[x86] AI Compute Extensions (ACE) Specification
Summary
The x86 Ecosystem Advisory Group has published the AI Compute Extensions (ACE) specification, defining new x86 instructions and register state for accelerating matrix multiplication and reduced precision data formats in machine learning workloads.
View Cached Full Text
Cached at: 06/18/26, 05:47 AM
Similar Articles
Is x86 ready to ACE it?
The article analyzes the new ACE specification from the x86 Ecosystem Advisory Group, which extends Intel's AMX for AI matrix multiplication with fixed tile sizes and outer product instructions, comparing it to Arm's SME.
AMD AI ENGAGE
The article discusses the AMD AI Engage Program, a community initiative for AI developers offering prizes, credits, and networking opportunities for building LLM apps and GenAI workflows.
The Powerhouse of the AI Chip (6 minute read)
This article explains how systolic arrays handle over 95% of AI chip compute, detailing their design, modes of operation, and why they are efficient for matrix multiplication.
@AMD: The next frontier for AI is physical @ServeTheHome details AMD Ryzen AI Embedded X100 Series processors and Kria AI pla…
AMD details its new Ryzen AI Embedded X100 Series processors and Kria AI platforms, aiming to lead in the physical AI market with high-performance compute and unified AI acceleration for edge systems.
@sumitdotml: week 25, 2026: cpu tensor core basics (add/mul, reduce, stride, 2d matmul, etc.) in c, reading some arcee
The author shares progress on building a CPU-only tensor library in C, covering basics like add/mul, reduce, strides, and 2D matmul, along with insights from reading Arcee's technical blogs on foundation models.