Recently [shraiwi] decided to have a bit of good nerdy fun and implement the FAST machine vision algorithm on an ESP32-S3 using its SIMD ISA. This involves using the assembly instructions for the ISA, making for an exciting opportunity to become familiar with this part of this Xtensa Lx7-based twin-core MCU.
The Features from Accelerated Segment Test (FAST) algorithm is a corner detection method that can determine with reasonable accuracy and in real-time whether a given input frame contains said corners which thus may correspond to objects and other characteristics worthy of note. This is essential for machine vision, with machine learning able to bump up its recognition accuracy even more.
Implementing this algorithm on the ESP32-S3 proved to be a bit of a challenge due to somewhat limited SIMD ISA. Missing instructions included things like comparisons between unsigned byte values, and there is no support for direct misaligned reads.
All of these required some creative coding to work around, but in the end the ESP32-S3 running at 240 MHz was able to process a VGA stream in real-time at 30 FPS. This means about a 2x speed-up over a naive implementation using only non-SIMD instructions.
Solana developers have advanced SIMD-0112 through core review as part of work aimed at reducing block-propagation latency.
The proposal is approved for implementation work but is not yet a fully deployed mainnet feature.
Validator software rollout is expected to arrive through a future client release.
Solana developers are moving forward with another performance-focused improvement, this time targeting the latency between validators as blocks propagate through the network.
SIMD-0112 has cleared core review and is moving into implementation work.
Lower Latency Matters Most Under Load
Solana’s performance story has always been about more than raw transaction counts.
A fast network also needs validators to receive and process block information quickly enough to stay synchronized during periods of heavy activity.
Reducing propagation latency can help improve that coordination and lower the risk that performance degrades when traffic spikes.
SIMD-0112 is aimed at that part of the stack.
The proposal is technical rather than user-facing, but it fits Solana’s broader effort to keep improving execution and validator performance as the network supports more trading, payments and consumer applications.
Approval Is Not The Same As Mainnet Deployment
The status is important.
SIMD-0112 has progressed through developer review, but that does not mean every validator is already running the change.
Implementation still needs to move into client software and through the normal release process before it becomes part of mainnet operation.
That makes this a roadmap milestone rather than a completed network upgrade.
For SOL holders, there is no token migration or wallet action involved.
For validator operators, the eventual client release will matter much more.
Solana’s ability to keep scaling depends on these lower-level improvements being deployed safely, not simply proposed.
The interesting part of SIMD-0112 is therefore not a headline speed number.
It is the continued focus on reducing bottlenecks inside the validator network — the kind of work that determines whether high throughput remains reliable when the chain is busy rather than only in ideal conditions.
Latency work can also have second-order effects for traders and applications. Faster propagation is not only about headline speed; it can reduce the window in which different validators are working from slightly different views of the network. That can matter for high-frequency markets, liquidations and other applications where a fraction of a second changes execution quality. Solana has already shown that raw throughput attracts demanding workloads. The engineering challenge now is making those workloads predictable during stress. SIMD-0112 is one piece of that broader effort rather than a standalone fix for every performance issue.
This article was written by the News Desk and edited by Samuel Rae.
Login
