SShortSingh.
Back to feed

Developer Builds Fast ARM Matrix Multiplication Using NEON Assembly on Apple M2

0
·3 views

A developer has published a technical walkthrough on DEV Community detailing how to implement optimized matrix multiplication on ARM processors using NEON assembly instructions. The project targets Apple's M2 chip, which has a theoretical single-threaded peak of 112 GFlops for 32-bit floating-point matrix operations. Starting from a basic reference implementation, the author progressively applies techniques such as multiple accumulators and output tiling across register banks to reduce pipeline stalls and improve compute intensity. Performance improved significantly with these optimizations, reaching 15.95 GFlops in an intermediate version, with further gains expected through tiling using the chip's 32 available 128-bit registers. The author plans a follow-up article covering more advanced ARM extensions, specifically SME and SVE2.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

AWS Confirms Permanent Data Loss in Middle East Regions After Military Strikes

AWS publicly acknowledged on September 15, 2026, that customer data has been permanently lost across its Bahrain (me-south-1) and UAE (me-central-1) regions following a series of military attacks between March and July 2026. The Bahrain region suffered complete, unrecoverable data loss across all three Availability Zones, while one of three AZs in the UAE region also lost data irretrievably. AWS stated that the destruction spread across multiple Availability Zones, exceeding what its regional and multi-AZ architecture was designed to withstand — effectively acknowledging that multi-AZ redundancy does not protect against large-scale physical warfare. Structural damage, power disruption, and water damage from firefighting operations were cited as key causes of the infrastructure failure. Data lost belonged primarily to customers who had not migrated workloads or maintained backups in other regions before the outages occurred.

0
ProgrammingDEV Community ·

B.Tech Graduate Builds Secure School Portal After 2023 Dehradun Cyber Fraud Case

A recent computer science graduate from Graphic Era Hill University developed a Secure School Management Portal after learning about a 2023 cyber fraud incident in Dehradun, Uttarakhand. In that incident, school manager Shambhu Prasad Pancholi lost ₹95,000 after a fraudster posing as a student's parent sent malicious WhatsApp links that enabled four unauthorized bank transactions. The incident, reported by the Times of India, required no OTP and exploited the manager's trust in a routine fee-payment scenario. Motivated by the case, the developer built a web portal with separate access portals for admins, teachers, and students, incorporating multiple layers of security including authentication and access control. The project, completed as a final-year initiative in 2025, was a personal learning exercise and is not affiliated with the school involved in the original fraud.

0
ProgrammingDEV Community ·

How Runtime Injection Could Bring DLSS Upscaling to Unsupported Legacy Games

A technical concept dubbed DLSS5-Autopilot proposes a method to bring NVIDIA's Deep Learning Super Sampling (DLSS) to older games that never received native support. Rather than requiring game engine modifications, the hypothetical framework operates at the OS driver boundary, intercepting DirectX 12 and Vulkan graphics calls after the game engine has already issued its commands. The system is described as having three layers: an interception layer that hooks GPU API calls, a background inference engine running on Tensor Cores, and a shader hot-swap module that reroutes frames through the DLSS pipeline. This approach targets thousands of AAA titles released between 2015 and 2021 whose closed-source engines make traditional DLSS integration impossible. The article, originally published on tamiz.pro, notes that DLSS5-Autopilot is a hypothetical framework extrapolated from existing NVIDIA driver capabilities and user-space injection techniques, not a released product.