Entdecken

10 technologies shown

• GPU hardware A processor built for massive parallelism, which is what neural network maths needs.
• A100 hardware NVIDIA's datacentre GPU that made large-model training routine.
• H100 hardware NVIDIA's datacentre GPU that became the default for training large models.
• H200 hardware Refresh of the H100 with substantially more high-bandwidth memory.
• NVLink hardware High-bandwidth interconnect between GPUs, letting them share memory directly.
• Tensor Core hardware Dedicated matrix-multiply units inside NVIDIA GPUs.
• V100 hardware The first NVIDIA GPU with tensor cores, and the one early transformers trained on.
• B200 hardware NVIDIA's Blackwell-generation datacentre GPU.
• TPU hardware Google's purpose-built accelerator for tensor arithmetic.
• MI300X hardware AMD's datacentre accelerator with a large unified memory pool.