Machine Learning Compiler
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About
Machine Learning Compiler (MLC) addresses the challenge of deploying AI models in diverse production environments. It tackles issues related to model and environment choices, minimizing dependencies, broader model coverage, leveraging hardware primitives, reducing memory footprint, and scaling to larger environments. MLC combines ML programming abstractions, learning-driven search, compilation, and optimized library runtime to optimize training and inference. This tutorial sequence provides a comprehensive study of key elements in this emerging field, covering machine learning program representation, automatic optimization techniques, and approaches to optimize dependency, memory, and performance in end-to-end machine learning deployment.
Platform
Task
Features
• optimized library runtime
• compilation
• learning-driven search
• ml programming abstractions
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