NVIDIA Launches A100 GPU Based on the Breakthrough Ampere Architecture
NVIDIA A100 GPU is a design breakthrough in the NVIDIA Ampere architecture — offering the company’s largest leap in performance to date within its eight generations of GPUs — to unify AI training and inference and boost performance by up to 20x over its predecessors. A universal workload accelerator, the A100 is also built for data analytics, scientific computing, and cloud graphics.
The powerful trends of cloud computing and AI are driving a tectonic shift in data center designs so that what was once a sea of CPU-only servers is now GPU-accelerated computing, said Jensen Huang, founder, and CEO of NVIDIA.
“NVIDIA A100 GPU is a 20x AI performance leap and an end-to-end machine learning accelerator — from data analytics to training to inference. For the first time, scale-up and scale-out workloads can be accelerated on one platform. NVIDIA A100 will simultaneously boost throughput and drive down the cost of data centers.”
New elastic computing technologies built into A100 make it possible to bring right-sized computing power to every job. A multi-instance GPU capability allows each A100 GPU to be partitioned into as many as seven independent instances for inferencing tasks, while third-generation NVIDIA NVLink® interconnect technology allows multiple A100 GPUs to operate as one giant GPU for ever-larger training tasks.
NVIDIA A100 GPUS is all set to immediate adoption worldwide by the likes of Microsoft, DoorDash, Adobe, and many more. Early adopters also include national laboratories and some of the world’s leading higher education and research institutions, each using A100 to power their next-generation supercomputers like Indiana University, Karlsruhe Institute of Technology, Max Planck Computing and Data Facility to name a few. NVIDIA A100 will also hit the cloud soon via its cloud partners like Alibaba Cloud, AWS, Baidu Cloud, Google Cloud, Microsoft Azure, Oracle, and Tencent Cloud are planning to offer A100-based services.
Five Breakthroughs of NVIDIA A100 GPU
The NVIDIA A100 GPU is a technical design breakthrough fueled by five key innovations:
- NVIDIA Ampere architecture — At the heart of A100 is the NVIDIA Ampere GPU architecture, which contains more than 54 billion transistors, making it the world’s largest 7-nanometer processor.
- Third-generation Tensor Cores with TF32 — NVIDIA’s widely adopted Tensor Cores are now more flexible, faster and easier to use. Their expanded capabilities include new TF32 for AI, which allows for up to 20x the AI performance of FP32 precision, without any code changes. In addition, Tensor Cores now support FP64, delivering up to 2.5x more compute than the previous generation for HPC applications.
- Multi-instance GPU — MIG, a new technical feature, enables a single A100 GPU to be partitioned into as many as seven separate GPUs so it can deliver varying degrees of compute for jobs of different sizes, providing optimal utilization and maximizing return on investment.
- Third-generation NVIDIA NVLink — Doubles the high-speed connectivity between GPUs to provide efficient performance scaling in a server.
- Structural sparsity — This new efficiency technique harnesses the inherently sparse nature of AI math to double the performance.
Together, these new features make the NVIDIA A100 ideal for diverse, demanding workloads, including AI training and inference as well as scientific simulation, conversational AI, recommender systems, genomics, high-performance data analytics, seismic modeling, and financial forecasting.
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