Open deep learning compiler stack for cpu, gpu and specialized accelerators

AutoKernel 是一个简单易用，低门槛的自动算子优化工具，提高深度学习算法部署效率。

Optimizing Mobile Deep Learning on ARM GPU with TVM

Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.

convert torch module to tensorrt network or tvm function

Reimplement RetinaFace using PyTorch.

Open, Modular, Deep Learning Accelerator

TVM stack: exploring the incredible explosion of deep-learning frameworks and how to bring them together

Large input size REAL-TIME Face Detector on Cpp. It can also support face verification using MobileFaceNet+Arcface with real-time inference. 480P Over 30FPS on CPU!

(MERGED) Rust bindings for TVM runtime

动手学习TVM核心原理教程

Benchmark scripts for TVM

DEPRECATED: this repo has been moved into https://github.com/dmlc/tvm/blob/master/rust

TVM learning and research

ANT framework's model database that provides DNN models for the various range of IoT devices

Benchmarks for popular classification and object detection models on CPUs and GPUs

This project contains a code generator that produces static C NN inference deployment code targeting tiny micro-controllers (TinyML) as replacement for other µTVM runtimes. This tools generates a runtime, which statically executes the compiled model. This reduces the overhead in terms of code size and execution time compared to having a dynamic on-device runtime.

TVM tutorials, which are adapted to EAIDK

Simple and compact virtual machine.

Assignments for Data Intensive Systems for Machine Learning Coursework

Docker container as ssh server

Post-training model quantization using apache's tvm.ai