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A Three-Layer Caching Architecture for Low-Latency LLM Web Search on Commodity CPU Hardware
OreoLook's three-layer Redis caching architecture cuts redundant LLM calls and embedding work for CPU-hosted web-search answer generation.
The paper describes a three-layer caching architecture for OreoLook (formerly lixSearch), an open-source LLM answer engine: a Redis session context window with Huffman-compressed disk overflow, a semantic query cache matching rephrasings via embedding cosine similarity, and a URL embedding cache deduplicating embedding computations. Deployed on a single 8-vCPU Intel Cascade Lake server with 30 Hypercorn workers across three containerized replicas, it achieved an 89.3% aggregate Redis keyspace hit rate, 0.1 ms read latency, and 1.38 MB memory overhead. An LRU eviction daemon migrates idle sessions to disk and rehydrates them for resumption hours or days later.
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OpenArch – PyTorch implementations of modern LLM architectures
OpenArch provides PyTorch reference implementations of modern LLM architectures for developers and researchers.
OpenArch is a GitHub project offering PyTorch implementations of modern large language model architectures. The repository attracted 43 points and 7 comments on Hacker News. It targets developers and researchers who want readable, runnable versions of current LLM architectures.
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Speculative Decoding in vLLM on AMD GPUs
vLLM benchmarks speculative decoding on AMD Instinct MI300X and MI355X GPUs across five drafting methods including EAGLE-3 and native MTP.
The vLLM project documents draft-and-verify speculative decoding support for AMD GPUs via ROCm, comparing native MTP, Gemma 4 MTP, EAGLE-3, DFlash, and DSpark drafting approaches. Output-token throughput effects varied with drafting method, proposal length, model family, draft checkpoint, workload, and acceptance behavior. The post also covers how to enable each method plus practical tuning and observability considerations.
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F5’s multi-cloud networking capabilities simplify operations for distributed application deployments
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Top 5 AI Gateways for Enterprise (2026 Guide)
A 2026 buyer's guide ranks NeuralTrust TrustGate, Kong AI Gateway, and Cloudflare AI Gateway as top enterprise AI gateways for security and governance.
The guide evaluates enterprise AI gateways on security, governance, routing, observability, and agent ecosystem support. NeuralTrust TrustGate ranks first for identity-aware agent governance across models, MCP servers, tools, and agent-to-agent traffic, with SaaS, hybrid, and private deployment options. Kong AI Gateway is recommended for organizations with mature API infrastructure, while Cloudflare AI Gateway emphasizes caching, retries, model fallbacks, and prompt/response guardrails.
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