Network address parsing is ubiquitous in Go applications, yet the standard library implementations process strings character by character, leaving significant performance on the table. In this comprehensive exploration, we’ll combine the SPMD concepts from our previous blogs to build a high-performance IPv4 parser inspired by Wojciech Muła’s SIMD research.

This post demonstrates how SPMD Go could be used to keep code readable, but significantly improve performance by applying the techniques we’ve explored: parallel processing, reduction operations, and cross-lane communication. This example is a lot less complex than trying things like base64 and shows the benefit of language-level support for parallel data manipulation in my opinion.

When Independent Lanes Aren’t Enough

Most SPMD examples show lanes working independently—each processing its own data without communicating with neighbors. But real-world algorithms often require cross-lane communication: lanes must exchange data to solve the problem correctly. Base64 decoding demonstrates this problem, transforming groups of 4 ASCII characters into groups of 3 bytes through coordinated lane operations.

Printf helper

One of the first and most repetitive tasks for doPrintf is to find % in a string. Right now, this is just iterating one character after another. This is very simple to parallelize using data parallelism and would look like the code below.