Gonka Optimizer

{
  "result": " Ship a Paged Two-Stage KV Ring-Buffer with per-head FP8 (E4M3) quantization as the production memory manager for 24 GB nodes. This system partitions the KV working set into 256-token pages in HBM, spills cold pages to a pinned host-memory ring buffer via asynchronous PCIe copy, and compresses the cache to halve its footprint. Hard-cap HBM reservation at 19.2 GB—80 % of 24 GB—leaving non-negotiable headroom for weights and activations. With page-table refcounting and two-stage prefetch (host → HBM), 64 k context sequences become deterministic and OOM-free on standard datacenter and consumer cards.\n\nImplementation is a medium-complexity kernel-and-scheduler refactor, not a drop-in swap. Prerequisites are Ada/Hopper-generation FP8 tensor cores, a pinned host-memory overflow pool, and explicit PCIe copy-engine orchestration to avoid CUDA stream bubbles. The scheduler must simultaneously land chunked-prefill (dynamic 512–2048 token chunks capped at 20 ms GPU time) to bound incoming latency and interleave decode micro-batches without head-of-line blocking. Wrap decode kernels in CUDA graphs to burn down CPU launch overhead and consistently hit the sub-100 ms step SLA. Integration touches the memory manager, batch scheduler, and validator instrumentation—budget two sprints.\n\nThe recommended configuration is derived from first-principles memory-geometry analysis and existing FP8 KV-cache compression literature, not yet from Gonka-specific benchmarks. The 80 % HBM envelope, 256-token page granularity, and 64 k worst-case occupancy model are theoretically sound, but the deterministic footprint must be validated in-situ before mainnet activation. Likewise, the sub-100 ms generation claim under chunked-prefill rests on kernel execution models rather than continuous-batching production traces. Treat this as a high-conviction engineering specification awaiting empirical burn-in; do not commit economic slashing logic until live variance data is collected.\n\nFour blockers must be empirically resolved before the economic spec unfreezes: (1) accuracy impact of per-head FP8 KV quantization on long-context retrieval, (2) host-memory bandwidth saturation under prefetch during bursty 64 k prefill waves, (3) divergence between deterministic memory oracles and real HBM pressure histograms from 24 GB and 48 GB shadow traffic, and (4) whether the 20 ms prefill chunk cap holds sub-100 ms decode latency under empirical arrival distributions. Next tick, the swarm will run a controlled benchmark of the paged ring-buffer under synthetic 64 k load, followed by canary deployment of shadow oracles to generate the validated variance surface required for the Nucleolus pricing and slashing LUT.",
  "items_processed": 200,
  "findings": 1,
  "hypotheses": 6
}