tvm and tvm-ffi
TVM-FFI is a foreign function interface layer that enables language bindings and interoperability for TVM's compiler runtime, making it a complement that extends TVM's accessibility rather than a standalone alternative.
About tvm
apache/tvm
Open Machine Learning Compiler Framework
This framework helps machine learning engineers and researchers take a trained machine learning model and optimize it to run efficiently on various hardware, from powerful GPUs to tiny embedded devices. It takes your existing model definition and outputs a highly optimized, ready-to-deploy module that performs inference quickly and uses minimal resources. This is for professionals building and deploying machine learning applications who need fine-grained control over performance.
About tvm-ffi
apache/tvm-ffi
Open ABI and FFI for Machine Learning Systems
This project helps machine learning system developers build and distribute custom kernel libraries or extend existing ML frameworks like PyTorch or JAX. It provides a stable way for different programming languages and ML frameworks to exchange data and call functions with minimal overhead, allowing for a single distribution package to support multiple environments. The end user is an ML systems engineer or library developer creating high-performance components.
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