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Exploiting Partially Reconfigurable FPGAs for Situation-Based Reconfiguration in Wireless Sensor Networks
Rafael Garcia, Dr. Ann Gordon-Ross, Dr. Alan George
Target Tracking• Overview & Potential of Kalman Filter
Estimate state of dynamic system (moving target in this case) in a noisy environment
Commonly used in target tracking, extendable for multiple targets, models, and dimensions
Assume white Gaussian sensor noise
Working w/ frames from USB Camera
CPU-FPGATransfer image
array(1)
FPGA-CPU Send X, Y, Width,
Height to CPU(2)
CPUUpdate frame
RemoveBackground
(2)
Erosion1
(1)
Erosion2
(2)
Label
(1)
GroupProperties
(2)
Sort
(1)
CPUCapture frame
FPGA Process image
• FPGA-Amenable Features Low memory/bandwidth requirements Simple filter with streaming inputs & outputs Requires only multiplication & addition, can
be implemented using only logic & MACs Filter receives/produces a stream of
coordinates, not images
VAPRES-based processing nodes
Intelligent Sensor Nodes
• Environment Adaptation Monitored by a process running inside the
controlling agent (Microblaze) Tracking filters loaded or unloaded
dynamically during run-time in response to: Number of targets inside tracking area Power available at VAPRES-based node Priority scheduling for critical targets
• Computation/Power Migration Hardware modules can migrate between
VAPRES based processing nodes Offload processing if a node runs out of
processing/power resources Migration supported by Microblaze network
interface
SCORES
Interface Interface Interface Interface Interface
Empty slot Empty slot Empty slot Empty slot Empty slot
Switch 1
Target 1 Target 2 Target 3 Target 4 Target 5
Switch 2 Switch 3 Switch 4 Switch 5
Interface Interface Interface Interface Interface
Sensor Interface
PR
R 1
Target controller
Multiple targets
Microblaze
PR
R 2
PR
R 3
PR
R 4
PR
R 5
DisplayController
Kalman filter v2
Kalman filter v1
Filtered coordinatesFSL Links
NetworkInterface
SensorNetwork
SensorNetwork
FlashController
ICAP Flash Memory(stores Kalman filter
partial bitstreams)
• Top Level Specifications VAPRES - Virtual Architecture for Partially
Reconfigurable Embedded Systems Microblaze-based reconfigurable embedded
system leveraging partial reconfiguration Highly parametric architecture: e.g. number
of partially reconfigurable regions (PRRs), FSL FIFOs depth, network-on-chip (SCORES) parameters
Two streaming communication backbones:o Microblaze-to-coprocessors through asynchronous FSL
(fast streaming links)o Intra-coprocessor communication through light-weight
custom network-on-chip (SCORES)
• Reconfigurable module features Partial reconfigurable coprocessors
can span multiple regions (PRRs) Each PRR is independently clocked
o Each coprocessor can run at an independent
clock frequencyo Clock frequency is managed by a controlling agent
(Microblaze)
• Reconfiguration Drivers Target behavior Target criticality Quality of sensor readings Available resources/power
Situation-Based Reconfiguration Policies
CharacteristicsSensor type
Target Type High Power
High Bandwidth
Precision Size Kernel Type
Low power Slow targets Fixed Point Small Kalman FilterFast sampling Fast targets Fixed Point Small Kalman FilterMulti-scale Airborne targets Floating
PointLarge Multiscale Kalman
SmootherHigh-Noise Filtering Noisy or generic
targetsFloating
PointMedium Kalman Filter
Feature selective Multiple targets Floating Point
Large Feature Extraction/Selection
Kalman Filter Taxonomy
Working w/ JPEG image
• Testbed Implementation CPU simulates the the sensor and the display