Empirical Validation & Telemetry

Technical Evidence & Hardware Validation.

Explore measured workloads, implementation results and evaluation evidence for the NeuroCore architecture.

Evidence Classification Taxonomy:

[MEASURED HARDWARE RESULT]Directly recorded telemetry on FPGA evaluation hardware.

[IMPLEMENTATION-FLOW VALIDATION]Verified RTL synthesis and place-and-route flow.

[EXTERNAL HARDWARE EVALUATION]Verified evaluation with external partner engineering teams.

MEASURED HARDWARE RESULT

Real-Time On-Chip Adaptation

Sensory Pattern Perturbation & Error Minimization

142 µs (0.142 ms)

Key Measured Metric

Platform

Single NeuroCore tile implemented on Xilinx Artix-7 / Zynq-7000 FPGA

Execution Mode

Single-core hardware evaluation running standalone firmware

Thermal & Power

30°C–50°C passive thermal profile (near-zero idle clock dissipation)

Measurement Method

Direct serial telemetry timestamp recording via UART COM port

Measured Finding: Pre-adaptation error rate of 99% reduced to 0% in 142 microseconds upon onset of localized error signal.

Evaluation Boundary & Limitations: Measured on FPGA emulation hardware; physical ASIC silicon will achieve significantly lower latency and power depending on process node and PDK selection.

MEASURED HARDWARE RESULT

Sequential Lifelong Task Retention

50 Sequential Benchmark Classification Tasks

Instantaneous task transition

Key Measured Metric

Platform

Single NeuroCore tile implemented on Xilinx FPGA evaluation platform

Execution Mode

Continuous sequential task switching without global model re-initialization

Thermal & Power

Ambient passive air cooling

Measurement Method

End-to-end task accuracy evaluation across all 50 sequential datasets

Measured Finding: Task 1 accuracy sustained with <0.8% degradation after learning 50 consecutive tasks, overcoming catastrophic forgetting in continuous learning.

Evaluation Boundary & Limitations: Demonstrated on standardized synthetic and acoustic temporal benchmark sequences.

MEASURED HARDWARE RESULT

Zero-Shot Cross-Modal Transfer

Acoustic Audio to RF Pulse Strobe Domain Transfer

0.0 ms (Zero adaptation latency required)

Key Measured Metric

Platform

Single NeuroCore tile implemented on Xilinx FPGA evaluation platform

Execution Mode

Direct sensory swap execution without gradient updates in target domain

Thermal & Power

Identical to baseline active inference

Measurement Method

Pre-trained acoustic weights evaluated against synthetic RF radar pulse train inputs

Measured Finding: Achieved 96.5% immediate classification accuracy in RF pulse domain using weights learned exclusively in the acoustic domain.

Evaluation Boundary & Limitations: Relies on structural isomorphism between source and target temporal signal domains.

IMPLEMENTATION-FLOW VALIDATION

Standard-Cell Physical Flow Synthesis

Full-chip synthesis, placement, and timing closure flow

Nominal clock frequency targeted up to 1.2 GHz (7nm FinFET target)

Key Measured Metric

Platform

Commercial EDA tool flow across 7nm FinFET, 16/28nm, and 45nm CMOS PDKs

Execution Mode

Multi-corner timing analysis (PVT corners)

Thermal & Power

Standard-cell dynamic and leakage power extraction

Measurement Method

Synopsys / Cadence EDA implementation flow scripts with SDC constraints

Measured Finding: Verified die area metrics: 0.60 mm² at 7nm FinFET, 0.85 mm² at 16/28nm, and 1.32 mm² at 45nm CMOS.

Evaluation Boundary & Limitations: Represents verified RTL-to-GDSII physical implementation flow validation, not manufactured or packaged ASIC silicon.

External Hardware Evaluation Evidence

Hardware Evaluation with Bharat Electronics Limited (BEL)

NeuroCore underwent an external hardware evaluation with Bharat Electronics Limited. The evaluation included FPGA programming, inference execution, status monitoring and reference-output verification.

Stage 1

FPGA Programming

Bitstream loading & hardware initialization on target evaluation carrier.

Stage 2

Inference Execution

Active execution of representative signal filtering and temporal patterns.

Stage 3

Status Monitoring

Telemetry verification across hardware interfaces and event queues.

Stage 4

Reference Verification

Output comparison against golden architectural reference simulation vectors.

* Scope notice: The external evaluation established functional execution on FPGA hardware; it does not constitute certification or production deployment endorsement.

Visual Hardware Metrics

Interactive Hardware Quantification

Toggle between evaluated metrics to explore hardware latency, memory retention, cross-modal transfer, and thermal telemetry.

Benchmark 1 • Hardware Quantification

142 µs Real-Time Hardware Adaptation

Hardware e-prop weight updates turn a 99% pre-adaptation error rate into 0% post-adaptation error in 142 microseconds on single-core silicon.

142 µs

Hardware
Measured

NeuroCore Single-Core (On-Chip E-Prop)142 µs (0.142 ms)

Offline Cloud Retraining Loop (Batch Backpropagation)~Hours (Offline Retraining Cycle)

Pre-Adaptation Error

99% Error

➔

Post-Adaptation Error

0% Error

100% Retention

Direct Serial Hardware Logs

PuTTY Terminal Telemetry Console

Select any recorded run below to inspect raw UART telemetry captured during physical FPGA hardware evaluation of the NeuroCore single-core implementation.

COM4 — PuTTY Terminal — NeuroCore Single Core Physical Hardware Run

BENCHMARK 1VERIFIED

On-The-Fly Hardware Learning (E-Prop)JSA LAABS Hardware Engine v1.0

Adaptation Latency

142 µs

Pre-Adapt Error

99%

Post-Adapt Error

10k Retention

100%

Streaming hardware output...

Target Architecture: NeuroCore Single Tile IP CoreSilicon Tested

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Detailed test vectors, FPGA bitstream configuration guides, and simulation harnesses are provided to prospective licensees under an evaluation agreement.

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