LEGaTO project goals: − Order of magnitude energy-efficiency on heterogeneous hardware through energy optimized programming models and runtimes − 5x decrease in MTTF through energy-efficient software-based fault tolerance. − 5x increase in FPGA designer productivity using hardware dataflow languages

1. The LEGaTO project has received funding from the European Union's Horizon 2020 research and innovation
programme under the grant agreement No 780681
11/7/19
XiTAO: an Energy -
Efficient Runtime for
the LEGaTO Tool Chain
Act!Sustainable, 07/11/2019
Lindholmen Science Park, Gothenburg, Sweden
Mustafa Abduljabbar, Ph.D.
Computer Science and Engineering
CHALMERS University of Technology

2. 07/11/19 2
LEGaTO Goals, Use Cases and Approach
Act!Sustainable, Gothenburg
•
Project Goals
− Order of magnitude energy-efficiency on heterogeneous hardware through energy
optimized programming models and runtimes
− 5x decrease in MTTF through energy-efficient software-based fault tolerance.
− 5x increase in FPGA designer productivity using hardware dataflow languages
•
Use Cases
− Healthcare: also increase in resilience and security
− IoT for smart cities.
− Machine Learning: by employing accelerators and runtime accuracy tuning.
•
Approach: Made-In Europe software stack → task-based programming model → Cutting
edge European hardware and FPGA-based Dataflow Engines (DFE).

3. 07/11/19 3
XiTAO (developed at CHALMERS)
Act!Sustainable, Gothenburg
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Reduces Overheads
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Reduces Parallel Slackness
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Destructive Interference
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Fine-grained parallelism
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Overheads
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Work-time Inflation
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Improves Parallel Slackness
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Bulk creation of parallelism
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Interference-freedom
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Constructive sharing

4. 07/11/19 4
XiTAO – Energy-Efficient Scheduling
Act!Sustainable, Gothenburg
WSQ PTT*Power WSQ PTT*Power WSQ PTT*Power WSQ PTT*Power
MAX&MAX MAX&MIN MIN&MAX MIN&MIN
0
20
40
60
80
100
120
140
160
180
200
Matrix Multiplication - Dynamic Energy
Parallelism=2 Parallelism=6 Parallelism=10
Energy[J]
WSQ PTT*Power WSQ PTT*Power WSQ PTT*Power WSQ PTT*Power
MAX&MAX MAX&MIN MIN&MAX MIN&MIN
0
50
100
150
200
250
300
350
Copy - Dynamic Energy
Parallelism=2 Parallelism=6 Parallelism=10
Energy[J]
Up to 90%
Energy
Savings, with
adaptive
energy aware
scheduling,
based on
modeled and
real time
feedback