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Performance Hints for BigQuery
trmlabs.com·6h·
Discuss: Hacker News
📈Query Optimization
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[Discussion] The "Noise" Bottleneck in Local 8B RAG – A comparison of cleaning strategies (Regex vs. Unstructured vs. Entropy)
reddit.com·7h·
Discuss: r/LocalLLaMA
🧪Parser Testing
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EROFS Boosts Container Efficiency with Page Cache Sharing, Cutting Memory by 40-60%
webpronews.com·9h
⚡Cache Optimization
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Training a Model on Multiple GPUs with Data Parallelism
machinelearningmastery.com·1d
🔀SIMD Programming
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Virtualization: Theory to Silicon
pooladkhay.com·12h·
Discuss: Hacker News
🖥️Minimal VMs
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What I Learned Building a Storage Engine That Outperforms RocksDB
tidesdb.com·3h·
Discuss: Hacker News, r/programming
🔗Memory Linearization
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Utilizing OS-recommended caching in go to store files on disk
dev.to·20h·
Discuss: DEV
🐹Go Internals
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Department of Computer Science and Technology – Technical reports: UCAM-CL-TR-949
cl.cam.ac.uk·4h·
Discuss: Hacker News
🏰Capability Machines
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Why is calling my asm function from Rust slower than calling it from C?
ohadravid.github.io·11h·
Discuss: Lobsters, Hacker News
📜Bytecode Interpreters
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[News] Micron Reveals Three Culprits Behind Memory Crunch—and Why It Won’t Ease Soon
trendforce.com·1d·
Discuss: r/hardware
🔮Speculative Execution
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The answer is in your heap: debugging a big memory increase in Ruby on Rails
island94.org·1d
📊Memory Profilers
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The Garbage Collection Handbook
gchandbook.org·5d
🗑️Garbage Collection
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What Deep Learning Theory Teaches Us About AI Memory
dev.to·1d·
Discuss: DEV
🗺️Region Inference
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Is the future of hardware just optimization?
reddit.com·12h·
Discuss: r/hardware
⚡Performance
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Think Your Python Code Is Slow? Stop Guessing and Start Measuring
towardsdatascience.com·1d
📈Performance Tools
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Dual-cache Ryzen 9 9950X3D2 shows up in benchmark with bigger L3 cache
neowin.net·11h
💾Cache Algorithms
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Linux perf Examples
brendangregg.com·17h
📊perf Tools
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Solved: The Ultimate WordPress Pagespeed Guide
wp.me·7h·
Discuss: DEV
🚀V8 Internals
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Small files are ruining your SSD
xda-developers.com·6h
🔗Weak References
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Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems: Kleppmann, Martin: 9781449373320: Amazon.com: Books
amazon.com·22h
💬Smalltalk VMs
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