Latest Blog
What Is Speculative Decoding Acceptance Rate, and Why Does It Matter?
Decode the acceptance metric, draft verification, rejection behavior, speedup limits, workload variation, and measurement for local inference.
What Is Prefill-Decode Disaggregation, and Why Does It Change LLM Serving?
Decode phase separation, KV transfer, independent scaling, interference control, latency objectives, and limits for local LLM serving.
What Is Continuous Batching, and When Does It Matter for a Home AI Server?
Decode continuous batching, its difference from static and dynamic batches, KV scheduling, latency tradeoffs, and home-server break-even conditions.
How Does PCIe Peer-to-Peer Transfer Affect Multi-GPU Local Inference?
Follow GPU tensor movement through direct peer access, host staging, PCIe topology, synchronization, and fallback in local multi-GPU inference.
How Does NVMe Queue Depth Affect Vector Index Ingest Speed?
Trace index writes, outstanding commands, flash parallelism, batching, fsync, latency, and saturation through a vector ingest pipeline.
How Does a RAID Scrub Interact With Local Inference Latency?
See how scrub reads and repairs compete with model loading, RAG retrieval, logging, and memory pressure across a home AI server.
How Does UPS Signaling Coordinate a Safe AI Server Shutdown?
Trace UPS state, shutdown policy, service ordering, storage commits, host power-off, and load removal through a safe home AI shutdown.
How Does Time-Series Downsampling Affect Smart Home Anomaly Detection?
See how bucket width, aggregation, anti-aliasing, missing data, event duration, and multiscale retention change smart home anomaly recall.
