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🧮 Compute Optimization

Instruction Selection, Compiler Transformations, SIMD, Parallelization

Build a Compiler from Scratch, Part0: Introduction
blog.sylver.dev·14h
⚙️Language Runtimes
Overtuning in Hyperparameter Optimization
arxiv.org·10h
📊Vector Databases
Scaling Pinterest ML Infrastructure with Ray: From Training to End-to-End ML Pipelines
medium.com·21h·
Discuss: Hacker News
🕯️Candle
Flynn Was Right: How a 2003 Warning Foretold Today’s Architectural Pivot
semiwiki.com·21h
⚡Hardware Acceleration
How I use Claude Code
jonatkinson.co.uk·4h
🪄Prompt Engineering
How to use Gemini 2.5 to fine-tune video outputs on Vertex AI
cloud.google.com·22h
📊Feed Optimization
0.5 tok/s with R1 Q4 on EPYC 7C13 with 1TB of RAM, BIOS settings to blame?
i.redd.it·17h·
Discuss: r/LocalLLaMA
🖥️Hardware Architecture
What does 10x-ing effective compute get you?
lesswrong.com·19h
🏆LLM Benchmarking
The one-more-re-nightmare compiler (2021)
applied-langua.ge·21h·
Discuss: Lobsters, r/programming
🔍RegEx Engines
Threaded Code
muforth.dev·3h·
Discuss: Hacker News
🪄Prompt Engineering
Plan for Speed -- Dilated Scheduling for Masked Diffusion Language Models
arxiv.org·10h
🧠LLM Inference
Greedy Is Good. Less Greedy May Be Better
gojiberries.io·13h·
Discuss: Hacker News
🏆LLM Benchmarking
The 20+ most common AI terms explained, simply
threadreaderapp.com·22h
🧠LLM Inference
Black-Box Test Code Fault Localization Driven by Large Language Models and Execution Estimation
arxiv.org·10h
🕯️Candle
Polaris: A Post-training recipe for scaling RL on Advanced ReasonIng models
github.com·17h·
Discuss: r/LocalLLaMA
🗜️Zstd
The Week I Spent Hand-Coding Neural Networks to Finally Understand Backpropagation
pub.towardsai.net·21h
🔢BitNet
HW Security: Multi-Agent AI Assistant Leveraging LLMs To Automate Key Stages of SoC Security Verification (U. of Florida)
semiengineering.com·7h
🕳LLM Vulnerabilities
The Internal Inconsistency of Large Language Models
blog.kortlepel.com·21h·
Discuss: Hacker News
🪄Prompt Engineering
AMD researchers reduce graphics card VRAM capacity of 3D-rendered trees from 38GB to just 52 KB with work graphs and mesh nodes — shifting CPU work to the GPU y...
tomshardware.com·3h
🖥GPUs
NaviAgent: Bilevel Planning on Tool Dependency Graphs for Function Calling
arxiv.org·10h
🛠️Build Optimization
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