NVIDIA CUDA Tile IR Open-Sourced
([NVIDIA] 3 Hours Ago
CUDA Tile IR Open-Source)
- Reference: 0001601748
- News link: https://www.phoronix.com/news/NVIDIA-CUDA-Tile-IR-Open-Source
- Source link:
As a wonderful Christmas gift to open-source fans, NVIDIA dropped their proprietary license on the CUDA Tile intermediate representation and has now made the IR open-source software.
Earlier this month with CUDA 13.1 [1]NVIDIA announced the CUDA Tile programming model as " the largest and most comprehensive update to the CUDA platform since it was invented two decades ago " The intermediate representation (IR) to CUDA Tile is now open-source software.
The CUDA Tile IR is based on the [2]MLIR intermediate representation out of the LLVM project. CUDA Tile IR being derived from Multi-Level Intermediate Representation (MLIR) is very significant and could help in seeing CUDA Tile IR being supported in non-NVIDIA environments. [3]AMD makes use of MLIR to varying degrees in their AI/compute environment, Google's IREE plays a big role here across different vendors, [4]Intel has a dialect of MLIR for their hardware , etc. Various IR frameworks like ONNX-MLIR, MLIRE-AIE, Torch-MLIR, and others exist too. With CUDA Tile IR being based on MLIR could help in lowering it and ultimately bringing CUDA Tile IR targeting software to other GPUs/accelerators. At the very least CUDA Tile IR being open-source will eventually help efforts like [5]ZLUDA .
The CUDA Tile code consists of the Tile MLIR dialect, Python API bindings, the bytecode representation, and a conformance test suite.
"CUDA Tile IR is an MLIR-based intermediate representation and compiler infrastructure for CUDA kernel optimization, focusing on tile-based computation patterns and optimizations targeting NVIDIA tensor core units. The project provides a comprehensive ecosystem for expressing and optimizing tiled computations for NVIDIA GPUs, simplifying the development of high-performance CUDA kernels through abstractions for common tiling patterns, memory hierarchy management, and GPU-specific optimizations.
It's fabulous seeing NVIDIA make CUDA Tile IR open-source and will be interesting to see what the future holds in 2026. The open-source code can be found on [6]GitHub . The open-source code is under an Apache 2.0 license.
[1] https://www.phoronix.com/news/NVIDIA-CUDA-13.1
[2] https://www.phoronix.com/search/MLIR
[3] https://www.phoronix.com/news/AMD-Ryzen-AI-LLVM-MLIR-Coding
[4] https://www.phoronix.com/news/Intel-XeVM-MLIR-In-LLVM
[5] https://www.phoronix.com/search/ZLUDA
[6] https://github.com/NVIDIA/cuda-tile
Earlier this month with CUDA 13.1 [1]NVIDIA announced the CUDA Tile programming model as " the largest and most comprehensive update to the CUDA platform since it was invented two decades ago " The intermediate representation (IR) to CUDA Tile is now open-source software.
The CUDA Tile IR is based on the [2]MLIR intermediate representation out of the LLVM project. CUDA Tile IR being derived from Multi-Level Intermediate Representation (MLIR) is very significant and could help in seeing CUDA Tile IR being supported in non-NVIDIA environments. [3]AMD makes use of MLIR to varying degrees in their AI/compute environment, Google's IREE plays a big role here across different vendors, [4]Intel has a dialect of MLIR for their hardware , etc. Various IR frameworks like ONNX-MLIR, MLIRE-AIE, Torch-MLIR, and others exist too. With CUDA Tile IR being based on MLIR could help in lowering it and ultimately bringing CUDA Tile IR targeting software to other GPUs/accelerators. At the very least CUDA Tile IR being open-source will eventually help efforts like [5]ZLUDA .
The CUDA Tile code consists of the Tile MLIR dialect, Python API bindings, the bytecode representation, and a conformance test suite.
"CUDA Tile IR is an MLIR-based intermediate representation and compiler infrastructure for CUDA kernel optimization, focusing on tile-based computation patterns and optimizations targeting NVIDIA tensor core units. The project provides a comprehensive ecosystem for expressing and optimizing tiled computations for NVIDIA GPUs, simplifying the development of high-performance CUDA kernels through abstractions for common tiling patterns, memory hierarchy management, and GPU-specific optimizations.
It's fabulous seeing NVIDIA make CUDA Tile IR open-source and will be interesting to see what the future holds in 2026. The open-source code can be found on [6]GitHub . The open-source code is under an Apache 2.0 license.
[1] https://www.phoronix.com/news/NVIDIA-CUDA-13.1
[2] https://www.phoronix.com/search/MLIR
[3] https://www.phoronix.com/news/AMD-Ryzen-AI-LLVM-MLIR-Coding
[4] https://www.phoronix.com/news/Intel-XeVM-MLIR-In-LLVM
[5] https://www.phoronix.com/search/ZLUDA
[6] https://github.com/NVIDIA/cuda-tile