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Intel's AMX extension: How x86 architecture is evolving for matrix workloads

CPU designs must evolve to keep up with changing workloads.

Insighttechnologymachine learningprogramming

chipsandcheese.com·Hacker News: Front Page·3d ago·20 min read

Why Unified Memory Lets Mini PCs Run Large AI Models That GPUs Can't Fit

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vettedconsumer.com7d ago

First Instruction Set Architecture for Dynamical System Hardware Aims to Standardize Analog Computing

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Shared by @NaveenGRao ↗

unconv.ai16d ago

Reverse-Engineered Analysis of Apple Neural Engine Architecture Across A11-A18 and M1-M5 Chips

The Apple Neural Engine (ANE) is the fixed-function matrix accelerator that has shipped in Apple systems-on-chip since the A11-class iPhone and iPad chips and the M1-class Mac chips, exposed to applications only through the Core ML model framework. This g

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Shared by @hn100.atproto.rocks ↗

arxiv.org17d ago

FPGA-Based Hardware Architecture Enables Real-Time Decoding of Quantum LDPC Codes

The architecture for the DX, DZ decoder. Memory elements shown in blue (light for RAM, dark for ROM). I/O in purple. Sub-modules in gray. Researchers from the IMDEA Software Institute, Nokia Bell Labs

Newstechnologysciencehardware architecture

quantumcomputingreport.com·Tech by Flipboard·22d ago·4 min read

PlayStation Architecture: A Technical Deep Dive into Sony's First Console CPU Design

An in-depth analysis that explains how this console works internally

Insighttechnologygaminghardware architecture

copetti.org·Hacker News: Front Page·1mo ago·29 min read

NextSilicon CEO Discusses Runtime-Reconfigurable Processors That Adapt to Code

In this podcast: What if hardware adapted itself to your code instead of forcing developers to optimize for the hardware?

technologydesignhardware architecture

eetimes.com·Tech by Flipboard·1mo ago·30 min read

Understanding the Super Nintendo's Hardware Architecture: Clock Signals and Component Synchronization

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fabiensanglard.net2mo ago

Research Directions for Overcoming Memory and Interconnect Challenges in Large Language Model Inference Hardware

Large Language Model (LLM) inference is hard. The autoregressive Decode phase of the underlying Transformer model makes LLM inference fundamentally different from training. Exacerbated by recent AI trends, the primary challenges are memory and interconnec

Insighttechnologyartificial intelligence

arxiv.org5mo ago