breakout session 3 stack of adaptive systems (with a view on self-adaptation)

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Breakout Session 3 Stack of adaptive systems (with a view on self- adaptation)

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Page 1: Breakout Session 3 Stack of adaptive systems (with a view on self-adaptation)

Breakout Session 3

Stack of adaptive systems(with a view on self-adaptation)

Page 2: Breakout Session 3 Stack of adaptive systems (with a view on self-adaptation)

Cores

Threads

Algorithm

Data

Autotunertunes

CPU frequency scales up

Cooldown is necessary

Following programms have to

run slower

Influences

Example:

Page 3: Breakout Session 3 Stack of adaptive systems (with a view on self-adaptation)

Layer

Layer

Layer

• Do the different layers interfere and how do they interfere?• How can we measure or classify those interferences

with respect to self-adaption / self-optimization

Page 4: Breakout Session 3 Stack of adaptive systems (with a view on self-adaptation)

SW/APPS/DB

Middleware

Virtual Machine

System Libraries

Hypervisor / OS Scheduler

HW

• CPU-frequency • Tradeoff: performance vs. energy

consumption / thermal

• Number of cores • Tradeoff: cores vs. energy

• Transmodel migration (CPU GPU, FPGA)• Tradeoff: performance vs. adaption

time

Page 5: Breakout Session 3 Stack of adaptive systems (with a view on self-adaptation)

SW/APPS/DB

Middleware

Virtual Machine

System Libraries

Hypervisor / OS Scheduler

HW

• Number of VMs (elasticity management, live migration)• Tradeoff: capacity vs. energy vs. cost

• Scheduling of VMs (priority boosting)• Tradeoff: overhead vs. performance

boost of high priority VMs

Page 6: Breakout Session 3 Stack of adaptive systems (with a view on self-adaptation)

SW/APPS/DB

Middleware

Virtual Machine

System Libraries

Hypervisor / OS Scheduler

HW

• Algorithms (adaptive rendering, sorting)• Tradeoff: response time vs.

accuracy/”quality”

Page 7: Breakout Session 3 Stack of adaptive systems (with a view on self-adaptation)

SW/APPS/DB

Middleware

Virtual Machine

System Libraries

Hypervisor / OS Scheduler

HW

• Number of VMs (elasticity management, live migration)• Tradeoff: capacity vs. energy vs. cost

• Scheduling of VMs (priority boosting)• Tradeoff: adaption time vs. performance

• Thread pool size (autotuner)• Tradeoff: degree of parallelism vs.

memory vs. adaption time

• JIT compiler (recompilation)• Tradeoff: response time vs.

performance

Page 8: Breakout Session 3 Stack of adaptive systems (with a view on self-adaptation)

SW/APPS/DB

Middleware

Virtual Machine

System Libraries

Hypervisor / OS Scheduler

HW

• Platform as a service (AppEng, Azure)• Tradeoff: latency vs. performance

• Inter app msg routing (relay networks)• Tradeoff: latency vs. utilization

Page 9: Breakout Session 3 Stack of adaptive systems (with a view on self-adaptation)

SW/APPS/DB

Middleware

Virtual Machine

System Libraries

Hypervisor / OS Scheduler

HW

• Number of Threads• Tradeoff: degree of parallelism vs.

memory consumption

• Query optimization• Tradeoff: Performance vs. latency

Page 10: Breakout Session 3 Stack of adaptive systems (with a view on self-adaptation)

Open questions:

• Need more interaction scenarios get a better feeling for the possible interactions and how they must be considered

• Coordination of the layers• How can the different layers exchange information• What kind of information