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View article: TorchTitan: One-stop PyTorch native solution for production ready LLM pre-training
TorchTitan: One-stop PyTorch native solution for production ready LLM pre-training Open
The development of large language models (LLMs) has been instrumental in advancing state-of-the-art natural language processing applications. Training LLMs with billions of parameters and trillions of tokens require sophisticated distribut…
View article: TorchBench: Benchmarking PyTorch with High API Surface Coverage
TorchBench: Benchmarking PyTorch with High API Surface Coverage Open
Deep learning (DL) has been a revolutionary technique in various domains. To facilitate the model development and deployment, many deep learning frameworks are proposed, among which PyTorch is one of the most popular solutions. The perform…
View article: Using Python for Model Inference in Deep Learning
Using Python for Model Inference in Deep Learning Open
Python has become the de-facto language for training deep neural networks, coupling a large suite of scientific computing libraries with efficient libraries for tensor computation such as PyTorch or TensorFlow. However, when models are use…
View article: Intel nGraph: An Intermediate Representation, Compiler, and Executor for Deep Learning
Intel nGraph: An Intermediate Representation, Compiler, and Executor for Deep Learning Open
The Deep Learning (DL) community sees many novel topologies published each year. Achieving high performance on each new topology remains challenging, as each requires some level of manual effort. This issue is compounded by the proliferati…