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Bringing Data Transformations Near-Memory for Low-Latency Analytics in HTAP Environments
arxiv.org·23h
🏹Apache Arrow
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Pushing the Packed SIMD Extension Over the Line: An Update on the Progress of Key RISC-V Extension
semiwiki.com·1d
SIMD
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ANN v3: 200ms p99 query latency over 100 billion vectors
turbopuffer.com·1d·
Discuss: Hacker News
🔮Prefetching
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SHADOW: Simultaneous Multi-Threading Architecture with Asymmetric Threads
danglingpointers.substack.com·1d·
Discuss: Substack
Glommio
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GPU-Resident Inverted File Index for Streaming Vector Databases
arxiv.org·23h
🗂️Vector Indexes
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ClickPy at 2 Trillion rows: Scaling ingestion and fixing the past
clickhouse.com·17h
ClickHouse
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Streamlining CUB with a Single-Call API
developer.nvidia.com·6h
🏟️Arena Allocators
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Python Code Optimization Tips
denvaar.dev·1d
SIMD Optimization
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Using Local LLMs to Discover High-Performance Algorithms
towardsdatascience.com·2d
🏗️LLM Infrastructure
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understanding LSM trees via read, write, and space amplification
bitsxpages.com·5h
🌲LSM-Trees
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TigerBeetle vs PostgreSQL Performance: Benchmark Setup, Local Tests
softwaremill.com·1d
📊Database Benchmarking
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Arctic Wolf’s Liquid Clustering Architecture Tuned for Petabyte Scale
databricks.com·10h
ClickHouse
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CUDA Programming: From Zero to GPU Kernels
pythongiant.github.io·17h·
Discuss: Hacker News
Hardware Acceleration
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Retrieve and Rerank: Personalized Search Without Leaving Postgres
paradedb.com·1d
👤Search Personalization
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Co-optimization Approaches For Reliable and Efficient AI Acceleration (Peking University et al.)
semiengineering.com·10h
Hardware Acceleration
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CPU-bound Insert Benchmark vs MySQL on 24-core and 32-core servers
smalldatum.blogspot.com·1d·
📊Database Benchmarking
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Gated DeltaNet: The “Surgical Eraser” Solving Linear Attention’s Memory Problem
pub.towardsai.net·23h
🧠LLM Inference
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Cache derive proc macro expansion with incremental query by Kobzol · Pull Request #145354
github.com·2d·
Discuss: r/rust
Rust Macros
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AI Systems Performance Engineering
github.com·3h·
Discuss: Hacker News
📅Resource Scheduling
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Field Notes on Scaling MoE Expert Parallelism with DeepEP
nousresearch.com·1d·
Discuss: Lobsters
🏗️LLM Infrastructure
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