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Add SPIR-V matmul variants/specialization constants for various workloads and targets #44

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benvanik opened this issue Oct 13, 2019 · 1 comment
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Add SPIR-V matmul variants/specialization constants for various workloads and targets #44

benvanik opened this issue Oct 13, 2019 · 1 comment
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Runtime Optimization

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@benvanik
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Enabling the use of extensions (such as cooperative matrix) and special codepaths for various runtime-detectable capabilities would be a good way of evaluating the flexibility of the compiler. Most of this work is predicated on support for such features in MLIR's SPIR-V dialect (if we want to go that route) and the design of the integration, however we could do some proof of concept work for benchmarking independently.
@benvanik benvanik added this to Ideas in Runtime Optimization via automation Oct 13, 2019
@benvanik
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Was done and is now getting removed.

Runtime Optimization automation moved this from Ideas to Done Mar 19, 2020
@GMNGeoffrey GMNGeoffrey mentioned this issue Mar 29, 2023
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@dpackwood dpackwood mentioned this issue Sep 8, 2023
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stellaraccident pushed a commit that referenced this issue Sep 24, 2023
Add a packaging workflow. (#44)
ab703ba 
Also fixes some other odds and ends:

* Switches to larger runners.
* Uses the compiler's native support for memory outputs (vs direct use
of memfd). This removes special casing that would be needed when
building for old glibc versions (the compiler already does the right
thing in these cases).
* Adds a :plugins target to build everything.
* Fixes the CUDA SDK env var to include the "_DIR" suffix.
* Installs the needed parts of the CUDA SDK
* Forks the build_linux_packages.sh that everyone uses and builds binary
plugins. Will extend this later to build Python wheels that
auto-configure.
@gabeweisz gabeweisz mentioned this issue Mar 25, 2024
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@benvanik