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Overview
Apache TVM An Open Machine Learning Compiler Framework Learn More Apache TVM is a machine learning compilation framework, following the principle of Python-first development and universal deployment.
News
TIRx: An Open Compiler Stack for Evolving Frontier ML Kernels
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Building an Open ABI and FFI for ML Systems
We are currently living in an exciting era for AI, where machine learning systems and infrastructures are crucial for training and deploying efficient AI models. The modern machine learning systems landscape comes rich with diverse components, including p
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Apache TVM Unity: a vision for the ML software & hardware ecosystem in 2022
Apache TVM Unity is a roadmap for the TVM ecosystem in 2022. We see a broader shift coming in the way that machine learning system stacks optimize for flexibility and agility in the face of a rapidly changing hardware landscape. TVM will evolve to break d
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Introducing TVM Auto-scheduler (a.k.a. Ansor)
Optimizing the execution speed of deep neural networks is extremely hard with the growing model size, operator diversity, and hardware heterogeneity. From a computational perspective, deep neural networks are just layers and layers of tensor computations.
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Bring Your Own Datatypes: Enabling Custom Datatype Exploration in TVM
In this post, we describe the Bring Your Own Datatypes framework, which enables the use of custom datatypes within TVM.
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How to Bring Your Own Codegen to TVM
To free data scientists from worrying about the performance when developing a new model, hardware backend providers (e.g., Intel, NVIDIA, ARM, etc) either provide kernel libraries such as cuBLAS or cuDNN with many commonly used deep learning kernels, or p
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