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Want a faster ML processor? Do it yourself! -- A framework for playing with custom opcodes to accelerate TensorFlow Lite for Microcontrollers (TFLM). . . . . . Online tutorial: https://google.githu…
Unified compiler/runtime for interfacing with PyTorch Dynamo.
A mini x86 linux debugger for teaching purposes
Playground with Neural Networks from scratch, using CPP
GroqFlow provides an automated tool flow for compiling machine learning and linear algebra workloads into Groq programs and executing those programs on GroqChip™ processors.
Must read research papers and links to tools and datasets that are related to using machine learning for compilers and systems optimisation
Enabling Flexible FPGA High-Level Synthesis of Tensorflow Deep Neural Networks
💥💻💥 A data-parallel functional programming language
Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure
A list of ICs and IPs for AI, Machine Learning and Deep Learning.
Automatically install github workflows for different types of projects (auto publish npm, pip, etc.)
Emscripten: An LLVM-to-WebAssembly Compiler
A pure, low-level tensor program representation enabling tensor program optimization via program rewriting. See the web demo at https://gussmith23.github.io/glenside-web-demo/
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Python library using the Futhark C backend via CFFI
Multi-backend GPU query engine written with Futhark