AI
Speculative decoding threshold tuning for code generation
Configure speculative decoding acceptance thresholds to optimize code generation throughput and prevent costly inference latency regressions.
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vllm
6 articles
AI
RadixAttention memory layout strategies explained
Diagnose GPU OOM errors and low cache hit rates by comparing contiguous vs paged KV cache layouts for…
AI
Speculative Decoding LLaMA Speedup Measurement
Construct a reproducible benchmarking harness to measure speculative decoding speedup using wall-clock time and valid statistical sampling methods.
AI
KV cache offloading NVMe: vLLM vs TensorRT-LLM
Compare vLLM and TensorRT-LLM KV cache offloading architectures to select the correct system for your latency constraints and…
AI
RadixAttention prefix caching: vLLM latency reduction
Understand how RadixAttention prefix caching in vLLM eliminates redundant prefill computation to significantly reduce time-to-first-token latency.
AI
Agent Pipeline Optimization: 5 GPU Idle Cuts (2026)
Idle agents waste GPU cycles and spike latency. Agent pipeline optimization trims idle time up to 45%, cutting…