Difference between revisions of "Nvidia"
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↑ https://nvidianews.nvidia.com/news/new-nvidia-data-center-inference-platform-to-fuel-next-wave-of-ai-powered-services
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| − | + | [[wikipedia:Nvidia]] ([[S&P 100]], [https://www.google.com/finance/quote/NVDA:NASDAQ?hl=en&window=MAX NVDA], [https://trends.google.com/trends/explore?date=today%205-y&q=nvidia&hl=en trends]) ([[Santa Clara]]) | |
| − | |||
| − | [[wikipedia: | ||
== Binaries == | == Binaries == | ||
| Line 7: | Line 5: | ||
== Models == | == Models == | ||
| − | * Nvidia P100 | + | * [[Nvidia P100]] |
| − | * Nvidia V100 | + | * [[Nvidia V100]] |
| − | * Nvidia T4 (September 2018<ref>https://nvidianews.nvidia.com/news/new-nvidia-data-center-inference-platform-to-fuel-next-wave-of-ai-powered-services</ref>) | + | * [[Nvidia T4]] (September 2018<ref>https://nvidianews.nvidia.com/news/new-nvidia-data-center-inference-platform-to-fuel-next-wave-of-ai-powered-services</ref>) |
** T4 can decode up to 38 [[full HD]] video streams | ** T4 can decode up to 38 [[full HD]] video streams | ||
** Up to 20 GPUs in a single node. | ** Up to 20 GPUs in a single node. | ||
** 320 TURING TENSOR CORES | ** 320 TURING TENSOR CORES | ||
** 2,560 NVIDIA CUDA® CORES | ** 2,560 NVIDIA CUDA® CORES | ||
| − | ** 8.1 | + | ** 8.1 [[TFLOPs]] at [[FP32]], 65 TFLOPS at FP16 as well as 130 TOPS of INT8 and 260 TOPS of INT4 |
| + | |||
| + | * [[Nvidia A100]] | ||
| + | * [[Nvidia H100 GPU]] | ||
* Nvidia DGX-2 https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/dgx-2/dgx-2-print-datasheet-738070-nvidia-a4-web-uk.pdf | * Nvidia DGX-2 https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/dgx-2/dgx-2-print-datasheet-738070-nvidia-a4-web-uk.pdf | ||
| − | + | * [[Nvidia Drive PX]] | |
== Related terms == | == Related terms == | ||
| Line 30: | Line 31: | ||
* <code>[[gpustat]]</code> | * <code>[[gpustat]]</code> | ||
* [[Nvidia Drive]] | * [[Nvidia Drive]] | ||
| + | * [[Nvidia Jetson]]: [[Jetson nano]] | ||
| + | * [[Tegra]] | ||
| + | * [[Jensen Huang]] | ||
| + | * [[Qualcomm]]: [[Qualcomm Snapdragon]] | ||
| + | * [[Intel]] | ||
| + | * [[Nvidia Grace]] | ||
| + | * [[Ampere]] | ||
| + | * [[Pascal]] | ||
| + | * [[AWS GPUs]]: [[G5]] | ||
== See also == | == See also == | ||
| + | * {{Nvidia tools}} | ||
| + | * {{Nvidia}} | ||
* {{GPU}} | * {{GPU}} | ||
| − | |||
| − | |||
[[Category:Computing]] | [[Category:Computing]] | ||
Latest revision as of 11:46, 29 May 2024
wikipedia:Nvidia (S&P 100, NVDA, trends) (Santa Clara)
Contents
Binaries[edit]
Models[edit]
- Nvidia P100
- Nvidia V100
- Nvidia T4 (September 2018[1])
Related terms[edit]
- Resnet50, DeepSpeech2, GNMT
- FP32
- Nvidia Parabricks Genomics Analysis Toolkit is a software suite for performing secondary analysis of next generation sequencing (NGS) DNA data
- InfiniBand
- nouveau (driver)
gpustat- Nvidia Drive
- Nvidia Jetson: Jetson nano
- Tegra
- Jensen Huang
- Qualcomm: Qualcomm Snapdragon
- Intel
- Nvidia Grace
- Ampere
- Pascal
- AWS GPUs: G5
See also[edit]
- Nvidia tools: CUDA, NVIDIA Data Center GPU Manager (DCGM),
nvcc, Nvidia Management Library (NVML),nvidia-smi, nvidia-device-plugin, CUDA Time-Slicing - Nvidia, GPU, Nvidia tools,
nvidia-smi, CUDA, Nvidia Drive, Tegra, EVGA Corporation, A10, A100, H100, T4, L4, K80,gpustat, Nvidia Xavier, NVML, TOPS, Nvidia broadcast, Mellanox, Jensen Huang, NVIDIA driver, Nvidia RTX, Tensor Cores, Nvidia DGX, Nvidia Omniverse Cloud, Drive Thor, Ada, Hopper, NVIDIA device plugin for Kubernetes, NVIDIA DCGM, NVIDIA GPU Operator, Megatron-Core, NVLM, NVIDIA GPU Boost, NVSwitch, NVIDIA Driver R450+ - GPU, eGPU, OpenCL, ROCm, Nvidia, CUDA, Nvidia Tesla, AMD, RTX,
gpustat, Teraflop, Ethash, Pytorch, Pascal GPU, TBDR, A100, H100, TRIP, AMD Instinct MI100, AMD Radeon, LPU, TFLOP
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