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COMPARISON OF ADAPTIVE VOLTAGE/FREQUENCY
SCALING AND ASYNCHRONOUS PROCESSOR
ARCHITECTURES FOR NEURAL SPIKE SORTING
May 2013 – EE241 Final Project
Introduction to ‘Spikes’
‘Spikes,’
also called ‘action potentials,’ are
when the electrical potential of a
neuron rises shortly. It is part of the
communication protocol of the brain.
Frequency Range
10-500Hz
Duration
3-5ms
Resolution
8-bit
Spike Sorting Systems
• Operate at constant 37°C
• Extremely low power
• Extremely low area
Purpose Statement
Adaptive Voltage and
Frequency Scaling
vs.
Asynchronous Timing
Determine the conditions
• under which adaptive voltage and frequency scaling provides a better power
performance than asynchronous timing in a neural spike processor.
• under which asynchronous timing provides a better power performance than
adaptive voltage and frequency scaling in a neural spike processor.
Theory
• E = I*VDD*t
• If you can decrease voltage and/or current faster than the increase in delay for an operation, you save
energy.
• Asynchronous circuits process data at the same energy ‘every time.’
• When data rates are low, I and VDD may be reduced such that the energy per spike of a synchronous
solution is lower than the asynchronous solution.
• The issue is that at some point, leakage current dominates, making increased operating time
undesirable.
Verilog Function
• Detection of the largest value in a spike and the point at which it
occurs facilitates spike sorting.
• Sorting spikes on chip results in a reduced amount of transmitted
data.
Synchronous Logic
Prior Art
Asynchronous Logic
Data Collection Methodology
Verilog
Cadence
hSpice
sim
LVS
sim
Synthesis
*RC
E vs. f
Data
sim
.sp netlist
Place and
Route
sim
Logic
Parasitic
extraction
Matlab
Demonstrations of functionality
with synch and asynch.
Determination of max.
frequency and E vs. VDD.
Known Simplifications
• Process Corners
• Entire Verification Space
• Noise/Margins
• Critical Path Monitors
• Adaptive control circuitry
Spice Data: Energy/Op vs. Frequency
Asynchronous:
300 less MOSFETS
>5000 less Rs and
Cs
At 20kHz: Synch: 1.9E-9A – 7.6pJ
Asynch: 1.71E-9A, 6.8pJ
Spice Data:
Current Breakdown - Synchronous
Assumptions
• Process Corners
• Only used TT as effects should be linear on both architectures.
• Verification Space
• Test vector data was designed to be representative, not the worse
case scenario. Testing across a wide range of frequencies and
voltages is an open problem.
• Noise/Margins
• Assumed no noise for this analysis. Noise should hurt both circuits
equally.
Critical Path Monitor
• Subthreshold critical path monitors are highly sensitive to
PVT both globally and locally.
• Current is exponential with changes in
,
, and T.
• Implies a currently unachievable level of specificity.
• First order approximation might be to double energy.
Adaptive Control Circuitry, Clock, + Vdd
•Assuming that the adaptive frequencies are less than the global clock, we can
implement the change in frequency with a clock divider (counter).
•Voltage scaling circuitry would take the global supply and reduce it using one
of many possible techniques.
–Linear Regulators: Inefficient for large changes in voltage.
–Capacitive Regulator: Results in supply ripples.
–Magnetic Regulator: Highest efficiency, but requires external parts
Matlab: Transient State Machine at .5MHz
Matlab: Transient State Machine at .6Mhz
Matlab: Transient State Machine at 5Mhz
Matlab:
Total Energy + Vdd vs. Event Frequency
Conclusion
• Asynchronous logic operates at a higher frequency for all
supply values than the synchronous version. Similarly, for
an equal operating frequencies, asynchronous can
operate at a lower VDD.
• For the speed of a neural processor, both circuits operate
at the lowest supply voltage and leakage current
dominates. There is no means to perform adaptive
analysis.
• In an application where incoming data frequency is on the
order of magnitude of the intrinsic asynchronous circuit
operating frequency, the adaptive circuit requires less
energy, as long as the average voltage required of the
adaptive circuit is less than the intrinsic voltage of the
asynchronous circuit.
References and Acknowledgements
Acknowledgements: Brian Zimmer, Nathan Narevsky,
Jan Rabaey, Stevo Bailey, Tsung-Te Liu, Bora Nikolic
APPENDIX
Spice Data:
Power vs. Max Operating Freq.
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