Ampere is the codename for a graphics processing unit (GPU) microarchitecture developed by Nvidia as the successor to both the Volta and Turing architectures. It was officially announced on May 14, 2020 and is named after French mathematician and physicist André-Marie Ampère.[1][2]
Launched | May 14, 2020 |
---|---|
Designed by | Nvidia |
Manufactured by | |
Fabrication process | TSMC N7 (professional) Samsung 8N (consumer) |
Codename(s) | GA10x |
Product Series | |
Desktop | |
Professional/workstation |
|
Server/datacenter |
|
Specifications | |
L1 cache | 192 KB per SM (professional) 128 KB per SM (consumer) |
L2 cache | 2 MB to 6 MB |
Memory support | |
PCIe support | PCIe 4.0 |
Supported Graphics APIs | |
DirectX | DirectX 12 Ultimate (Feature Level 12_2) |
Direct3D | Direct3D 12.0 |
Shader Model | Shader Model 6.8 |
OpenCL | OpenCL 3.0 |
OpenGL | OpenGL 4.6 |
CUDA | Compute Capability 8.6 |
Vulkan | Vulkan 1.3 |
Media Engine | |
Encode codecs | |
Decode codecs | |
Color bit-depth |
|
Encoder(s) supported | NVENC |
Display outputs | |
History | |
Predecessor | Turing (consumer) Volta (professional) |
Successor | Ada Lovelace (consumer) Hopper (datacenter) |
Support status | |
Supported |
Nvidia announced the Ampere architecture GeForce 30 series consumer GPUs at a GeForce Special Event on September 1, 2020.[3][4] Nvidia announced the A100 80 GB GPU at SC20 on November 16, 2020.[5] Mobile RTX graphics cards and the RTX 3060 based on the Ampere architecture were revealed on January 12, 2021.[6]
Nvidia announced Ampere's successor, Hopper, at GTC 2022, and "Ampere Next Next" (Blackwell) for a 2024 release at GPU Technology Conference 2021.
Details
editArchitectural improvements of the Ampere architecture include the following:
- CUDA Compute Capability 8.0 for A100 and 8.6 for the GeForce 30 series[7]
- TSMC's 7 nm FinFET process for A100
- Custom version of Samsung's 8 nm process (8N) for the GeForce 30 series[8]
- Third-generation Tensor Cores with FP16, bfloat16, TensorFloat-32 (TF32) and FP64 support and sparsity acceleration.[9] The individual Tensor cores have with 256 FP16 FMA operations per clock 4x processing power (GA100 only, 2x on GA10x) compared to previous Tensor Core generations; the Tensor Core Count is reduced to one per SM.
- Second-generation ray tracing cores; concurrent ray tracing, shading, and compute for the GeForce 30 series
- High Bandwidth Memory 2 (HBM2) on A100 40 GB & A100 80 GB
- GDDR6X memory for GeForce RTX 3090, RTX 3080 Ti, RTX 3080, RTX 3070 Ti
- Double FP32 cores per SM on GA10x GPUs
- NVLink 3.0 with a 50 Gbit/s per pair throughput[9]
- PCI Express 4.0 with SR-IOV support (SR-IOV is reserved only for A100)
- Multi-instance GPU (MIG) virtualization and GPU partitioning feature in A100 supporting up to seven instances
- PureVideo feature set K hardware video decoding with AV1 hardware decoding[10] for the GeForce 30 series and feature set J for A100
- 5 NVDEC for A100
- Adds new hardware-based 5-core JPEG decode (NVJPG) with YUV420, YUV422, YUV444, YUV400, RGBA. Should not be confused with Nvidia NVJPEG (GPU-accelerated library for JPEG encoding/decoding)
Chips
edit- GA100[11]
- GA102
- GA103
- GA104
- GA106
- GA107
- GA10B
Comparison of Compute Capability: GP100 vs GV100 vs GA100[12]
GPU features | Nvidia Tesla P100 | Nvidia Tesla V100 | Nvidia A100 |
---|---|---|---|
GPU codename | GP100 | GV100 | GA100 |
GPU architecture | Pascal | Volta | Ampere |
Compute capability | 6.0 | 7.0 | 8.0 |
Threads / warp | 32 | 32 | 32 |
Max warps / SM | 64 | 64 | 64 |
Max threads / SM | 2048 | 2048 | 2048 |
Max thread blocks / SM | 32 | 32 | 32 |
Max 32-bit registers / SM | 65536 | 65536 | 65536 |
Max registers / block | 65536 | 65536 | 65536 |
Max registers / thread | 255 | 255 | 255 |
Max thread block size | 1024 | 1024 | 1024 |
FP32 cores / SM | 64 | 64 | 64 |
Ratio of SM registers to FP32 cores | 1024 | 1024 | 1024 |
Shared Memory Size / SM | 64 KB | Configurable up to 96 KB | Configurable up to 164 KB |
Comparison of Precision Support Matrix[13][14]
Supported CUDA Core Precisions | Supported Tensor Core Precisions | |||||||||||||||
FP16 | FP32 | FP64 | INT1 | INT4 | INT8 | TF32 | BF16 | FP16 | FP32 | FP64 | INT1 | INT4 | INT8 | TF32 | BF16 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Nvidia Tesla P4 | No | Yes | Yes | No | No | Yes | No | No | No | No | No | No | No | No | No | No |
Nvidia P100 | Yes | Yes | Yes | No | No | No | No | No | No | No | No | No | No | No | No | No |
Nvidia Volta | Yes | Yes | Yes | No | No | Yes | No | No | Yes | No | No | No | No | No | No | No |
Nvidia Turing | Yes | Yes | Yes | No | No | No | No | No | Yes | No | No | Yes | Yes | Yes | No | No |
Nvidia A100 | Yes | Yes | Yes | No | No | Yes | No | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | Yes |
Legend:
- FPnn: floating point with nn bits
- INTn: integer with n bits
- INT1: binary
- TF32: TensorFloat32
- BF16: bfloat16
Comparison of Decode Performance
Concurrent streams | H.264 decode (1080p30) | H.265 (HEVC) decode (1080p30) | VP9 decode (1080p30) |
---|---|---|---|
V100 | 16 | 22 | 22 |
A100 | 75 | 157 | 108 |
Ampere dies
editDie | GA100[15] | GA102[16] | GA103[17] | GA104[18] | GA106[19] | GA107[20] | GA10B[21] | GA10F |
---|---|---|---|---|---|---|---|---|
Die size | 826 mm2 | 628 mm2 | 496 mm2 | 392 mm2 | 276 mm2 | 200 mm2 | 448 mm2 | ? |
Transistors | 54.2B | 28.3B | 22B | 17.4B | 12B | 8.7B | 21B | ? |
Transistor density | 65.6 MTr/mm2 | 45.1 MTr/mm2 | 44.4 MTr/mm2 | 44.4 MTr/mm2 | 43.5 MTr/mm2 | 43.5 MTr/mm2 | 46.9 MTr/mm2 | ? |
Graphics processing clusters | 8 | 7 | 6 | 6 | 3 | 2 | 2 | 1 |
Streaming multiprocessors | 128 | 84 | 60 | 48 | 30 | 20 | 16 | 12 |
CUDA cores | 12288 | 10752 | 7680 | 6144 | 3840 | 2560 | 2048 | 1536 |
Texture mapping units | 512 | 336 | 240 | 192 | 120 | 80 | 64 | 48 |
Render output units | 192 | 112 | 96 | 96 | 48 | 32 | 32 | 16 |
Tensor cores | 512 | 336 | 240 | 192 | 120 | 80 | 64 | 48 |
RT cores | N/A | 84 | 60 | 48 | 30 | 20 | 8 | 12 |
L1 cache | 24 MB | 10.5 MB | 7.5 MB | 6 MB | 3 MB | 2.5 MB | 3 MB | 1.5 MB |
192 KB per SM |
128 KB per SM | 192 KB per SM |
128 KB per SM | |||||
L2 cache | 40 MB | 6 MB | 4 MB | 4 MB | 3 MB | 2 MB | 4 MB | ? |
A100 accelerator and DGX A100
editThe Ampere-based A100 accelerator was announced and released on May 14, 2020.[9] The A100 features 19.5 teraflops of FP32 performance, 6912 FP32/INT32 CUDA cores, 3456 FP64 CUDA cores, 40 GB of graphics memory, and 1.6 TB/s of graphics memory bandwidth.[22] The A100 accelerator was initially available only in the 3rd generation of DGX server, including 8 A100s.[9] Also included in the DGX A100 is 15 TB of PCIe gen 4 NVMe storage,[22] two 64-core AMD Rome 7742 CPUs, 1 TB of RAM, and Mellanox-powered HDR InfiniBand interconnect. The initial price for the DGX A100 was $199,000.[9]
Comparison of accelerators used in DGX:[23][24][25]
Model | Architecture | Socket | FP32 CUDA cores |
FP64 cores (excl. tensor) |
Mixed INT32/FP32 cores |
INT32 cores |
Boost clock |
Memory clock |
Memory bus width |
Memory bandwidth |
VRAM | Single precision (FP32) |
Double precision (FP64) |
INT8 (non-tensor) |
INT8 dense tensor |
INT32 | FP4 dense tensor |
FP16 | FP16 dense tensor |
bfloat16 dense tensor |
TensorFloat-32 (TF32) dense tensor |
FP64 dense tensor |
Interconnect (NVLink) |
GPU | L1 Cache | L2 Cache | TDP | Die size | Transistor count |
Process | Launched |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
B200 | Blackwell | SXM6 | N/A | N/A | N/A | N/A | N/A | 8 Gbit/s HBM3e | 8192-bit | 8 TB/sec | 192 GB HBM3e | N/A | N/A | N/A | 4.5 POPS | N/A | 9 PFLOPS | N/A | 2.25 PFLOPS | 2.25 PFLOPS | 1.2 PFLOPS | 40 TFLOPS | 1.8 TB/sec | GB100 | N/A | N/A | 1000 W | N/A | 208 B | TSMC 4NP | Q4 2024 (expected) |
B100 | Blackwell | SXM6 | N/A | N/A | N/A | N/A | N/A | 8 Gbit/s HBM3e | 8192-bit | 8 TB/sec | 192 GB HBM3e | N/A | N/A | N/A | 3.5 POPS | N/A | 7 PFLOPS | N/A | 1.98 PFLOPS | 1.98 PFLOPS | 989 TFLOPS | 30 TFLOPS | 1.8 TB/sec | GB100 | N/A | N/A | 700 W | N/A | 208 B | TSMC 4NP | |
H200 | Hopper | SXM5 | 16896 | 4608 | 16896 | N/A | 1980 MHz | 6.3 Gbit/s HBM3e | 6144-bit | 4.8 TB/sec | 141 GB HBM3e | 67 TFLOPS | 34 TFLOPS | N/A | 1.98 POPS | N/A | N/A | N/A | 990 TFLOPS | 990 TFLOPS | 495 TFLOPS | 67 TFLOPS | 900 GB/sec | GH100 | 25344 KB (192 KB × 132) | 51200 KB | 1000 W | 814 mm2 | 80 B | TSMC 4N | Q3 2023 |
H100 | Hopper | SXM5 | 16896 | 4608 | 16896 | N/A | 1980 MHz | 5.2 Gbit/s HBM3 | 5120-bit | 3.35 TB/sec | 80 GB HBM3 | 67 TFLOPS | 34 TFLOPS | N/A | 1.98 POPS | N/A | N/A | N/A | 990 TFLOPS | 990 TFLOPS | 495 TFLOPS | 67 TFLOPS | 900 GB/sec | GH100 | 25344 KB (192 KB × 132) | 51200 KB | 700 W | 814 mm2 | 80 B | TSMC 4N | Q3 2022 |
A100 80GB | Ampere | SXM4 | 6912 | 3456 | 6912 | N/A | 1410 MHz | 3.2 Gbit/s HBM2e | 5120-bit | 1.52 TB/sec | 80 GB HBM2e | 19.5 TFLOPS | 9.7 TFLOPS | N/A | 624 TOPS | 19.5 TOPS | N/A | 78 TFLOPS | 312 TFLOPS | 312 TFLOPS | 156 TFLOPS | 19.5 TFLOPS | 600 GB/sec | GA100 | 20736 KB (192 KB × 108) | 40960 KB | 400 W | 826 mm2 | 54.2 B | TSMC N7 | Q1 2020 |
A100 40GB | Ampere | SXM4 | 6912 | 3456 | 6912 | N/A | 1410 MHz | 2.4 Gbit/s HBM2 | 5120-bit | 1.52 TB/sec | 40 GB HBM2 | 19.5 TFLOPS | 9.7 TFLOPS | N/A | 624 TOPS | 19.5 TOPS | N/A | 78 TFLOPS | 312 TFLOPS | 312 TFLOPS | 156 TFLOPS | 19.5 TFLOPS | 600 GB/sec | GA100 | 20736 KB (192 KB × 108) | 40960 KB | 400 W | 826 mm2 | 54.2 B | TSMC N7 | |
V100 32GB | Volta | SXM3 | 5120 | 2560 | N/A | 5120 | 1530 MHz | 1.75 Gbit/s HBM2 | 4096-bit | 900 GB/sec | 32 GB HBM2 | 15.7 TFLOPS | 7.8 TFLOPS | 62 TOPS | N/A | 15.7 TOPS | N/A | 31.4 TFLOPS | 125 TFLOPS | N/A | N/A | N/A | 300 GB/sec | GV100 | 10240 KB (128 KB × 80) | 6144 KB | 350 W | 815 mm2 | 21.1 B | TSMC 12FFN | Q3 2017 |
V100 16GB | Volta | SXM2 | 5120 | 2560 | N/A | 5120 | 1530 MHz | 1.75 Gbit/s HBM2 | 4096-bit | 900 GB/sec | 16 GB HBM2 | 15.7 TFLOPS | 7.8 TFLOPS | 62 TOPS | N/A | 15.7 TOPS | N/A | 31.4 TFLOPS | 125 TFLOPS | N/A | N/A | N/A | 300 GB/sec | GV100 | 10240 KB (128 KB × 80) | 6144 KB | 300 W | 815 mm2 | 21.1 B | TSMC 12FFN | |
P100 | Pascal | SXM/SXM2 | N/A | 1792 | 3584 | N/A | 1480 MHz | 1.4 Gbit/s HBM2 | 4096-bit | 720 GB/sec | 16 GB HBM2 | 10.6 TFLOPS | 5.3 TFLOPS | N/A | N/A | N/A | N/A | 21.2 TFLOPS | N/A | N/A | N/A | N/A | 160 GB/sec | GP100 | 1344 KB (24 KB × 56) | 4096 KB | 300 W | 610 mm2 | 15.3 B | TSMC 16FF+ | Q2 2016 |
Products using Ampere
edit- GeForce MX series
- GeForce MX570 (mobile) (GA107)
- GeForce 20 series
- GeForce RTX 2050 (mobile) (GA107)
- GeForce 30 series
- GeForce RTX 3050 Laptop GPU (GA107)
- GeForce RTX 3050 (GA106 or GA107)[26]
- GeForce RTX 3050 Ti Laptop GPU (GA107)
- GeForce RTX 3060 Laptop GPU (GA106)
- GeForce RTX 3060 (GA106 or GA104)[27]
- GeForce RTX 3060 Ti (GA104 or GA103)[28]
- GeForce RTX 3070 Laptop GPU (GA104)
- GeForce RTX 3070 (GA104)
- GeForce RTX 3070 Ti Laptop GPU (GA104)
- GeForce RTX 3070 Ti (GA104 or GA102)[29]
- GeForce RTX 3080 Laptop GPU (GA104)
- GeForce RTX 3080 (GA102)
- GeForce RTX 3080 12 GB (GA102)
- GeForce RTX 3080 Ti Laptop GPU (GA103)
- GeForce RTX 3080 Ti (GA102)
- GeForce RTX 3090 (GA102)
- GeForce RTX 3090 Ti (GA102)
- Nvidia Workstation GPUs (formerly Quadro)
- RTX A1000 (mobile) (GA107)
- RTX A2000 (mobile) (GA106)
- RTX A2000 (GA106)
- RTX A3000 (mobile) (GA104)
- RTX A4000 (mobile) (GA104)
- RTX A4000 (GA104)
- RTX A5000 (mobile) (GA104)
- RTX A5500 (mobile) (GA103)
- RTX A4500 (GA102)
- RTX A5000 (GA102)
- RTX A5500 (GA102)
- RTX A6000 (GA102)
- A800 Active
- Nvidia Data Center GPUs (formerly Tesla)
- Nvidia A2 (GA107)
- Nvidia A10 (GA102)
- Nvidia A16 (4 × GA107)
- Nvidia A30 (GA100)
- Nvidia A40 (GA102)
- Nvidia A100 (GA100)
- Nvidia A100 80 GB (GA100)
- Nvidia A100X
- NVIDIA A30X
- Tegra SoCs
- AGX Orin (GA10B)
- Orin NX (GA10B)
- Orin Nano (GA10B)
Type | GA10B | GA107 | GA106 | GA104 | GA103 | GA102 | GA100 |
---|---|---|---|---|---|---|---|
GeForce MX series | — | GeForce MX570 (mobile) | — | — | — | — | — |
GeForce 20 series | — | GeForce RTX 2050 (mobile) | — | — | — | — | — |
GeForce 30 series | — | GeForce RTX 3050 Laptop GeForce RTX 3050 GeForce RTX 3050 Ti Laptop |
GeForce RTX 3050 GeForce RTX 3060 Laptop GeForce RTX 3060 |
GeForce RTX 3060 GeForce RTX 3060 Ti GeForce RTX 3070 Laptop GeForce RTX 3070 GeForce RTX 3070 Ti Laptop GeForce RTX 3070 Ti GeForce RTX 3080 Laptop |
GeForce RTX 3060 Ti GeForce RTX 3080 Ti Laptop |
GeForce RTX 3070 Ti GeForce RTX 3080 GeForce RTX 3080 Ti GeForce RTX 3090 GeForce RTX 3090 Ti |
— |
Nvidia Workstation GPUs | — | RTX A1000 (mobile) | RTX A2000 (mobile) RTX A2000 |
RTX A3000 (mobile) RTX A4000 (mobile) RTX A4000 RTX A5000 (mobile) |
RTX A5500 (mobile) | RTX A4500 RTX A5000 RTX A5500 RTX A6000 |
— |
Nvidia Data Center GPUs | — | Nvidia A2 Nvidia A16 |
— | — | — | Nvidia A10 Nvidia A40 |
Nvidia A30 Nvidia A100 |
Tegra SoCs | AGX Orin Orin NX Orin Nano |
— | — | — | — | — | — |
See also
editReferences
edit- ^ Newsroom, NVIDIA. "NVIDIA's New Ampere Data Center GPU in Full Production". NVIDIA Newsroom Newsroom.
{{cite web}}
:|last=
has generic name (help) - ^ "NVIDIA Ampere Architecture In-Depth". NVIDIA Developer Blog. May 14, 2020.
- ^ "NVIDIA Delivers Greatest-Ever Generational Leap with GeForce RTX 30 Series GPUs". Nvidia Newsroom. September 1, 2020. Retrieved April 9, 2023.
- ^ "NVIDIA GeForce Ultimate Countdown". Nvidia.
- ^ "NVIDIA Doubles Down: Announces A100 80GB GPU, Supercharging World's Most Powerful GPU for AI Supercomputing". Nvidia Newsroom. November 16, 2020. Retrieved April 9, 2023.
- ^ "NVIDIA GeForce Beyond at CES 2023". NVIDIA.
- ^ "I.7. Compute Capability 8.x". Nvidia. Retrieved September 23, 2020.
- ^ Bosnjak, Dominik (September 1, 2020). "Samsung's old 8nm tech at the heart of NVIDIA's monstrous Ampere cards". SamMobile. Retrieved September 19, 2020.
- ^ a b c d e Smith, Ryan (May 14, 2020). "NVIDIA Ampere Unleashed: NVIDIA Announces New GPU Architecture, A100 GPU, and Accelerator". AnandTech.
- ^ Delgado, Gerardo (September 1, 2020). "GeForce RTX 30 Series GPUs: Ushering In A New Era of Video Content With AV1 Decode". Nvidia. Retrieved April 9, 2023.
- ^ Morgan, Timothy Prickett (May 29, 2020). "Diving Deep Into The Nvidia Ampere GPU Architecture". The Next Platform. Retrieved March 24, 2022.
- ^ "NVIDIA A100 Tensor Core GPU Architecture: Unprecedented Accerlation at Every Scale" (PDF). Nvidia. Retrieved September 18, 2020.
- ^ "NVIDIA Tensor Cores: Versatility for HPC & AI". NVIDIA.
- ^ "Abstract". docs.nvidia.com.
- ^ "NVIDIA A100 Tensor Core GPU Architecture" (PDF). NVIDIA Corporation. Retrieved April 29, 2024.
- ^ "NVIDIA GA102 GPU Specs". TechPowerUp. Retrieved April 29, 2024.
- ^ "NVIDIA GA103 GPU Specs". TechPowerUp. Retrieved April 29, 2024.
- ^ "NVIDIA GA104 GPU Specs". TechPowerUp. Retrieved April 29, 2024.
- ^ "NVIDIA GA106 GPU Specs". TechPowerUp. Retrieved April 29, 2024.
- ^ "NVIDIA GA107 GPU Specs". TechPowerUp. Retrieved April 29, 2024.
- ^ "NVIDIA AGX Orin Series Technical Brief v1.2" (PDF). NVIDIA Corporation. Retrieved April 29, 2024.
- ^ a b Tom Warren; James Vincent (May 14, 2020). "Nvidia's first Ampere GPU is designed for data centers and AI, not your PC". The Verge.
- ^ Smith, Ryan (March 22, 2022). "NVIDIA Hopper GPU Architecture and H100 Accelerator Announced: Working Smarter and Harder". AnandTech.
- ^ Smith, Ryan (May 14, 2020). "NVIDIA Ampere Unleashed: NVIDIA Announces New GPU Architecture, A100 GPU, and Accelerator". AnandTech.
- ^ "NVIDIA Tesla V100 tested: near unbelievable GPU power". TweakTown. September 17, 2017.
- ^ Igor, Wallossek (February 13, 2022). "The two faces of the GeForce RTX 3050 8GB". Igor's Lab. Retrieved February 23, 2022.
- ^ Shilov, Anton (September 25, 2021). "Gainward and Galax List GeForce RTX 3060 Cards With GA104 GPU". Tom's Hardware. Retrieved September 23, 2022.
- ^ Tyson, Mark (February 23, 2022). "Zotac Debuts First RTX 3060 Ti Desktop Cards With GA103 GPU". Tom's Hardware. Retrieved September 23, 2022.
- ^ WhyCry (October 26, 2022). "ZOTAC launches GeForce RTX 3070 Ti with GA102-150 GPU". VideoCardz. Retrieved May 21, 2023.