Tenstorrent
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TT-Metalium™ is Tenstorrent's open-source, low-level AI hardware SDK designed to provide developers with direct access to the underlying hardware components for custom kernel development and experimentation. Unlike other platforms, TT-Metalium™ offers complete transparency with no black boxes, encrypted APIs, or hidden functions, making it ideal for developers aiming to customize models, create new ones, or run non-machine learning code.
TT-Forge™ is Tenstorrent's MLIR-based compiler, designed to seamlessly integrate with various machine learning (ML) frameworks, including PyTorch, JAX, TensorFlow, and ONNX. It serves as a bridge between high-level models and Tenstorrent hardware, facilitating efficient compilation and execution of AI workloads. By leveraging open-source technologies such as OpenXLA, LLVM’s MLIR, and torch-mlir, TT-Forge™ offers a flexible and extensible foundation for AI development. Its architecture supports the ingestion of models from multiple frameworks, enabling a structured approach to compilation and optimization. This integration ensures that developers can build and deploy AI models with ease, maximizing performance on Tenstorrent hardware.
