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nullprogram.com | ||
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www.nickwilcox.com
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| | | | | In the previous article on auto-vectorization we looked at the different SIMD instruction set families on X86-64. We saw how he target-feature compiler flag and #[target_feature()] attribute gave us more control over the instructions used in the generated assembly. | |
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ashvardanian.com
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| | | | | David Patterson had recently mentioned that (rephrasing): The programmers may benefit from using complex instruction sets directly, but it is increasingly challenging for compilers to automatically generate them in the right spots. In the last 3-4 years I gave a bunch of talks on the intricacies of SIMD programming, highlighting the divergence in hardware and software design in the past ten years. Chips are becoming bigger and more complicated to add more functionality, but the general-purpose compilers like GCC, LLVM, MSVC and ICC cannot keep up with the pace. Hardly any developer codes in Assembly today, hoping that the compiler will do the heavy lifting. | |
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www.da.vidbuchanan.co.uk
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| | | | | [AI summary] The blog post discusses the implementation of Conway's Game of Life using Python with optimized techniques such as SWAR (Shift and Arithmetic Word) and parallel processing. The author leverages Python's native integer operations for SIMD-like acceleration, eliminating the need for explicit SIMD instructions. They also use SDL2 for rendering and achieve high frame rates through parallel execution across multiple processes. The post highlights performance gains, comparing the optimized approach with naive implementations and exploring potential further optimizations using lower-level languages or GPU acceleration. | |
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hugozap.com
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| | | A simple example of how to use WebAssembly in the browser and what the toolchain looks like. | ||
