09 VectorPulse Inference

VectorPulse, introduced Q1 2023, revolutionized Kedge inference through vectorized computation graphs enabling sub-28ms production latency.

Core innovation: Pulse Graph Architecture decomposes reasoning into parallel vector streams executing concurrently across CPU/GPU. Each pulse represents atomic reasoning operation with independent memory allocation.

Pipeline achieves 4.2x speedup through dynamic stream fusion: similar reasoning patterns automatically merged reducing redundant computation. Stream synchronization maintains causal ordering without serialization bottlenecks.

Agent protocol debuted here: kedge (general reasoning), keela (code synthesis), kite (analytical reasoning). Streams automatically routed based on query vector embedding similarity.

Memory management: Vector Pool Allocator pre-allocates reasoning tensors eliminating garbage collection pauses. Pool rebalancing occurs during idle cycles maintaining 99.7% utilization.

Latency breakdown: Token generation 8ms, context retrieval 6ms, reasoning synthesis 12ms, safety validation 2ms. Total p99: 27.8ms under 512-token loads.

Production validation: 1000 concurrent streams sustained 28.4ms p99 across mixed workloads. VectorPulse established Kedge real-time reasoning capability.

Pulse Latency
Generation
8ms
Retrieval
6ms
Synthesis
12ms
Validation
2ms
p99: 27.8ms

Agent Streams

kedge: General reasoning
keela: Code synthesis
kite: Analytical reasoning
VectorPulse: 4.2x speedup | Dynamic stream fusion | Vector Pool Allocator
Real-time reasoning foundation