Myths Programmers Believe about CPU Caches
software.rajivprab.com·1d·
Discuss: Hacker News
🧠Memory Models
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The Hidden Cost of Bad Caching: Why More Cache Isn't Always Better
dev.to·18h·
Discuss: DEV
⚡Cache-Aware Algorithms
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A hitchhiker's guide to CUDA programming
seanzhang.me·1d·
Discuss: Hacker News
🔀SIMD Programming
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Fungus: The Befunge CPU(2015)
bedroomlan.org·1h·
Discuss: Hacker News
🌳B+ Trees
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Accelerating AI inferencing with external KV Cache on Managed Lustre
cloud.google.com·10h
⚡Cache-Aware Algorithms
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Utilizing Chiplet-Locality For Efficient Memory Mapping In MCM GPUs (ETRI, Sungkyunkwan Univ.)
semiengineering.com·1d
🗺️Memory Mapping
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Strix Halo's Memory Subsystem: Tackling iGPU Challenges
chipsandcheese.com·4h·
Discuss: Hacker News
🧠Memory Hierarchy
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Well-Typed.Com: Case Study: Debugging a Haskell space leak
well-typed.com·1d
📚Stack Allocation
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Kioshun - in-memory cache now with optional, embedded, mesh cluster.
reddit.com·1d·
Discuss: r/golang
💾Caching Compilers
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🚀 Go Faster: Cutting the Slack in GC with Smart Memory Allocation
dev.to·2d·
Discuss: DEV
🧠Memory Allocators
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Don't give Postgres too much memory
vondra.me·13h·
Discuss: Hacker News
🧠Memory Models
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Challenging the Fastest OSS Workflow Engine
obeli.sk·18h·
Discuss: Lobsters, Hacker News
📡Erlang BEAM
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Opportunistically Parallel Lambda Calculus
dl.acm.org·1d·
Discuss: Hacker News
🌱Minimal Languages
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How We Saved 70% of CPU and 60% of Memory in Refinery’s Go Code, No Rust Required.
honeycomb.io·1d·
Discuss: Hacker News, r/programming
📚Stack Data Structures
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No Cap, This Memory Slaps: Breaking Through the OLTP Memory Wall
danglingpointers.substack.com·1d·
Discuss: Substack
🧠Memory Models
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Memoization, a useful pattern for quick optimization
event-driven.io·3d
🔗Weak References
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Why vLLM is the best choice for AI inference today
developers.redhat.com·1d
📡Erlang BEAM
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ReLook: Vision-Grounded RL with a Multimodal LLM Critic for Agentic Web Coding
paperium.net·1h·
Discuss: DEV
💬Interactive REPLs
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2025 Holiday Readiness Checklist (Page Speed Edition!)
speedcurve.com·2h
📈Performance Tools
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Designing Data-Intensive Applications — Chapter 1: Reliable, Scalable, and Maintainable Applications
techblog.netflix.com·2d·
Discuss: DEV
🗄️Database Engines
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