Multiple Use-cases, One Solution!

E2E’s GPU Cloud

is suitable for a wide range of uses

• 

  AI Model Training and Inference:

  Earlier, GPUs were confined to perform domain-specific tasks with either training or inference. With NVIDIA A100, you can get the best of both worlds with an accelerator for training as well as inference. Compare to earlier cards, we can speedup training and inference by 3X to 7X.

• 

  Image/Video Decoding:

  One of the significant challenge in achieving high end-to-end throughput in a DL platform is to be able to keep the input video decoding performance matching the training and inference performance. A100 GPU fixed this by adding 5 NVDEC (NVIDIA DECode) unit compared to 1 Unit in earlier GPU Card.

• 

  High-Performance Computing:

  A100 introduces double-precision Tensor Cores, 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.

• 

  Deep Video Analytics:

  Media publishers to surveillance systems, deep video analytics is the new vogue for extracting actionable insights from streaming video clips. NVIDIA A100’s memory bandwidth of 1.5 terabytes per second makes it perfect choice for image recognition, contactless attendance, and other deep learning applications.

• 

  Language Model Training:

  Natural Language Processing (NLP) has seen rapid progress in recent years. It is no longer possible to fit large models parameters in the main memory of even the largest GPU. NVIDIA A100 is the flagship product of the NVIDIA which is the only solution can run 1-trillion-parameter model in reasonable time with the scaling feature of A100-based systems connected by the new NVIDIA NVSwitch and Mellanox State of Art InfiniBand and ethernet solution.