered all tiers of the PC graphics market, ranging from cost-sensitive GPUs integrated on motherboards, to mainstream add-in retail boards. Most recently, GeForce technology has been introduced into Nvidia's line of embedded application processors, designed for electronic handhelds and mobile handsets.

<span class="mw-page-title-main">GeForce 7 series</span> Series of GPUs by Nvidia

The GeForce 7 series is the seventh generation of Nvidia's GeForce line of graphics processing units. This was the last series available on AGP cards.

The GeForce 8 series is the eighth generation of Nvidia's GeForce line of graphics processing units. The third major GPU architecture developed by Nvidia, Tesla represents the company's first unified shader architecture.

The GeForce 9 series is the ninth generation of Nvidia's GeForce line of graphics processing units, the first of which was released on February 21, 2008. The products are based on an updated Tesla microarchitecture, adding PCI Express 2.0 support, improved color and z-compression, and built on a 65 nm process, later using 55 nm process to reduce power consumption and die size.

In the field of 3D computer graphics, the unified shader model refers to a form of shader hardware in a graphical processing unit (GPU) where all of the shader stages in the rendering pipeline have the same capabilities. They can all read textures and buffers, and they use instruction sets that are almost identical.

Tesla is the codename for a GPU microarchitecture developed by Nvidia, and released in 2006, as the successor to Curie microarchitecture. It was named after the pioneering electrical engineer Nikola Tesla. As Nvidia's first microarchitecture to implement unified shaders, it was used with GeForce 8 series, GeForce 9 series, GeForce 100 series, GeForce 200 series, and GeForce 300 series of GPUs, collectively manufactured in 90 nm, 80 nm, 65 nm, 55 nm, and 40 nm. It was also in the GeForce 405 and in the Quadro FX, Quadro x000, Quadro NVS series, and Nvidia Tesla computing modules.

The GeForce 200 series is a series of Tesla-based GeForce graphics processing units developed by Nvidia.

The GeForce 500 series is a series of graphics processing units developed by Nvidia, as a refresh of the Fermi based GeForce 400 series. It was first released on November 9, 2010 with the GeForce GTX 580.

The GeForce 600 series is a series of graphics processing units developed by Nvidia, first released in 2012. It served as the introduction of the Kepler architecture. It is succeeded by the GeForce 700 series.

The GeForce 700 series is a series of graphics processing units developed by Nvidia. While mainly a refresh of the Kepler microarchitecture, some cards use Fermi (GF) and later cards use Maxwell (GM). GeForce 700 series cards were first released in 2013, starting with the release of the GeForce GTX Titan on February 19, 2013, followed by the GeForce GTX 780 on May 23, 2013. The first mobile GeForce 700 series chips were released in April 2013.

Fermi is the codename for a graphics processing unit (GPU) microarchitecture developed by Nvidia, first released to retail in April 2010, as the successor to the Tesla microarchitecture. It was the primary microarchitecture used in the GeForce 400 series and 500 series. All desktop Fermi GPUs were manufactured in 40nm, mobile Fermi GPUs in 40nm and 28nm. Fermi is the oldest microarchitecture from Nvidia that receives support for Microsoft's rendering API Direct3D 12 feature_level 11.

The GeForce 800M series is a family of graphics processing units by Nvidia for laptop PCs. It consists of rebrands of mobile versions of the GeForce 700 series and some newer chips that are lower end compared to the rebrands.

<span class="mw-page-title-main">GeForce 900 series</span> Series of GPUs by Nvidia

The GeForce 900 series is a family of graphics processing units developed by Nvidia, succeeding the GeForce 700 series and serving as the high-end introduction to the Maxwell microarchitecture, named after James Clerk Maxwell. They are produced with TSMC's 28 nm process.

The GeForce 10 series is a series of graphics processing units developed by Nvidia, initially based on the Pascal microarchitecture announced in March 2014. This design series succeeded the GeForce 900 series, and is succeeded by the GeForce 16 series and GeForce 20 series using the Turing microarchitecture.

<span class="mw-page-title-main">Kepler (microarchitecture)</span> GPU microarchitecture by Nvidia

Kepler is the codename for a GPU microarchitecture developed by Nvidia, first introduced at retail in April 2012, as the successor to the Fermi microarchitecture. Kepler was Nvidia's first microarchitecture to focus on energy efficiency. Most GeForce 600 series, most GeForce 700 series, and some GeForce 800M series GPUs were based on Kepler, all manufactured in 28 nm. Kepler found use in the GK20A, the GPU component of the Tegra K1 SoC, and in the Quadro Kxxx series, the Quadro NVS 510, and Tesla computing modules.

<span class="mw-page-title-main">Maxwell (microarchitecture)</span> GPU microarchitecture by Nvidia

Maxwell is the codename for a GPU microarchitecture developed by Nvidia as the successor to the Kepler microarchitecture. The Maxwell architecture was introduced in later models of the GeForce 700 series and is also used in the GeForce 800M series, GeForce 900 series, and Quadro Mxxx series, as well as some Jetson products.

<span class="mw-page-title-main">Pascal (microarchitecture)</span> GPU microarchitecture by Nvidia

Pascal is the codename for a GPU microarchitecture developed by Nvidia, as the successor to the Maxwell architecture. The architecture was first introduced in April 2016 with the release of the Tesla P100 (GP100) on April 5, 2016, and is primarily used in the GeForce 10 series, starting with the GeForce GTX 1080 and GTX 1070, which were released on May 27, 2016, and June 10, 2016, respectively. Pascal was manufactured using TSMC's 16 nm FinFET process, and later Samsung's 14 nm FinFET process.

Volta is the codename, but not the trademark, for a GPU microarchitecture developed by Nvidia, succeeding Pascal. It was first announced on a roadmap in March 2013, although the first product was not announced until May 2017. The architecture is named after 18th–19th century Italian chemist and physicist Alessandro Volta. It was Nvidia's first chip to feature Tensor Cores, specially designed cores that have superior deep learning performance over regular CUDA cores. The architecture is produced with TSMC's 12 nm FinFET process. The Ampere microarchitecture is the successor to Volta.

Turing is the codename for a graphics processing unit (GPU) microarchitecture developed by Nvidia. It is named after the prominent mathematician and computer scientist Alan Turing. The architecture was first introduced in August 2018 at SIGGRAPH 2018 in the workstation-oriented Quadro RTX cards, and one week later at Gamescom in consumer GeForce 20 series graphics cards. Building on the preliminary work of Volta, its HPC-exclusive predecessor, the Turing architecture introduces the first consumer products capable of real-time ray tracing, a longstanding goal of the computer graphics industry. Key elements include dedicated artificial intelligence processors and dedicated ray tracing processors. Turing leverages DXR, OptiX, and Vulkan for access to ray tracing. In February 2019, Nvidia released the GeForce 16 series GPUs, which utilizes the new Turing design but lacks the RT and Tensor cores.

References

↑ Killian, Zak (July 3, 2017). "Nvidia finally lets Fermi GPU owners enjoy DirectX 12". Tech Report. Retrieved July 4, 2017.
↑ "OFFICIAL: NVIDIA says GT300 on schedule for Q4 2009, yields are fine - Bright Side Of News*". Brightsideofnews.com. September 25, 2009. Retrieved September 20, 2010.
↑ Compute Capability Comparison Table in "Page 147-148, Appendix G.1, CUDA 3.1 official reference manual" (PDF). Page 97 in Appendix A lists the older NVIDIA GPUs and shows all G200 series to be compute capability 1.3, while Fermi-based cards have compute capability 2.x (page 14, Section 2.5).
↑ NVIDIA Fermi Compute Architecture Whitepaper nvidia.com
↑ Archived at Ghostarchive and the Wayback Machine : "The Misunderstanding - Presented by AMD". YouTube .
↑ "AMD Pokes Fun of NVIDIA's Fermi GPU Heat Output in "The Misunderstanding" Video". August 9, 2010.
↑ "NVIDIA Fermi GF100 GPUs - Too little, too late, too hot, and too expensive". ZDNet .
↑ "GeForce GTX 480: Is it Hot Enough to Fry an Egg?". Archived from the original on September 20, 2019. Retrieved September 20, 2019.
↑ siliconmadness.com (2010). "Nvidia Announces Tesla 20 Series". Archived from the original on May 21, 2010.
1 2 "The GF100 Recap - Nvidia's GeForce GTX 480 and GTX 470: 6 Months Late, Was It Worth the Wait?". Anandtech.com. Archived from the original on August 5, 2011. Retrieved December 11, 2015.
↑ Smith, Ryan. "NVIDIA's GeForce GTX 460: The $200 King". www.anandtech.com. Retrieved May 16, 2024.
↑ "NVIDIA Official Forums". NVIDIA. Retrieved May 16, 2024.
↑ "NVIDIA Tesla C2xxx webpage"., note from the description one may infer that on Teslas, ECC may be switched on and off using 1/8 of existing on-board memory, unlike standard ECC memory modules which requires 1/8 extra memory chips (that is, one extra chip to be mounted on the printed circuit board for every 8).
↑ "Support Plan for 32-bit and 64-bit Operating Systems | NVIDIA".
↑ "Support Plan for Fermi series GeForce GPUs | NVIDIA".
↑ "GF104: Nvidia Goes Superscalar - Nvidia's GeForce GTX 460: The $200 King". Anandtech.com. Archived from the original on December 22, 2015. Retrieved December 11, 2015.
↑ "GeForce GTX 480 And 470: From Fermi And GF100 To Actual Cards!". Tomshardware.com. March 27, 2010. Retrieved December 11, 2015.
↑ "The Khronos Group". May 31, 2022.
↑ "Nvidia Fermi Compute Architecture Whitepaper" (PDF). Archived (PDF) from the original on November 22, 2009. Retrieved April 17, 2010. ( 855KB), page 11 of 22

External links

This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.

[geforce_400_1-16] 1 2 Unified shaders: texture mapping units: render output units

[geforce_400_3-18] 1 2 Each SM in the GF100 contains 4 texture filtering units for every texture address unit. The complete GF100 die contains 64 texture address units and 256 texture filtering units.^[10] Each SM in the GF104/106/108 architecture contains 8 texture filtering units for every texture address unit but has doubled both addressing and filtering units. The complete GF104 die also contains 64 texture address units and 512 texture filtering units despite the halved SM count, the complete GF106 die contains 32 texture address units and 256 texture filtering units and the complete GF108 die contains 16 texture address units and 128 texture filtering units.^[16]

[geforce_400_2-19] 1 2 To calculate the processing power see Fermi (microarchitecture)#Performance.

[geforce_400_4-21] 1 2 3 4 5 Note that while GTX 460's TDP is comparable to that of AMD's HD5000 series, GF100-based cards (GTX 480/470/465) are rated much lower but pull significantly more power, e.g. GTX 480 with 250W TDP consumes More power than an HD 5970 with 297W TDP.^[17]

[geforce_400_6-22] 1 2 The 400 series is the only non-OEM family from GeForce 9 to 700 series not to include an official dual-GPU system. However, on March 18, 2011, EVGA released the first single-PCB card with dual 460s on board. The card came with 2048 MB of memory at 3600 MHz and 672 shader processors at 1400 MHz and was offered at the MSRP of $429.

[geforce_400_7-23] The GeForce 405 card is a rebranded GeForce 310 which itself is a rebranded GeForce 210.

[1] Killian, Zak (July 3, 2017). "Nvidia finally lets Fermi GPU owners enjoy DirectX 12". Tech Report. Retrieved July 4, 2017.

[2] "OFFICIAL: NVIDIA says GT300 on schedule for Q4 2009, yields are fine - Bright Side Of News*". Brightsideofnews.com. September 25, 2009. Retrieved September 20, 2010.

[3] Compute Capability Comparison Table in "Page 147-148, Appendix G.1, CUDA 3.1 official reference manual" (PDF). Page 97 in Appendix A lists the older NVIDIA GPUs and shows all G200 series to be compute capability 1.3, while Fermi-based cards have compute capability 2.x (page 14, Section 2.5).

[4] NVIDIA Fermi Compute Architecture Whitepaper nvidia.com

[5] Archived at Ghostarchive and the Wayback Machine : "The Misunderstanding - Presented by AMD". YouTube .

[6] "AMD Pokes Fun of NVIDIA's Fermi GPU Heat Output in "The Misunderstanding" Video". August 9, 2010.

[7] "NVIDIA Fermi GF100 GPUs - Too little, too late, too hot, and too expensive". ZDNet .

[8] "GeForce GTX 480: Is it Hot Enough to Fry an Egg?". Archived from the original on September 20, 2019. Retrieved September 20, 2019.

[nvidiatesla-siliconmadness-9] siliconmadness.com (2010). "Nvidia Announces Tesla 20 Series". Archived from the original on May 21, 2010.

[anandtech.com-10] 1 2 "The GF100 Recap - Nvidia's GeForce GTX 480 and GTX 470: 6 Months Late, Was It Worth the Wait?". Anandtech.com. Archived from the original on August 5, 2011. Retrieved December 11, 2015.

[11] Smith, Ryan. "NVIDIA's GeForce GTX 460: The $200 King". www.anandtech.com. Retrieved May 16, 2024.

[12] "NVIDIA Official Forums". NVIDIA. Retrieved May 16, 2024.

[13] "NVIDIA Tesla C2xxx webpage"., note from the description one may infer that on Teslas, ECC may be switched on and off using 1/8 of existing on-board memory, unlike standard ECC memory modules which requires 1/8 extra memory chips (that is, one extra chip to be mounted on the printed circuit board for every 8).

[14] "Support Plan for 32-bit and 64-bit Operating Systems | NVIDIA".

[15] "Support Plan for Fermi series GeForce GPUs | NVIDIA".

[17] "GF104: Nvidia Goes Superscalar - Nvidia's GeForce GTX 460: The $200 King". Anandtech.com. Archived from the original on December 22, 2015. Retrieved December 11, 2015.

[20] "GeForce GTX 480 And 470: From Fermi And GF100 To Actual Cards!". Tomshardware.com. March 27, 2010. Retrieved December 11, 2015.

[vulkandrv-24] "The Khronos Group". May 31, 2022.

[25] "Nvidia Fermi Compute Architecture Whitepaper" (PDF). Archived (PDF) from the original on November 22, 2009. Retrieved April 17, 2010. ( 855KB), page 11 of 22

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

[15]

[lower-alpha 1]

[lower-alpha 2]

[lower-alpha 3]

[lower-alpha 4]

[lower-alpha 5]

[lower-alpha 6]

[18]

[19]

[16]

[17]