NVIDIA Tesla T4 v.s V100

ATTENTION: This blog post is a work in progress, consisting of preliminary notes. I will notify you once it’s completed. Thank you for your understanding.

The Tesla T4 and V100 are both graphics processing units (GPUs) manufactured by NVIDIA, but they have some key differences in terms of their architecture and intended usage.

1. Architecture:
— Tesla T4: The T4 is based on the Turing architecture, which was introduced by NVIDIA in 2018. It features 16GB of GDDR6 memory and 16GB of GPU memory with a memory bandwidth of 320 GB/s. The T4 has 16 Streaming Multiprocessors (SMs) and a total of 2,560 CUDA cores.
— Tesla V100: The V100 is based on the Volta architecture, which was introduced by NVIDIA in 2017. It offers significantly higher performance compared to the T4. The V100 comes in two variants: 16GB and 32GB. It has a memory bandwidth of up to 900 GB/s and features 5,120 CUDA cores with 80 SMs.

2. Performance:
— Tesla T4: The T4 is designed for a wide range of workloads, including artificial intelligence (AI) inference, machine learning, and deep learning. It provides excellent performance for inference tasks, making it suitable for real-time applications and deployment in data centers.
— Tesla V100: The V100 is a high-performance GPU specifically designed for demanding AI and high-performance computing (HPC) workloads. It delivers exceptional performance for both training and inference tasks and is often used in research institutions and data centers where…