SparseTIR: Sparse Tensor Compiler for Deep Learning
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Updated
Mar 31, 2023 - Python
SparseTIR: Sparse Tensor Compiler for Deep Learning
Experimental tensor compiler with a Python frontend, typed SSA IR, semantics preservation tests, and Metal lowering.
Optimizing RetinaFace inference using TVM.
A tiny educational tensor compiler built from scratch to explain the core ideas behind Apache TVM.
SchedForge — A Target-Aware CPU Tensor Compiler. Forge tensor schedules into efficient CPU code.
Verified C++20 tensor compiler/runtime with bounded graph execution, Mul/ReGLU workloads, independent verification, and reproducible evidence.
Tensor compiler: PyTorch model -> graph fusion -> loop-nest IR -> tiling/AVX2/OpenMP C and CUDA shared-memory kernels, with autotuning and roofline analysis. In active development.
A tensor compiler that writes its own ARM64 machine code. Pure Python standard library — no LLVM, no assembler, no numpy. Every instruction verified against Apple's own assembler.
Tensor-aware meta-tracing JIT
Programmable AI inference runtime: xModel and XLang3 Tensor Expression to TensorGraph and hardware-specialized execution.
Tensor graph compiler in Rust: bit-exact CPU backends, ONNX import and an optional wgpu GPU backend (Vulkan, Metal, DX12). Every claim is tested and measured; GPU numerics are documented.
Tensor compiler using JIT kernel generation for ARM processors
A tensor compiler for the transformer nanoinfer runs by hand: graph IR with symbolic shapes, fusion, schedules and C codegen, checked against nanoinfer
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