Measuring energy usage: regular code vs. SIMD code

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • StringZilla

    Up to 10x faster strings for C, C++, Python, Rust, and Swift, leveraging SWAR and SIMD on Arm Neon and x86 AVX2 & AVX-512-capable chips to accelerate search, sort, edit distances, alignment scores, etc 🦖

  • The 3.5x energy-efficiency gap between serial and SIMD code becomes even larger when

    A. you do byte-level processing instead of float words;

    B. you use embedded, IoT, and other low-energy devices.

    A few years ago I've compared Nvidia Jetson Xavier (long before the Orin release), Intel-based MacBook Pro with Core i9, and AVX-512 capable CPUs on substring search benchmarks.

    On Xavier one can quite easily disable/enable cores and reconfigure power usage. At peak I got to 4.2 GB/J which was an 8.3x improvement in inefficiency over LibC in substring search operations. The comparison table is still available in the older README: https://github.com/ashvardanian/StringZilla/tree/v2.0.2?tab=...

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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