Nvidia_Tesla
Nvidia Tesla
Nvidia's line of general purpose GPUs
This article is about GPGPU cards. For the GPU microarchitecture, see Tesla (microarchitecture).
"Tesla P100" redirects here. For the line of performance cars by Tesla Motors (P100D), see Tesla Model S and Tesla Model X.
Nvidia Tesla is the former name for a line of products developed by Nvidia targeted at stream processing or general-purpose graphics processing units (GPGPU), named after pioneering electrical engineer Nikola Tesla. Its products began using GPUs from the G80 series, and have continued to accompany the release of new chips. They are programmable using the CUDA or OpenCL APIs.
Quick Facts Manufacturer, Introduced ...
| Manufacturer | Nvidia |
|---|---|
| Introduced | May 2, 2007; 16 years ago (2007-05-02) |
| Discontinued | The brand Tesla discontinued on May 2020; 3 years ago (2020-05), now branded as Nvidia Data Center GPUs |
| Type | General purpose graphics cards |
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The Nvidia Tesla product line competed with AMD's Radeon Instinct and Intel Xeon Phi lines of deep learning and GPU cards.
Nvidia retired the Tesla brand in May 2020, reportedly because of potential confusion with the brand of cars.[1] Its new GPUs are branded Nvidia Data Center GPUs[2] as in the Ampere-based A100 GPU.[3]
Nvidia DGX servers feature Nvidia GPGPUs.
Offering computational power much greater than traditional microprocessors, the Tesla products targeted the high-performance computing market.[4] As of 2012[update], Nvidia Teslas power some of the world's fastest supercomputers, including Summit at Oak Ridge National Laboratory and Tianhe-1A, in Tianjin, China.
Tesla cards have four times the double precision performance of a Fermi-based Nvidia GeForce card of similar single precision performance.[citation needed] Unlike Nvidia's consumer GeForce cards and professional Nvidia Quadro cards, Tesla cards were originally unable to output images to a display. However, the last Tesla C-class products included one Dual-Link DVI port.[5]
Tesla products are primarily used in simulations and in large-scale calculations (especially floating-point calculations), and for high-end image generation for professional and scientific fields.[6]
In 2013, the defense industry accounted for less than one-sixth of Tesla sales, but Sumit Gupta predicted increasing sales to the geospatial intelligence market.[7]
More information Model, Micro-architecture ...
| Model | Micro- architecture |
Launch | Chips | Core clock (MHz) |
Shaders | Memory | Processing power (GFLOPS)[lower-alpha 1] | CUDA compute capability[lower-alpha 2] |
TDP (W) |
Notes, form factor | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CUDA cores (total) |
Base clock (MHz) | Max boost clock (MHz)[lower-alpha 3] |
Bus type | Bus width (bit) |
Size (GB) |
Clock (MT/s) |
Bandwidth (GB/s) |
Half precision Tensor Core FP32 Accumulate |
Single precision (MAD or FMA) |
Double precision (FMA) | ||||||||
| C870 GPU Computing Module[lower-alpha 4] | Tesla | May 2, 2007 | 1× G80 | 600 | 128 | 1,350 | — | GDDR3 | 384 | 1.5 | 1,600 | 76.8 | No | 345.6 | No | 1.0 | 170.9 | Internal PCIe GPU (full-height, dual-slot) |
| D870 Deskside Computer[lower-alpha 4] | May 2, 2007 | 2× G80 | 600 | 256 | 1,350 | — | GDDR3 | 2× 384 | 2× 1.5 | 1,600 | 2× 76.8 | No | 691.2 | No | 1.0 | 520 | Deskside or 3U rack-mount external GPUs | |
| S870 GPU Computing Server[lower-alpha 4] | May 2, 2007 | 4× G80 | 600 | 512 | 1,350 | — | GDDR3 | 4× 384 | 4× 1.5 | 1,600 | 4× 76.8 | No | 1382.4 | No | 1.0 | 1U rack-mount external GPUs, connect via 2× PCIe (×16) | ||
| C1060 GPU Computing Module[lower-alpha 5] | April 9, 2009 | 1× GT200 | 602 | 240 | 1,296[9] | — | GDDR3 | 512 | 4 | 1,600 | 102.4 | No | 622.08 | 77.76 | 1.3 | 187.8 | Internal PCIe GPU (full-height, dual-slot) | |
| S1070 GPU Computing Server "400 configuration"[lower-alpha 5] | June 1, 2008 | 4× GT200 | 602 | 960 | 1296 | — | GDDR3 | 4× 512 | 4× 4 | 1,538.4 | 4× 98.5 | No | 2,488.3 | 311.0 | 1.3 | 800 | 1U rack-mount external GPUs, connect via 2× PCIe (×8 or ×16) | |
| S1070 GPU Computing Server "500 configuration"[lower-alpha 5] | 1,440 | — | No | 2,764.8 | 345.6 | |||||||||||||
| S1075 GPU Computing Server[lower-alpha 5][10] | June 1, 2008 | 4× GT200 | 602 | 960 | 1,440 | — | GDDR3 | 4× 512 | 4× 4 | 1,538.4 | 4× 98.5 | No | 2,764.8 | 345.6 | 1.3 | 1U rack-mount external GPUs, connect via 1× PCIe (×8 or ×16) | ||
| Quadro Plex 2200 D2 Visual Computing System[lower-alpha 6] | July 25, 2008 | 2× GT200GL | 648 | 480 | 1,296 | — | GDDR3 | 2× 512 | 2× 4 | 1,600 | 2× 102.4 | No | 1,244.2 | 155.5 | 1.3 | Deskside or 3U rack-mount external GPUs with 4 dual-link DVI outputs | ||
| Quadro Plex 2200 S4 Visual Computing System[lower-alpha 6] | July 25, 2008 | 4× GT200GL | 648 | 960 | 1,296 | — | GDDR3 | 4× 512 | 4× 4 | 1,600 | 4× 102.4 | No | 2,488.3 | 311.0 | 1.3 | 1,200 | 1U rack-mount external GPUs, connect via 2× PCIe (×8 or ×16) | |
| C2050 GPU Computing Module[11] | Fermi | July 25, 2011 | 1× GF100 | 575 | 448 | 1,150 | — | GDDR5 | 384 | 3[lower-alpha 7] | 3000 | 144 | No | 1,030.4 | 515.2 | 2.0 | 247 | Internal PCIe GPU (full-height, dual-slot) |
| M2050 GPU Computing Module[12] | July 25, 2011 | — | 3,092 | 148.4 | No | 225 | ||||||||||||
| C2070 GPU Computing Module[11] | July 25, 2011 | 1× GF100 | 575 | 448 | 1,150 | — | GDDR5 | 384 | 6[lower-alpha 7] | 3,000 | 144 | No | 1,030.4 | 515.2 | 2.0 | 247 | Internal PCIe GPU (full-height, dual-slot) | |
| C2075 GPU Computing Module[13] | July 25, 2011 | — | 3,000 | 144 | No | 225 | ||||||||||||
| M2070/M2070Q GPU Computing Module[14] | July 25, 2011 | — | 3,132 | 150.336 | No | 225 | ||||||||||||
| M2090 GPU Computing Module[15] | July 25, 2011 | 1× GF110 | 650 | 512 | 1,300 | — | GDDR5 | 384 | 6[lower-alpha 7] | 3700 | 177.6 | No | 1,331.2 | 665.6 | 2.0 | 225 | Internal PCIe GPU (full-height, dual-slot) | |
| S2050 GPU Computing Server | July 25, 2011 | 4× GF100 | 575 | 1792 | 1150 | — | GDDR5 | 4× 384 | 4× 3[lower-alpha 7] | 3 | 4× 148.4 | No | 4,121.6 | 2,060.8 | 2.0 | 900 | 1U rack-mount external GPUs, connect via 2× PCIe (×8 or ×16) | |
| S2070 GPU Computing Server | — | 4× 6[lower-alpha 7] | No | |||||||||||||||
| K10 GPU accelerator[16] | Kepler | May 1, 2012 | 2× GK104 | — | 3,072 | 745 | ? | GDDR5 | 2× 256 | 2× 4 | 5,000 | 2× 160 | No | 4,577 | 190.7 | 3.0 | 225 | Internal PCIe GPU (full-height, dual-slot) |
| K20 GPU accelerator[17][18] | November 12, 2012 | 1× GK110 | — | 2,496 | 706 | 758 | GDDR5 | 320 | 5 | 5,200 | 208 | No | 3,524 | 1,175 | 3.5 | 225 | Internal PCIe GPU (full-height, dual-slot) | |
| K20X GPU accelerator[19] | November 12, 2012 | 1× GK110 | — | 2,688 | 732 | ? | GDDR5 | 384 | 6 | 5,200 | 250 | No | 3,935 | 1,312 | 3.5 | 235 | Internal PCIe GPU (full-height, dual-slot) | |
| K40 GPU accelerator[20] | October 8, 2013 | 1× GK110B | — | 2,880 | 745 | 875 | GDDR5 | 384 | 12[lower-alpha 7] | 6,000 | 288 | No | 4,291–5,040 | 1,430–1,680 | 3.5 | 235 | Internal PCIe GPU (full-height, dual-slot) | |
| K80 GPU accelerator[21] | November 17, 2014 | 2× GK210 | — | 4,992 | 560 | 875 | GDDR5 | 2× 384 | 2× 12 | 5,000 | 2× 240 | No | 5,591–8,736 | 1,864–2,912 | 3.7 | 300 | Internal PCIe GPU (full-height, dual-slot) | |
| M4 GPU accelerator[22][23] | Maxwell | November 10, 2015 | 1× GM206 | — | 1,024 | 872 | 1,072 | GDDR5 | 128 | 4 | 5,500 | 88 | No | 1,786–2,195 | 55.81–68.61 | 5.2 | 50–75 | Internal PCIe GPU (half-height, single-slot) |
| M6 GPU accelerator[24] | August 30, 2015 | 1× GM204-995-A1 | — | 1536 | 722 | 1,051 | GDDR5 | 256 | 8 | 4,600 | 147.2 | No | 2,218–3,229 | 69.3–100.9 | 5.2 | 75–100 | Internal MXM GPU | |
| M10 GPU accelerator[25] | 4× GM107 | — | 2,560 | 1,033 | ? | GDDR5 | 4× 128 | 4× 8 | 5,188 | 4× 83 | No | 5,289 | 165.3 | 5.2 | 225 | Internal PCIe GPU (full-height, dual-slot) | ||
| M40 GPU accelerator[23][26] | November 10, 2015 | 1× GM200 | — | 3,072 | 948 | 1,114 | GDDR5 | 384 | 12 or 24 | 6,000 | 288 | No | 5,825–6,844 | 182.0–213.9 | 5.2 | 250 | Internal PCIe GPU (full-height, dual-slot) | |
| M60 GPU accelerator[27] | August 30, 2015 | 2× GM204-895-A1 | — | 4,096 | 899 | 1,178 | GDDR5 | 2× 256 | 2× 8 | 5,000 | 2× 160 | No | 7,365–9,650 | 230.1–301.6 | 5.2 | 225–300 | Internal PCIe GPU (full-height, dual-slot) | |
| P4 GPU accelerator[28] | Pascal | September 13, 2016 | 1× GP104 | — | 2,560 | 810 | 1,063 | GDDR5 | 256 | 8 | 6,000 | 192.0 | No | 4,147–5,443 | 129.6–170.1 | 6.1 | 50-75 | PCIe card |
| P6 GPU accelerator[29][30] | March 24, 2017 | 1× GP104-995-A1 | — | 2,048 | 1,012 | 1,506 | GDDR5 | 256 | 16 | 3,003 | 192.2 | No | 6,169 | 192.8 | 6.1 | 90 | MXM card | |
| P40 GPU accelerator[28] | September 13, 2016 | 1× GP102 | — | 3,840 | 1,303 | 1,531 | GDDR5 | 384 | 24 | 7,200 | 345.6 | No | 10,007–11,758 | 312.7–367.4 | 6.1 | 250 | PCIe card | |
| P100 GPU accelerator (mezzanine)[31][32] | April 5, 2016 | 1× GP100-890-A1 | — | 3,584 | 1,328 | 1,480 | HBM2 | 4,096 | 16 | 1,430 | 732 | No | 9,519–10,609 | 4,760–5,304 | 6.0 | 300 | SXM card | |
| P100 GPU accelerator (16 GB card)[33] | June 20, 2016 | 1× GP100 | — | 1126 | 1303 | No | 8,071‒9,340 | 4,036‒4,670 | 250 | PCIe card | ||||||||
| P100 GPU accelerator (12 GB card)[33] | June 20, 2016 | — | 3,072 | 12 | 549 | No | 8,071‒9,340 | 4,036‒4,670 | ||||||||||
| V100 GPU accelerator (mezzanine)[34][35][36] | Volta | May 10, 2017 | 1× GV100-895-A1 | — | 5120 | Unknown | 1,455 | HBM2 | 4,096 | 16 or 32 | 1,750 | 900 | 119,192 | 14,899 | 7,450 | 7.0 | 300 | SXM card |
| V100 GPU accelerator (PCIe card)[34][35][36] | June 21, 2017 | 1× GV100 | — | Unknown | 1,370 | 112,224 | 14,028 | 7,014 | 250 | PCIe card | ||||||||
| V100 GPU accelerator (PCIe FHHL card) | March 27, 2018 | 1× GV100 | — | 937 | 1,290 | 16 | 1,620 | 829.44 | 105,680 | 13,210 | 6,605 | 250 | PCIe FHHL card | |||||
| T4 GPU accelerator (PCIe card)[37][38] | Turing | September 12, 2018 | 1× TU104-895-A1 | — | 2,560 | 585 | 1,590 | GDDR6 | 256 | 16 | 5,000 | 320 | 64,800 | 8,100 | Unknown | 7.5 | 70 | PCIe card |
| A2 GPU accelerator (PCIe card)[39] | Ampere | November 10, 2021 | 1× GA107 | — | 1,280 | 1,440 | 1,770 | GDDR6 | 128 | 16 | 6,252 | 200 | 18,124 | 4,531 | 140 | 8.6 | 40-60 | PCIe card (half height, single-slot) |
| A10 GPU accelerator (PCIe card)[40] | April 12, 2021 | 1× GA102-890-A1 | — | 9,216 | 885 | 1,695 | GDDR6 | 384 | 24 | 6,252 | 600 | 124,960 | 31,240 | 976 | 8.6 | 150 | PCIe card (single-slot) | |
| A16 GPU accelerator (PCIe card)[41] | April 12, 2021 | 4× GA107 | — | 4× 1,280 | 885 | 1,695 | GDDR6 | 4× 128 | 4× 16 | 7,242 | 4× 200 | 4x 18,432 | 4× 4,608 | 1,084.8 | 8.6 | 250 | PCIe card (dual-slot) | |
| A30 GPU accelerator (PCIe card)[42] | April 12, 2021 | 1× GA100 | — | 3,584 | 930 | 1,440 | HBM2 | 3,072 | 24 | 1,215 | 933.1 | 165,120 | 10,320 | 5,161 | 8.0 | 165 | PCIe card (dual-slot) | |
| A40 GPU accelerator (PCIe card)[43] | October 5, 2020 | 1× GA102 | — | 10,752 | 1,305 | 1,740 | GDDR6 | 384 | 48 | 7,248 | 695.8 | 149,680 | 37,420 | 1,168 | 8.6 | 300 | PCIe card (dual-slot) | |
| A100 GPU accelerator (PCIe card)[44][45] | May 14, 2020[46] | 1× GA100-883AA-A1 | — | 6,912 | 765 | 1410 | HBM2 | 5,120 | 40 or 80 | 1,215 | 1,555 | 312,000 | 19,500 | 9,700 | 8.0 | 250 | PCIe card (dual-slot) | |
| H100 GPU accelerator (PCIe card)[47] | Hopper | March 22, 2022[48] | 1× GH100[49] | — | 14,592 | 1,065 | 1,755 CUDA 1620 TC | HBM2E | 5120 | 80 | 1,000 | 2,039 | 756,449 | 51,200 | 25,600 | 9.0 | 350 | PCIe card (dual-slot) |
| H100 GPU accelerator (SXM card) | — | 16,896 | 1,065 | 1,980 CUDA 1,830 TC | HBM3 | 5,120 | 80 | 1,500 | 3,352 | 989,430 | 66,900 | 33,500 | 9.0 | 700 | SXM card | |||
| L40 GPU accelerator[50] | Ada Lovelace | October 13, 2022 | 1× AD102[51] | — | 18,176 | 735 | 2,490 | GDDR6 | 384 | 48 | 2,250 | 864 | 362,066 | 90,516 | 1,414 | 8.9 | 300 | PCIe card (dual-slot) |
| L4 GPU accelerator[52][53] | March 21, 2023[54] | 1x AD104[55] | — | 7,424 | 795 | 2,040 | GDDR6 | 192 | 24 | 1,563 | 300 | 121,000 | 30,300 | 490 | 8.9 | 72 | HHHL single slot PCIe card | |
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Notes
- To calculate the processing power see Tesla (microarchitecture)#Performance, Fermi (microarchitecture)#Performance, Kepler (microarchitecture)#Performance, Maxwell (microarchitecture)#Performance, or Pascal (microarchitecture)#Performance. A number range specifies the minimum and maximum processing power at, respectively, the base clock and maximum boost clock.
- Core architecture version according to the CUDA programming guide.
- GPU Boost is a default feature that increases the core clock rate while remaining under the card's predetermined power budget. Multiple boost clocks are available, but this table lists the highest clock supported by each card.[8]
- Specifications not specified by Nvidia assumed to be based on the GeForce 8800 GTX
- Specifications not specified by Nvidia assumed to be based on the GeForce GTX 280
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S1075 has one interface card
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