Who is this for?

This Learning Path is for software developers who are interested in porting SIMD code across Arm platforms.

What will you learn?

Upon completion of this Learning Path, you will be able to:

  • Describe how to use SIMD.info's tools and features, such as navigation, search, and comparison, to simplify the process of finding equivalent SIMD intrinsics between architectures to improve code portability.

Prerequisites

Before starting, you will need the following:

  • A basic understanding of SIMD.
  • Access to an Arm platform with a SIMD-supported engine, installed with recent versions of a C compiler such as Clang or GCC.

Summary

AI-assisted

This summary was drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.

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You’ll use SIMD.info to port SIMD intrinsics from a concise SSE4.2 C example to Arm Neon/ASIMD. You’ll search and compare intrinsic pages, and map comparison, addition, multiplication, and square-root operations. Then, you’ll adapt vector initialization and storage. You’ll replace the SSE calls with Neon constructs and compare the results with the original behavior, prioritizing correctness over performance.

Frequently asked questions

AI-assisted

These FAQs were drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.

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How do I find the Arm Neon equivalent for an SSE intrinsic in SIMD.info?
Search for the SSE intrinsic name, such as _mm_cmpgt_ps, and open its page. Review Purpose, Result, and Example, then use the comparison features to find the suggested Neon counterpart.
How do I decide between multiple Neon options shown for the same SSE intrinsic?
Compare the Purpose and Result descriptions, then review the examples to match your code’s semantics. Choose the option that matches your data types and intended operation sequence.
What should I change when adapting vector initialization and storage for Neon?
Replace SSE macro-style initialization, such as _mm_set_ps, with Neon’s brace initialization. Update stores for Neon’s memory operations and preserve the original element ordering.
Which operations from the example should I map when porting the code?
Map _mm_cmpgt_ps, _mm_add_ps, _mm_mul_ps, and _mm_sqrt_ps to their Neon equivalents in SIMD.info. These intrinsics cover the example’s comparison, addition, multiplication, and square-root operations.
What should I do if there is no one-to-one Neon replacement listed?
Use the Purpose and Result details to compose equivalent behavior from multiple Neon operations. Implement the closest semantic match and compare the output with the SSE baseline.
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