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Refer to https://github.com/numba/llvmlite/issues/270
(EDIT)
The llvmlite issue identified several ways to enable autovec of loops. But, we don't know which technique offers the best performanc…
sklam updated
6 years ago
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Hi, thanks for the presentation you gave at Inria Parietal today ;)
I just wanted to give a heads up on https://github.com/QuantStack/xsimd which might be a useful tool to make kernel computation m…
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project: https://compilers.cs.uni-saarland.de/projects/wfv/
papar: https://compilers.cs.uni-saarland.de/papers/karrenberg_wfv.pdf
slide: https://compilers.cs.uni-saarland.de/projects/wfv/wfv_cgo11_s…
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Idea:
Each lane of SIMD computes an interleaved path in the input. Maybe 8-chars at a time. Compiler should be able to produce masked operations automatically in case of predicted or not predicted …
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Our current configuration logic for SIMD vectorization support is as follows:
- We select the level of vectorization support statically at (deal.II library) configuration time and record it via `DEA…
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Two use cases:
1. More significantly, sometimes auto-vectorization with SIMD makes a function slower. There are the environment variables to disable auto-vectorization, but that affects _all_ code …
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This may be a regression between LLVM version 17.0.1 and 18.1.0.
The issue is still present in the main branch as of version 19.0.0 (dbc3e26c25587e5460ae12caed84cb09197c4ed7).
Consider the followi…
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### Use case
Hi , as we all know java 21 has simd capability.
With simd we can assign variables much faster then regular sisd instructions.
Can we increase the performance of applications by util…
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Hello,
The following simple code produces a pretty inefficient assembly code with the flags `-O3 -mavx2 -mfma -ffast-math` whatever the version of Clang used. This can be seen on [GodBolt](https://…
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We have observed unexpected loss of vectorization effort by the compiler when compiling the code below. Target was amd64 machine with AVX2 instruction set supported.
```rust
type T = u32;
#[i…