The Sequence Scope: Triton: GPU Programming for Deep Neural Networks

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📝 Editorial: Triton: GPU Programming for Deep Neural Networks

For decades, the software industry has evolved, removing the dependencies in hardware architectures. Developers don’t spend any cycles thinking about hardware infrastructures when they develop web apps or APIs. The rise of deep learning seems to have brought us all the way back. Optimizations for GPU architectures are a common state in the lifecycle of deep learning models. Data science teams are often puzzled by the differences that GPU topologies can induce in the execution of neural networks. Optimizing for data partitioning, memory allocation, computation distributions, and other aspects are typically beyond the skill set of most data scientists.