Module tensor Future

Tensor Module - Future Enhancements

Scope

• hardening and refinement of tensor runtime behavior
• deterministic reliability improvements for index/bridge/fingerprint paths
• stronger benchmark-backed guardrails for tensor hot paths

Design Constraints

• tensor contracts remain backward compatible within major release line.
• index and bridge outcomes remain explicit and deterministic.
• degraded fingerprint and replay-adjacent paths remain observable.
• advanced structural behavior remains bounded and diagnosable.

Required Interfaces

Interface	Requirement
index interfaces	deterministic tensor index lifecycle behavior
bridge interfaces	explicit ingestion/core/mmap bridge contracts
graph interfaces	stable fingerprint insert/query/export semantics
structural interfaces	bounded helper/transformation behavior

Implementation Notes

• tighten parity between index routing and bridge diagnostics.
• standardize incident taxonomy for fingerprint and replay-adjacent classes.
• expand resilience tests for prolonged concurrent tensor graph workloads.
• broaden benchmark depth for tensor graph and dedup scenarios.

Test Strategy

• unit and integration suites for tensor index, bridge, and fingerprint paths.
• regressions for export/replay edge scenarios and bridge fault conditions.
• deterministic stress runs for concurrent tensor graph access patterns.
• release-profile benchmark runs for mapped tensor targets.

Performance Targets

• TensorFingerprintGraph key-based similarity (findSimilar) with 10k candidate adapters: p95 <= 80 ms, p99 <= 140 ms on release profile (windows-release), exact TT cosine path.
• TensorFingerprintGraph fingerprint path (findSimilarByFingerprint) with 10k candidates and median fingerprint width <= 128: p95 <= 15 ms, p99 <= 30 ms.
• AdapterRepository overwrite path (store on existing key) must avoid O(N) metadata updates; steady-state overhead target <= 5% versus insert path at equal payload size.
• Graph/read-heavy mixed workload (90% query, 10% store/remove) should sustain >= 2,000 ops/s per process on reference CI hardware without unbounded memory growth.
• Benchmark manifests for tensor graph and adapter repository must include at least: 1k/10k/50k candidate scales, single-tenant and 10-tenant split, and warm/cold-cache runs.

Security / Reliability

• maintain strict bounded behavior for index and bridge transitions.
• preserve explicit failure signaling for fingerprint and replay-adjacent faults.
• enforce predictable degradation under concurrent tensor graph load.
• keep diagnostics actionable for production tensor incidents.

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