A field team faces an unresolved physical question: What does INT8 spend to make an NPU efficient? They must answer it before changing npu arithmetic bit depth on the real device. Predict the direction first.
See the relationship before changing it
The figure reads from left to right. The blue card is npu arithmetic bit depth. The middle card applies this page's relationship. The green card is quantisation step. Walk the arrows once: set the input, apply the rule, then read the result with its unit.
The retained audit below checks several chapter fixtures. This added model holds every other chapter fixture fixed, so the numeric fixture does not switch without explanation.
Derive the baseline in four named moves
- 1
Name the input. The chapter baseline for npu arithmetic bit depth is 8.
- 2
Name the relationship. q=range/2^N; qrms=q/√12; SNR=6.02N+1.76; fevent≤finfer/2
- 3
Substitute the chapter fixture. Set npu arithmetic bit depth to 8. The page ledger gives quantisation step as 0.008.
- 4
Read the result. Keep the stated output unit beside the value. Use it only inside the technical boundary on this page.
Predict, then change npu arithmetic bit depth
Try Predict the direction of quantisation step. Move one control, calculate, then check your prediction.
Observe The control changes how values are represented inside the accelerator. Only a scheduler or latency change can move the physical decision cadence. Reset the control to 8 and compare quantisation step.
Explain Only npu arithmetic bit depth moves here. The other chapter fixtures remain fixed.
Check yourself
What should you do before trusting a moved-control result?
What does this small model leave out?
1. One array, two limits
Fewer bits let hardware pack more multiply-accumulate units into an area and move less data. That efficiency widens each numeric step. A separate inference cadence decides how often the physical system gets a new decision.
2. Name each move
Count levels2^N levels span the normalized range.
Divide the rangeq = 2/2^N.
Convert step to RMSqrms = q/√12.
Estimate the ideal ceilingSNR = 6.02N + 1.76 dB.
Halve the decision rateA 10 Hz cadence has a 5 Hz Nyquist boundary.
3. Work INT8 and INT16
INT16 gives 65,536 levels and an ideal 98.1 dB ceiling, 48.2 dB above INT8. Neither result changes the chapter's 10 inferences/s cadence or its 5 Hz event boundary.
4. Try one controlled change
TryMove only the arithmetic bit depth. The normalized range and 10-inference/s physical decision schedule stay fixed.
ObserveAt 8 bits the ideal ceiling is 49.9 dB and the RMS floor is 0.002255. Raising precision improves those numbers, while the 10 Hz cadence, 100 ms period, and 5 Hz event boundary remain fixed.
ExplainThe control changes how values are represented inside the accelerator. Only a scheduler or latency change can move the physical decision cadence.
The precision calculation is an ideal full-range uniform quantiser.
- Distribution
- Real weights and activations may not use the full range uniformly
- Network
- Clipping and rounding accumulate across operations and layers
- Timing
- Event bandwidth is not always a sinusoid and latency includes the whole pipeline
Benchmark the final artifact, operators, preprocessing, memory traffic, scheduler, and event set on the target.
5. Interpret the 48.2 dB gap
It is an ideal representation-margin difference, not a predicted accuracy drop. A well-calibrated INT8 model can preserve the task while a poorly ranged INT16 model can still clip or fail elsewhere.
6. Record the complete accelerator claim
Keep bit depth, scale policy, calibration set, operator support, accuracy delta, tensor memory, inference latency, cadence, energy per decision, thermal state, and fallback together.
7. Check yourself
Why does INT8 have 256 levels over [−1,1] here?
Does 49.9 dB predict the model's accuracy?
Can a faster MAC array alone move the 5 Hz event boundary?
This bridge explains the chapter's first-order hardware trade without claiming NPU or model completeness.
- 2.0 range
- Normalized teaching interval
- 49.9 dB
- Ideal INT8 ceiling
- 5 Hz
- Ideal boundary at 10 decisions/s
Go deeper in the chapter and validate the complete runtime on representative events.
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