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Intel Xeon 658X Review: 24 Cores, Massive Memory Bandwidth Tested

 🏗️System Design
hothardware.com·

Now available: Amazon EC2 M9g and M9gd instances powered by new AWS Graviton5 processors

 📊Observability  Content type: Blog

A Database You Can See

 🎮Game Engines  Content type: Blog
nockawa.github.io·

AMD is resurrecting a 4-year-old CPU, and it exposes some uncomfortable truths about the PC industry

 🖥️Emulation
xda-developers.com·

Beyond the Memory Wall: The CPU Was Helping You All Along

 🗄️Database Sharding  Content type: Blog
prawns.dev··Hacker News

Amazon's Graviton5 processor will go head-to-head with Intel and AMD in the cloud

 🗄️Database Sharding  Content type: News
tweaktown.com·

Rayforce

 ⚙️CPU Microarchitecture  Content type: Code

A Fast Locality Simulator for GEMM Design-Space Exploration on Multi-Chiplet GPUs

 🔁Cache Coherence  Content type: Academic
arxiv.org·

GEEKOM A7 2026 Edition (AMD Ryzen 5 7545U) mini PC review - Part 1: specifications, unboxing, teardown, and first boot - CNX Software

 🖥️Emulation  Content type: News

dod hash-trie - gardenweb

 🗂️Data Structures

The best-selling all-rounder GEEKOM A6 mini PC is now 20% off and cheaper than Prime Day

 🔌ESP32
neowin.net·

Issue #390 - The ML Engineer 🤖

 🏗️System Design  Content type: News  Content type: Blog

AMD Zen 6 Leak: Next-Gen Ryzen Processors Tipped To Clear 6.5GHz Barrier

 ⚙️CPU Microarchitecture  Content type: News
hothardware.com·

GEEKOM A6 AMD Ryzen 7 6800H Mini PC is now off by 20% for a limited time (Sponsored) - CNX Software

 🔌ESP32  Content type: News
cnx-software.com·

Gigabyte RTX 5060 Laptop Drops To $999, Lenovo Legion Tab Gen 3 Hits $387

 ⚙️Performance Profiling  Content type: News
hothardware.com·

ASTRA-sim 3.0: Next-Level Distributed Machine Learning Simulations via High-Fidelity GPU and Infrastructure Modeling

 🗄️Database Sharding  Content type: Academic
arxiv.org·

Release 0.17.6: Merge pull request #3782 from tigerbeetle/release-2026-06-05 · tigerbeetle/tigerbeetle

 🪨RocksDB  Content type: Code
github.com·

bigattichouse/packed-twin-inference: PTI achieves ~2× throughput using a single quantized model (Q5_K_M or better) by running 4 generation streams in one batched decode call. The GPU loads model weights once per step and produces 4 predictions simultaneously. KV cache overhead is ~0.8 GiB total for all 4 streams. No draft model. No quality loss

 🏗Computer Architecture  Content type: Code
github.com··r/LocalLLaMA

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