Optimization Techniques for 27.8 Million MNIST Inferences per Second on Tesla T4
Published:Dec 28, 2025 08:15
•1 min read
•Zenn ML
Analysis
This article discusses optimization techniques to achieve high-speed MNIST inference on a Tesla T4 GPU, a six-year-old generation GPU. The core of the article is based on a provided Colab notebook, aiming to replicate and systematize the optimization methods used to achieve a rate of 28 million inferences per second. The focus is on practical implementation and reproducibility within the Google Colab environment. The article likely details specific techniques such as model quantization, efficient data loading, and optimized kernel implementations to maximize the performance of the T4 GPU for this specific task. The provided link to the Colab notebook allows for direct experimentation and verification of the claims.
Key Takeaways
Reference
“The article is based on the content of the provided Colab notebook (mnist_t4_ultrafast_inference_v7.ipynb).”