Building a Deep Learning Framework from Scratch: 'Forge' Shows Impressive Progress
infrastructure#framework📝 Blog|Analyzed: Apr 11, 2026 15:38•
Published: Apr 11, 2026 15:26
•1 min read
•r/deeplearningAnalysis
A developer is taking on the incredible challenge of building a deep learning framework called Forge entirely from scratch in C++. This exciting project recently achieved a major milestone by successfully training an MLP on the MNIST dataset on a CPU, proving its functional core. The ultimate goal of this ambitious endeavor is to eventually train a modern Transformer entirely within this custom architecture.
Key Takeaways
- •The 'Forge' framework successfully utilizes an autodiff engine and tensor system to stably decrease loss over epochs.
- •Future updates will include a CUDA backend, allowing the framework to harness GPU acceleration for heavy workloads.
- •The core architecture already features fused operations, such as combining log softmax and CrossEntropy for optimized performance.
Reference / Citation
View Original"i am building a deep learning framework called "Forge" completely from scratch in C++, its nowhere near complete yet, training MNIST Classifier shows a functional core on CPU"
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