Taichi & PyTorch 03: Accelerate PyTorch with Taichi - Data Preprocessing & High-performance ML Operator Customization
Our previous blogs (Taichi & PyTorch 01 and 02) pointed out that Taichi and Torch serve different application scenarios can they complement each other? And the answer is an unequivocal yes! In this blog, we will use two simple examples to explain how to use Taichi kernel to implement data preprocessing operators or custom ML operators. With Taichi, you can accelerate your ML model development with ease and get rid of the tedious low-level parallel programming (CUDA for example) for good.
Taichi & PyTorch 02: Data containers
In my last blog, I compared the purposes and design philosophies of Taichi Lang and PyTorch. Now, it's time to take a closer look at their data containers - the most essential part of any easy-to-use programming language.
Taichi & PyTorch 01: Underlying difference
"How does Taichi differ from PyTorch? They are both embedded in Python and can run on GPU! And when should I choose Taichi over PyTorch or the other way around?"
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