NVIDIA A100’s third-generation Tensor Cores with Tensor Float (TF32) precision provide up to 20X higher performance over the prior generation with zero code changes and an additional 2X boost with automatic mixed precision and FP16. When combined with third-generation NVIDIA® NVLink®, NVIDIA NVSwitch™, PCI Gen4, NVIDIA Mellanox InfiniBand, and the NVIDIA Magnum IO™ software SDK, it’s possible to scale to thousands of A100 GPUs. This means that large AI models like BERT can be trained in just 37 minutes on a cluster of 1,024 A100s, offering unprecedented performance and scalability..

A100 introduces double-precision Tensor Cores, providing the biggest milestone since the introduction of double-precision computing in GPUs for HPC. This enables researchers to reduce a 10-hour, double-precision simulation running on NVIDIA V100 Tensor Core GPUs to just four hours on A100. HPC applications can also leverage TF32 precision in A100’s Tensor Cores to achieve up to 10X higher throughput for single-precision dense matrix multiply operations.

A100 with MIG maximizes the utilization of GPU-accelerated infrastructure like never before. MIG allows an A100 GPU to be partitioned into as many as seven independent instances, giving multiple users access to GPU acceleration for their applications and development projects. MIG works with Kubernetes, containers, and hypervisor-based server virtualization with NVIDIA Virtual Compute Server (vComputeServer). MIG lets infrastructure managers offer a right-sized GPU with guaranteed quality of service (QoS) for every job, optimizing utilization and extending the reach of accelerated computing resources to every user.