NVIDIA A100, an Ampere architecture-based GPU, is already in production and will soon be sold to clients all over the world. Microsoft will be the first to make the most out of the GPU’s scalability and performance.

Built into A100, the never before used elastic computing technologies will bring new computing power to many people. Every A100 GPU comes with multi-instance GPU option. This gives each GPU the capability of having seven independent instances for conducting inferencing tasks. The NVIDIA NVLink interconnect technology, on the other hand, makes it possible for GPUs of this architecture to work as one huge GPU for conducting even bigger operations.

Making the most out of the NVIDIA Ampere architecture, A100 offers the most substantial performance boost for companies to date. The leap in performance is up to twenty times over that of older GPUs. Built for data analytics, the A100 is a universal workload accelerator, delivering cloud graphics and scientific computing.

Presently, the data center designs are experiencing a tectonic shift driven by AI and cloud computing. What we previously knew as CPU-centric servers has been transformed into a GPU-based computing power.

According to NVIDIA’s founder and CEO, Jensen Huang, the A100 GPU of his company brings to bear an end-to-end machine leering accelerator and comes in with twenty times better AI performance compare to previous generation GPUs. He further claimed that A100 will decrease the cost while increase the productivity of data centers.

The NVIDIA’s A100 GPU would be a substantial breakthrough, resulting from several notable innovations.

First and foremost is the NVIDIA Ampere GPU architecture. At its heart, it comes with 54 billion transistors, comprising the biggest 7-nanometer processor in the world. Tensor Cores by NVIDIA, while now performing faster is at the same time more flexible and simpler to use. The new capabilities of these third-generation cores now allow for FP32 precision and twenty times the AI performance increase. Additionally, the FP64 support of Tensor Cores delivers two and a half times more compute power than older generation HPC applications.

MIG, or the multi-instance GPU, is also a new technical innovation that makes A100 GPU partitioning possible. Delivering various level of computing power for tasks of different sizes, it promises maximum return on investment while accounting for optimal resource utilization.