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Nvidia Tesla

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From Wikipedia, the free encyclopedia

Nvidia's line of general purpose GPUs

This article is about GPGPU cards. For the GPU microarchitecture, seeTesla (microarchitecture).

"Tesla P100" redirects here. For the line of performance cars by Tesla Motors (P100D), seeTesla Model S andTesla Model X.

Nvidia Tesla
Nvidia Tesla M40 GPU


Manufacturer	Nvidia
Introduced	May 2, 2007; 18 years ago (2007-05-02)
Discontinued	The Tesla branding was discontinued in May 2020; 5 years ago (2020-05)—now branded as Nvidia Data Center GPUs
Type	General purposegraphics cards

Nvidia Tesla is the former name for a line of products developed byNvidia targeted atstream processing orgeneral-purpose graphics processing units (GPGPU), named after pioneering electrical engineerNikola Tesla. Its products began using GPUs from theG80 series, and have continued to accompany the release of new chips. They are programmable using theCUDA orOpenCL APIs.

The Nvidia Tesla product line competed with AMD'sRadeon Instinct and IntelXeon Phi lines of deep learning and GPU cards.

Nvidia retired the Tesla brand in May 2020, reportedly because of potential confusion withthe brand of cars.^[1] Its new GPUs are brandedNvidia Data Center GPUs^[2] as in theAmpere-based A100 GPU.^[3]

Nvidia DGX servers feature Nvidia GPGPUs.

Overview

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CSIRO data-center GPU cluster utilizing Tesla S1070

Offering computational power much greater than traditionalmicroprocessors, the Tesla products targeted thehigh-performance computing market.^[4] As of 2012,^[update] Nvidia Teslas power some of the world's fastestsupercomputers, includingSummit atOak Ridge National Laboratory andTianhe-1A, inTianjin,China.

Unlike Nvidia's consumerGeForce cards and professionalNvidia Quadro cards, Tesla cards were originally unable to output images to adisplay. However, the last Tesla C-class products included one Dual-Link DVI port.^[5]

Applications

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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 thegeospatial intelligence market.^[7]

Two Nvidia Tesla M40 in a consumer-grade PC
Nvidia Tesla P100 die
Servers utilizing an Nvidia Tesla GPU cluster

Specifications

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Model	Microarchitecture	Launch	Core	Core clock (MHz)	Shaders			Memory					Processing power (TFLOPS)^[a]			CUDA compute capability^[b]	TDP (W)	Notes, form factor
Model	Microarchitecture	Launch	Core	Core clock (MHz)	Core config^[c]	Base clock (MHz)	Max boost clock (MHz)^[d]	Bus type	Bus width (bit)	Size (GB)	Clock (MT/s)	Bandwidth (GB/s)	Half precision Tensor Core FP32 Accumulate	Single precision (MAD orFMA)	Double precision (FMA)	CUDA compute capability^[b]	TDP (W)	Notes, form factor
C870 GPU Computing Module^[e]	Tesla	May 2, 2007	1× G80	600	128:32 :24:0:0 (16)	1350	N/a	GDDR3	384	1.5	1600	76.8	No	0.3456	No	1.0	170.9	Internal PCIe GPU (full-height, dual-slot)
D870 Deskside Computer^[e]		May 2, 2007	2× G80	600	2× 128:32 :24:0:0 (16)	1350	N/a	GDDR3	2× 384	2× 1.5	1600	2× 76.8	No	0.6912	No	1.0	520	Deskside or 3Urack-mount external GPUs
S870 GPU Computing Server^[e]		May 2, 2007	4× G80	600	4× 128:32 :24:0:0 (16)	1350	N/a	GDDR3	4× 384	4× 1.5	1600	4× 76.8	No	1.382	No	1.0		1Urack-mount external GPUs, connect via 2× PCIe (×16)
C1060 GPU Computing Module^[f]		April 9, 2009	1× GT200	602	240:80 :32:0:0 (30)	1296^[9]	N/a	GDDR3	512	4	1600	102.4	No	0.6221	0.07776	1.3	187.8	Internal PCIe GPU (full-height, dual-slot)
S1070 GPU Computing Server "400 configuration"^[f]		June 1, 2008	4× GT200	602	4× 240:80 :32:0:0 (30)	1296	N/a	GDDR3	4× 512	4× 4	1538.4	4× 98.5	No	2.488	0.311	1.3	800	1Urack-mount external GPUs, connect via 2× PCIe (×8 or ×16)
S1070 GPU Computing Server "500 configuration"^[f]		June 1, 2008	4× GT200	602	4× 240:80 :32:0:0 (30)	1440	N/a	GDDR3	4× 512	4× 4	1538.4	4× 98.5	No	2.765	0.3456	1.3	800	1Urack-mount external GPUs, connect via 2× PCIe (×8 or ×16)
S1075 GPU Computing Server^[f]^[10]		June 1, 2008	4× GT200	602	4× 240:80 :32:0:0 (30)	1440	N/a	GDDR3	4× 512	4× 4	1538	4× 98.5	No	2.765	0.3456	1.3		1Urack-mount external GPUs, connect via 1× PCIe (×8 or ×16)
Quadro Plex 2200 D2 Visual Computing System^[g]		July 25, 2008	2× GT200GL	648	2× 240:80 :32:0:0 (30)	1296	N/a	GDDR3	2× 512	2× 4	1600	2× 102.4	No	1.244	0.1555	1.3		Deskside or 3Urack-mount external GPUs with 4 dual-link DVI outputs
Quadro Plex 2200 S4 Visual Computing System^[g]		July 25, 2008	4× GT200GL	648	4× 240:80 :32:0:0 (30)	1296	N/a	GDDR3	4× 512	4× 4	1600	4× 102.4	No	2.488	0.311	1.3	1200	1Urack-mount external GPUs, connect via 2× PCIe (×8 or ×16)
C2050 GPU Computing Module^[11]	Fermi	July 25, 2011	1× GF100	575	448:56 :48:0:0 (14)	1150	N/a	GDDR5	384	3^[h]	3000	144	No	1.030	0.5152	2.0	247	Internal PCIe GPU (full-height, dual-slot)
M2050 GPU Computing Module^[12]		July 25, 2011	1× GF100	575	448:56 :48:0:0 (14)	1150	N/a	GDDR5	384	3^[h]	3092	148.4	No	1.030	0.5152	2.0	225	Internal PCIe GPU (full-height, dual-slot)
C2070 GPU Computing Module^[11]		July 25, 2011	1× GF100	575	448:56 :48:0:0 (14)	1150	N/a	GDDR5	384	6^[h]	3000	144	No	1.030	0.5152	2.0	247	Internal PCIe GPU (full-height, dual-slot)
C2075 GPU Computing Module^[13]		July 25, 2011					N/a				3000	144	No				225
M2070/M2070Q GPU Computing Module^[14]		July 25, 2011					N/a				3132	150.3	No				225
M2090 GPU Computing Module^[15]		July 25, 2011	1× GF110	650	512:64 :48:0:0 (16)	1300	N/a	GDDR5	384	6^[h]	3700	177.6	No	1.331	0.6656	2.0	225	Internal PCIe GPU (full-height, dual-slot)
S2050 GPU Computing Server		July 25, 2011	4× GF100	575	4× 448:56 :48:0:0 (14)	1150	N/a	GDDR5	4× 384	4× 3^[h]	3000	4× 148.4	No	4.122	2.061	2.0	900	1Urack-mount external GPUs, connect via 2× PCIe (×8 or ×16)
S2070 GPU Computing Server		July 25, 2011	4× GF100	575	4× 448:56 :48:0:0 (14)	1150	N/a	GDDR5	4× 384	4× 6^[h]	3000	4× 148.4	No	4.122	2.061	2.0	900	1Urack-mount external GPUs, connect via 2× PCIe (×8 or ×16)
K10 GPU accelerator^[16]	Kepler	May 1, 2012	2× GK104	N/a	2× 1536:138 :32:0:0 (8)	745	?	GDDR5	2× 256	2× 4	5000	2× 160	No	4.577	0.1907	3.0	225	Internal PCIe GPU (full-height, dual-slot)
K20 GPU accelerator^[17]^[18]		November 12, 2012	1× GK110	N/a	2496:208 :40:0:0 (13)	706	758	GDDR5	320	5	5200	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	N/a	2688:224 :48:0:0 (14)	732	?	GDDR5	384	6	5200	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	N/a	2880:240 :48:0:0 (15)	745	875	GDDR5	384	12^[h]	6000	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	N/a	2× 2496:208 :48:0:0 (13)	560	875	GDDR5	2× 384	2× 12	5000	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	N/a	1024:64 :32:0:0 (8)	872	1072	GDDR5	128	4	5500	88	No	1.786–2.195	0.05581–0.06861	5.2	50–75	Internal PCIe GPU (half-height, single-slot)
M6 GPU accelerator^[24]		August 30, 2015	1× GM204-995-A1	N/a	1536:96 :64:0:0 (12)	722	1051	GDDR5	256	8	4600	147.2	No	2.218–3.229	0.0693–0.1009	5.2	75–100	Internal MXM GPU
M10 GPU accelerator^[25]		May 18, 2016	4× GM107	N/a	4× 640:40 :16:0:0 (5)	1033	?	GDDR5	4× 128	4× 8	5188	4× 83	No	5.289	0.1653	5.2	225	Internal PCIe GPU (full-height, dual-slot)
M40 GPU accelerator^[23]^[26]		November 10, 2015	1× GM200	N/a	3072:192 :96:0:0 (24)	948	1114	GDDR5	384	12 or 24	6000	288	No	5.825–6.844	0.182–0.2139	5.2	250	Internal PCIe GPU (full-height, dual-slot)
M60 GPU accelerator^[27]		August 30, 2015	2× GM204-895-A1	N/a	2× 2048:128 :64:0:0 (16)	899	1178	GDDR5	2× 256	2× 8	5000	2× 160	No	7.365–9.650	0.2301–0.3016	5.2	225–300	Internal PCIe GPU (full-height, dual-slot)
P4 GPU accelerator^[28]	Pascal	September 13, 2016	1× GP104	N/a	2560:160 :64:0:0 (20)	810	1063	GDDR5	256	8	6000	192.0	No	4.147–5.443	0.1296–0.1701	6.1	50–75	PCIe card
P6 GPU accelerator^[29]^[30]		March 24, 2017	1× GP104-995-A1	N/a	2048:128 :64:0:0 (16)	1012	1506	GDDR5	256	16	3003	192.2	No	6.169	0.1928	6.1	90	MXM card
P40 GPU accelerator^[28]		September 13, 2016	1× GP102	N/a	3840:240 :96:0:0 (30)	1303	1531	GDDR5	384	24	7200	345.6	No	10.01–11.76	0.3127–0.3674	6.1	250	PCIe card
P100 GPU accelerator (mezzanine)^[31]^[32]		April 5, 2016	1× GP100-890-A1	N/a	3584:224 :96:0:0 (56)	1328	1480	HBM2	4096	16	1430	732	No	9.519–10.61	4.760–5.304	6.0	300	SXM card
P100 GPU accelerator (16 GB card)^[33]		June 20, 2016	1× GP100	N/a		1126	1303		4096	16		732	No	8.071‒9.340	4.036‒4.670		250	PCIe card
P100 GPU accelerator (12 GB card)^[33]		June 20, 2016	1× GP100	N/a		1126	1303		3072	12		549	No	8.071‒9.340	4.036‒4.670		250	PCIe card
V100 GPU accelerator (mezzanine)^[34]^[35]^[36]	Volta	May 10, 2017	1× GV100-895-A1	N/a	5120:320 :128:640:0 (80)	Unknown	1455	HBM2	4096	16 or 32	1750	900	119.2	14.90	7.450	7.0	300	SXM card
V100 GPU accelerator (PCIe card)^[34]^[35]^[36]		June 21, 2017	1× GV100	N/a		Unknown	1370			16 or 32	1750	900	112.2	14.03	7.014		250	PCIe card
V100 GPU accelerator (PCIe FHHL card)		March 27, 2018	1× GV100	N/a		937	1290			16	1620	829.4	105.7	13.21	6.605		250	PCIe FHHL card
T4 GPU accelerator (PCIe card)^[37]^[38]	Turing	September 12, 2018	1× TU104-895-A1	N/a	2560:160 :64:320:40 (40)	585	1590	GDDR6	256	16	5000	320	64.8	8.1	Unknown	7.5	70	PCIe card
A2 GPU accelerator (PCIe card)^[39]	Ampere	November 10, 2021	1× GA107	N/a	1280:40 :32:40:10 (10)	1440	1770	GDDR6	128	16	6252	200	18.12	4.531	0.14	8.6	40–60	PCIe card (half height, single-slot)
A10 GPU accelerator (PCIe card)^[40]		April 12, 2021	1× GA102-890-A1	N/a	9216:288 :96:288:72 (72)	885	1695	GDDR6	384	24	6252	600	125.0	31.24	0.976	8.6	150	PCIe card (single-slot)
A16 GPU accelerator (PCIe card)^[41]		April 12, 2021	4× GA107	N/a	4× 1280:40 :32:40:10 (10)	885	1695	GDDR6	4× 128	4× 16	7242	4× 200	4x 18.43	4× 4.608	1.085	8.6	250	PCIe card (dual-slot)
A30 GPU accelerator (PCIe card)^[42]		April 12, 2021	1× GA100	N/a	3584:224 :96:224:0 (56)	930	1440	HBM2	3072	24	1215	933.1	165.1	10.32	5.161	8.0	165	PCIe card (dual-slot)
A40 GPU accelerator (PCIe card)^[43]		October 5, 2020	1× GA102	N/a	10752:336 :112:336:84 (84)	1305	1740	GDDR6	384	48	7248	695.8	149.7	37.42	1.168	8.6	300	PCIe card (dual-slot)
A100 GPU accelerator (PCIe card)^[44]^[45]		May 14, 2020^[46]	1× GA100-883AA-A1	N/a	6912:432 :160:432:0 (108)	765	1410	HBM2	5120	40 or 80	1215	1555	312.0	19.5	9.7	8.0	250	PCIe card (dual-slot)
H100 GPU accelerator (PCIe card)^[47]	Hopper	March 22, 2022^[48]	1× GH100^[49]	N/a	14592:456 :24:456:0 (114)	1065	1755 CUDA 1620 TC	HBM2E	5120	80	1000	2039	756.4	51.2	25.6	9.0	350	PCIe card (dual-slot)
H100 GPU accelerator (SXM card)		March 22, 2022^[48]	1× GH100^[49]	N/a	16896:528 :24:528:0 (132)	1065	1980 CUDA 1830 TC	HBM3	5120	64 or 80 or 96	1500	3352	989.4	66.9	33.5	9.0	700	SXM card
H200 GPU accelerator (PCIe card)^[50]		November 18, 2024^[51]	1× GH100	N/a		1365	1785	HBM3E	5120	141	1313	3360	835	60.32	30.16	9.0	600	PCIe card (dual-slot)
H200 GPU accelerator (SXM card)		November 18, 2024^[51]	1× GH100	N/a		1590	1980	HBM3E	5120	141	1313	3360	989	66.91	33.45	9.0	700	SXM card
H800 GPU accelerator (SXM card)		March 21, 2023^[52]	1× GH100	N/a		1095	1755	HBM3	5120	80	1313	3360	N/a	59.3	29.65	9.0	700	SXM card
L40 GPU accelerator^[53]	Ada Lovelace	October 13, 2022	1× AD102^[54]	N/a	18176:568 :192:568:142 (142)	735	2490	GDDR6	384	48	2250	864	362.1	90.52	1.414	8.9	300	PCIe card (dual-slot)
L4 GPU accelerator^[55]^[56]	Ada Lovelace	March 21, 2023^[57]	1x AD104^[58]	N/a	7424:240 :80:240:0 (60)	795	2040	GDDR6	192	24	1563	300	121.0	30.3	0.49	8.9	72	HHHL single slot PCIe card
B100 GPU accelerator^[59]	Blackwell	November 2024	2× GB102	N/a	2× 16896:528 :24:528:0 (132)	1665	1837	HBM3E	2× 4096	2× 96	2000	2× 4100	2× 990^[60]	2× 62.08	2× 31.04	10.1	700^[60]	SXM card
B200 GPU accelerator^[61]	Blackwell	2024	2× GB100	N/a	2× 16896:528 :24:528:0 (132)	1665	1837	HBM3E	2× 4096	2× 96	2000	2× 4100	2× 1125^[60]	2× 62.08	2× 31.04	10.0	1000	SXM card

Notes

^To calculate the processing power seeTesla (microarchitecture)#Performance,Fermi (microarchitecture)#Performance,Kepler (microarchitecture)#Performance,Maxwell (microarchitecture)#Performance, orPascal (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 theCUDA programming guide.
^Mainshader processors :texture mapping unit :render output units :tensor cores :ray-tracing cores (streaming multiprocessors)
^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]
^^a ^b ^cSpecifications not specified by Nvidia assumed to be based on theGeForce 8800 GTX
^^a ^b ^c ^dSpecifications not specified by Nvidia assumed to be based on theGeForce GTX 280
^^a ^bSpecifications not specified by Nvidia assumed to be based on the Quadro FX 5800
^^a ^b ^c ^d ^e ^fWith ECC on, a portion of the dedicated memory is used for ECC bits, so the available user memory is reduced by 12.5%. (e.g. 4 GB total memory yields 3.5 GB of user available memory.)

References

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External links

[edit]

Wikimedia Commons has media related toNvidia Tesla series.

Nvidia

GeForce(List of GPUs)

Fixed pixel pipeline

Pre-GeForce	NV1 NV2 RIVA 128 RIVA TNT TNT2

Vertex andpixel shaders

GeForce 3

4 Ti

Unified shaders

Unified shaders &NUMA

Ray tracing &Tensor Cores

Software and technologies

Multimedia acceleration	NVENC (video encoding) NVDEC (video decoding) PureVideo (video decoding)
Software	Cg (shading language) CUDA Nvidia GameWorks OptiX (ray tracing API) PhysX (physics SDK) Nvidia Omniverse (3D graphics) Nvidia RTX (ray tracing platform) Nvidia System Tools VDPAU (video decode API)
Technologies	Nvidia 3D Vision (stereo 3D) Nvidia G-Sync (variable refresh rate) Nvidia Optimus (GPU switching) Nvidia Surround (multi-monitor) MXM (module/socket) SXM (module/socket) NVLink (protocol) Scalable Link Interface (multi-GPU) TurboCache (framebuffer in system memory) Video Super Resolution (live video upscaling)
GPU microarchitectures	Celsius Kelvin Rankine Curie Tesla Fermi Kepler Maxwell Pascal Volta Turing Ampere Hopper Ada Lovelace Blackwell Rubin Feynman

Other products

GraphicsWorkstation cards	Nvidia Quadro Quadro Plex
GPGPU software	Nvidia Tesla DGX
Console components	NV2A(Xbox) RSX 'Reality Synthesizer'(PlayStation 3) Tegra X1(Nintendo Switch) Tegra T239 "Drake"(Nintendo Switch 2)
Nvidia Shield	Shield Portable Shield Tablet Shield Android TV GeForce Now
SoCs and embedded	GoForce Drive Jetson Tegra
CPUs	Project Denver
Computerchipsets	nForce

Company

Key people	Jen-Hsun Huang Chris Malachowsky Curtis Priem David Kirk Bill Dally Colette Kress Debora Shoquist Ranga Jayaraman Jonah M. Alben
Acquisitions	3dfx Interactive Ageia ULi Bright Computing Cumulus Networks DeepMap Icera Mellanox Technologies Mental Images PortalPlayer Exluna MediaQ Stexar

Graphics processing unit

GPU

Desktop	Intel GT Xe Arc Nvidia GeForce Quadro Tesla Tegra AMD Radeon Radeon Pro Instinct Matrox InfiniteReality NEC µPD7220 3dfx Voodoo S3 Glaze3D Apple silicon Jingjia Micro Tseng Labs SiS
Mobile	Adreno Apple silicon Mali PowerVR VideoCore Vivante Imageon Intel 2700G