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memory-bandwidth

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Intent-aware KV execution prototype for agentic long-context inference: semantic block selection, dynamic scoring, KV quantization modeling, speculative prefetch simulation, CPU references, and future Triton/CUDA kernels.

  • Updated May 29, 2026
  • Python

Measures actual GPU costs for LLM prefill and decode on RTX 2070 (8GB) to validate simulation parameters. Key findings: prefill converges to 30-70 us/token at long sequences; decode is memory-bandwidth-bound (constant with prefix length, 5300-10800 us/token single-request); simulation defaults are correct for server-level amortized batching.

  • Updated Jul 10, 2026
  • Python

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