[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>
2 files changed
tree: bad1a0224bbb8a505afe5c62f556b0887e3f4719
  1. .github/
  2. build_tools/
  3. compiler/
  4. docs/
  5. experimental/
  6. integrations/
  7. lib/
  8. llvm-external-projects/
  9. runtime/
  10. samples/
  11. tests/
  12. third_party/
  13. tools/
  14. .bazel_to_cmake.cfg.py
  15. .bazelignore
  16. .bazelrc
  17. .bazelversion
  18. .clang-format
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  20. .gitattributes
  21. .gitignore
  22. .gitmodules
  23. .pre-commit-config.yaml
  24. .yamllint.yml
  25. AUTHORS
  26. BUILD.bazel
  27. CITATION.cff
  28. CMakeLists.txt
  29. configure_bazel.py
  30. CONTRIBUTING.md
  31. LICENSE
  32. MAINTAINERS.md
  33. MODULE.bazel
  34. README.md
  35. RELEASING.md
README.md

IREE: Intermediate Representation Execution Environment

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.

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For more details on the release process, see https://iree.dev/developers/general/release-management/.

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  • MLIR topic within LLVM Discourse: IREE is enabled by and heavily relies on MLIR. IREE sometimes is referred to in certain MLIR discussions. Useful if you are also interested in MLIR evolution.

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IREE Architecture IREE Architecture

See our website for more information.

Presentations and talks

Community meeting recordings: IREE YouTube channel

DateTitleRecordingSlides
2025-06-10Data-Tiling in IREE: Achieving High Performance Through Compiler Design (AsiaLLVM)recordingslides
2025-05-17Introduction to GPU architecture and IREE's GPU CodeGen Pipelinerecordingslides
2025-02-12The Long Tail of AI: SPIR-V in IREE and MLIR (Vulkanised)recordingslides
2024-10-01Unveiling the Inner Workings of IREE: An MLIR-Based Compiler for Diverse Hardwarerecording
2021-06-09IREE Runtime Design Tech Talkrecordingslides
2020-08-20IREE CodeGen (MLIR Open Design Meeting)recordingslides
2020-03-18Interactive HAL IR Walkthroughrecording
2020-01-31End-to-end MLIR Workflow in IREE (MLIR Open Design Meeting)recordingslides

License

IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.