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ECE 1161/2161Embedded Computer System Design 2
Computing for Embedded Systems - II
Wei Gao
1
How to Address the Local Resource Constraints? Local resource constraints at embedded systems Limited battery power Limited local computing capacity
Low-power designs Hardware
• Advanced VLSI manufacturing• New computing architecture
Software • DVFS• Duty cycling
May not fundamentally remove the limitation!
ECE 1161/2161 Embedded Computer System Design 2 2
Better Alternatives Cloud computing Offload the local computing workloads to the cloud
Problem: long latency for data transmission• Most embedded systems are delay-sensitive!
ECE 1161/2161 Embedded Computer System Design 2 3
Cloud processing Local processing
Wirelesstransmission
What can we do – Edge Computing
ECE 1161/2161 Embedded Computer System Design 2 4
Computing Storage
DATA CENTERS
END USERS
EDGECLOUD
Embedded Applications of Edge Computing
Cloud Gaming
Virtual Reality
Internet of Things
Smart Cities and Communities5
Challenges Adaptability Optimized performance? Minimized cost?
User mobility Minimized cost?
?Provisioning for the peak load
user mobility
?Complete move of data and program
6
Hierarchical Architecture Adaptability Aggregation of
peak load
User mobility Partial migration
of data and programFlat Edge Cloud
Geo-distributed tree hierarchy 7
Optimal Workload Placement How to minimize the
response latency Where to place a workload How much capacity for a
workload
Challenge Delay tradeoff
ECE 1161/2161 Embedded Computer System Design 2 8
Computation delay
Communication delay
Computation Communication
Response latency
Low tiersHigh tiers
Supporting User Mobility
ECE 1161/2161 Embedded Computer System Design 2 9
A B
Virtual Machine Virtual Machine
BA
programbinarymemorydata
VM Migration
The Big Data Challenge Some embedded systems may be data intensive
ECE 1161/2161 Embedded Computer System Design 2 10
Cloud processing Local processing
Data partitioning
Wirelesstransmission
How to transmit? What to transmit?
What to Transmit? Dynamic data partitioning
ECE 1161/2161 Embedded Computer System Design 2 11
Existing work Assuming stationary and
fixed method transitions
Benefit of remote processing
Computation Cost Transmission Cost
Decisions over Program Methods
Modeling on Method Transitions?
ENERGY EFFICIENCY
Motivation Dynamic behaviors of run-time
program execution Input data User operation
Open-source Android applications Online profiling within source codes
12
Firefox Chess game Barcode scanner
Dynamics of execution paths
Heterogeneity of method execution times
Modeling of Method Transitions
Transitions among program methods: semi-Markov model
Data partitioning approach: a stochastic framework
13
Method execution times
Invocation dependency
System heterogeneity
Order-k
Arbitrary sojourn time distribution
Do We Have More Difficult Scenarios?
Data partitioning Move data-inexpensive computations to the cloud
What if the local computations are both data-intensive and computation-intensive?
ECE 1161/2161 Embedded Computer System Design 2 14
Virtual Reality
Solutions Exploit the redundancy in computations Whether we can reuse the previous computing results
• Within the same user• Across different users
Memoization
ECE 1161/2161 Embedded Computer System Design 2 15
Want to Use Edge Computing? You just need a server!
Existing VM solutions Virtual Box QEMU
Be careful about your programming models
ECE 1161/2161 Embedded Computer System Design 2 16