[CUDA] Add sm_121/Blackwell to known target (#24523) ## Summary Add initial CUDA known target support for `sm_121` / Blackwell NVIDIA GB10. The CUDA execution limits are based on local cudaDeviceProp results from an sm_121 device. Existing NVIDIA MMA ops are reused as a conservative baseline until Blackwell-specific MMA intrinsics are modeled. Related to #24477. #24477 reports that IREE does not currently recognize newer Blackwell CUDA targets such as `sm_120`. This PR addresses the same target-enablement path for `sm_121`, which is the Blackwell target I can validate locally on NVIDIA GB10. It intentionally does not add `sm_120` support because I do not have `sm_120` hardware to confirm the device limits or runtime behavior. ## Testing Tested locally on NVIDIA GB10 / `sm_121`. `sm_121` requires PTX 8.8. Using `+ptx88` compiles successfully. Compiled and ran a local abs.mlir smoke test: ``` ../iree-build/tools/iree-compile abs.mlir \ --iree-hal-target-device=cuda \ --iree-cuda-target=sm_121 \ --iree-cuda-target-features=+ptx88 \ -o abs_cuda.vmfb ../iree-build/tools/iree-run-module \ --device=cuda \ --module=abs_cuda.vmfb \ --function=abs \ --input=4xf32=-1,-2,3,-4 ``` Results: ``` 4xf32=1 2 3 4 ``` Compiled and ran a local matmul.mlir smoke test: ``` ../iree-build/tools/iree-compile matmul.mlir \ --iree-hal-target-device=cuda \ --iree-cuda-target=sm_121 \ --iree-cuda-target-features=+ptx88 \ -o matmul_cuda.vmfb ../iree-build/tools/iree-run-module \ --device=cuda \ --module=matmul_cuda.vmfb \ --function=matmul \ --input=128x256xf16=1 \ --input=256x128xf16=1 ``` Result: 128x128xf32 values are 256 as expected. --------- Signed-off-by: Charlie-Tsai1123 <charlie1123tsai@gmail.com>
IREE (Intermediate Representation Execution Eenvironment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.
See our website for project details, user guides, and instructions on building from source.
Releases notes are published on GitHub releases.
| Package | Release status |
|---|---|
| GitHub release (stable) | |
| GitHub release (nightly) | |
iree-base-compiler | |
iree-base-runtime |
For more details on the release process, see https://iree.dev/developers/general/release-management/.
| Operating system | Build status |
|---|---|
| Linux | |
| macOS | |
| macOS |
For the full list of workflows see https://iree.dev/developers/general/github-actions/.
See our website for more information.
Community meeting recordings: IREE YouTube channel
| Date | Title | Recording | Slides |
|---|---|---|---|
| 2025-06-10 | Data-Tiling in IREE: Achieving High Performance Through Compiler Design (AsiaLLVM) | recording | slides |
| 2025-05-17 | Introduction to GPU architecture and IREE's GPU CodeGen Pipeline | recording | slides |
| 2025-02-12 | The Long Tail of AI: SPIR-V in IREE and MLIR (Vulkanised) | recording | slides |
| 2024-10-01 | Unveiling the Inner Workings of IREE: An MLIR-Based Compiler for Diverse Hardware | recording | |
| 2021-06-09 | IREE Runtime Design Tech Talk | recording | slides |
| 2020-08-20 | IREE CodeGen (MLIR Open Design Meeting) | recording | slides |
| 2020-03-18 | Interactive HAL IR Walkthrough | recording | |
| 2020-01-31 | End-to-end MLIR Workflow in IREE (MLIR Open Design Meeting) | recording | slides |
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.