deep-learning-compiler

A compiler-first PyTorch alternative. MLIR-based Boom IR, Guile scripting, CUDA and CPU. On consumer GPUs it already beats llama.cpp’s LLM decode with the same kernels; the compiler makes the difference. GPLv3.

This is the project repository of our ESEC/FSE 2021 paper: A Comprehensive Study of Deep Learning Compiler Bugs.

GenCoG: A DSL-Based Approach to Generating Computation Graphs for TVM Testing (ISSTA‘23)

A differentiable Machine Learning framework built from scratch using Python and C.

How does torch.compile() achieve massive speedups despite highly optimized torch functions? See how operator fusion works!

⏳ Lightweight deep learning library and compiler suite built for educational purposes.

A Branchless, Zero-Jitter Ingress Router for 32-GPU Distributed Mesh Networks utilizing JAX/XLA and NCCL.

Top Deep Learning Compilers (Opensource) Star if you like it!

Use Pytorch Glow deep learning compiler in a Docker container inside your Github workflows

Occupancy aware C++/CUDA operator fusion decision engine and physical hardware benchmark suite (Tesla T4 calibrated).

Multi-model shared MCTS for Reasoning Compiler-style TVM tensor program optimization.

Bare-Metal Deep-Kernel Fused JIT & Memory Bandwidth Optimizer for Frontier AI Accelerators (Tenstorrent, Triton, CUDA, Apple Silicon).

A from-scratch deep learning compiler: it lowers trained ONNX models through two custom MLIR dialects and a full optimization pipeline to a binary instruction stream for a simulated edge NPU, then runs them in a cycle-costed simulator validated against onnxruntime.

TVM BYOC compiler targeting RISC-V RVV on BananaPi BPI-F3 (SpacemiT K1) — from YOLOv8n import to vectorized inference

My upstream C++/OpenMP contributions to PyTorch Internals (Inductor BMM kernels, Autograd, & Compiler correctness).