Software-Defined
Stochastic Inference Engine

Entropy-governed dynamic precision routing and speculative verification for energy-constrained large language model inference on modern datacenter and edge accelerators.

Energy Expenditure
-46.7%

Per-token energy reduced from 6.40 J down to 3.41 J via speculative scouting.

Memory Bus Traffic
-71.9%

Memory bandwidth cut per projection layer via custom Triton INT4 GEMM kernel.

Code Compressibility
94.7%

Sub-byte High-Gear duty cycle achieved on structured code and reasoning tokens.

Kernel Latency
74.2 µs

Zero-stall on-chip SRAM dequantization on Blackwell Tensor Cores.

System Architecture

The Hardware-Aware Adaptive Runtime

Decoupling wall-clock execution time from deterministic silicon precision without paying the software emulation tax.

1

Shannon Entropy Routing

Calculates instantaneous logit uncertainty in real time (Ht = −∑ pi log2 pi). Routine syntax and predictable tokens are routed to sub-byte execution, reserving full FP16 precision for complex reasoning transitions.

Ht < θlow → Shift to INT4 High Gear
2

Schmitt-Trigger Clutch

Prevents pipeline thrashing and "gear hunting" across sentence boundaries via a dual-threshold deadband (θlow, θhigh, h) and smoothed moving entropy window (W = 3).

Hysteresis deadband prevents stalls
3

Speculative Verification

Pairs ultra-lightweight draft scouts (1B / INT4) with target verifiers (8B–70B) in a unified VRAM pool. Achieves 50.4%+ draft acceptance, validating multi-token blocks in a single memory fetch.

1-Pass parallel multi-token validation

Macro-Thermodynamics

Datacenter Scale & OpEx Calculator

Estimate enterprise power grid relief, carbon reductions, and annual cost savings using verified SDSIE metrics.

GPU Cluster Size: 512 GPUs
Daily Query Volume: 5,000,000 tokens/day
Electricity Cost ($ / kWh): $0.12 / kWh

Annual Projected Impact

Energy Saved:
1,824 MWh / yr
Annual OpEx Reduction:
$218,880 / yr
CO2 Emissions Avoided:
474 Metric Tons CO2e

Academic Citation

Cite SDSIE in Your Research

Permanent DOI minted via CERN / Zenodo repository.

@software{jacklin2026sdsie,
  author       = {Zanno Jacklin},
  title        = {{SDSIE: Entropy-Governed Dynamic Precision and Speculative 
                   Verification for Energy-Constrained Inference on Modern Accelerators}},
  month        = aug,
  year         = 2026,
  publisher    = {Zenodo},
  version      = {v1.1.0},
  doi          = {10.5281/zenodo.21499379},
  url          = {https://doi.org/10.5281/zenodo.21499379}
}