Inbyggda realtidssystem: En flerkärning frälsning

Embedded real-time systems: A multi-core salvationThomas Nolte, 2013-04-25

1997 – 2000 – 2006 – 2009 – 2012Undergrad.

StudentGrad./PHD

StudentAssistant Professor

Associate Professor

ProfessorABB CRC

2002 2005, 2006

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5

Embedded systems

Environment

Control program

sensors

actuators

TaskTaskTaskTask

CPU

Key properties of interest = performance & predictability

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Embedded systems

LINK

8

9

Too EARLY inflation

Too LATE inflation

Perfect TIMING

Environment Control program

sensors

actuators

TaskTaskTaskTask

When software is executing, it is executing as tasks

void foo(){

…while(status){

in = read_sensor();action = take_action(in);…status = perform_action(action);sleep(1000);

}}

Task

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Instruction and data memory (1)

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Instruction and data memory (2)

DATAINSTRUCTION

void foo(){

…while(status){

in = read_sensor();action = take_action(in);…status = perform_action(action);sleep(1000);

}}

Task

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Instruction and data memory (3)

cache memory

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Instruction and data memory (4)

cache memory

Key properties of interest = performance & predictability

A simple model

Environment Control program

sensors

actuators

TaskTaskTaskTask

task task task

time

period

worst-case execution time

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What to run and when

Environment Control program

sensors

actuators

TaskTaskTaskTask

task1 task1 task1

time

task2 task2 task2

time

task2

prio low

prio high

time

task2 task2 task2 task2task1 task1 task1

The scheduler decides which task to execute

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Determining the response time

Environment Control program

sensors

actuators

TaskTaskTaskTask

time

task2 task2 task2 task2task1

preempted preempted

resumed resumed

finished

response time of task1

response timeof task2

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Predictability wrt embedded control systems● Program, or task

● Instruction for how the computer should work, i.e., what the computer shall do

● Execution time● How long time it takes for the program/task to

execute● Response time

● How long time it takes for the program/task to execute to completion, also when running together with other programs/tasks

● Research conducted the past 30 yearsPretty good understanding how predictable embedded systems should be constructed

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The multi-core arrived!● Isn’t more better?

The Free Lunch Is Over A Fundamental Turn Toward Concurrency in SoftwareBy Herb Sutter

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The multi-core revolution

single core dual core quad core multi core

parallel computer = many cores

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Multi-core memory hierarchy (1)

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Multi-core memory hierarchy (2)

Challenges with many cores

● Sequential guarantee is not valid anymore● Programs could previously execute in parallel, but

at any given time only one program is executing

● Now at any given point in time as many programs as there are cores can be executing

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pgm1

timepgm2 pgm2 pgm2

time

pgm2

Core 1

Core 2

pgm2 pgm2 pgm2 pgm2pgm1

timeCore

Performance on a parallel machine (1)● The way we construct programs become

different

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100 chefs do not bake 1 cake 100x

faster than 1 chef

Performance on a parallel machine (2)● The way we execute programs become

different

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pgm1

time

Core pgm1 pgm1

100

5149

pgm2

51

Performance on a parallel machine (3)● The way we execute programs become

different

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pgm1

timepgm2 pgm2 pgm2

time

Core 1

Core 2

pgm1 pgm1

100 51

50%

Performance on a parallel machine (4)● The way we execute programs become

different

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timepgm2 pgm2 pgm2

time

Core 1

Core 2

pgm1 pgm1 pgm1pgmj pgmj pgmj

Predictability under parallelism (1)● New techniques are required to resolve

conflicts

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pgm1

timepgm2 pgm2 pgm2

time

pgm2

Core 1

Core 2

Predictability under parallelism (2)● New techniques are required to resolve

conflicts

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pgm1

timepgm2 pgm2 pgm2

time

pgm2

Core 1

Core 2

shared memory

Predictability under parallelism (3)● New techniques are required to resolve

conflicts

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pgm1

timepgm2 pgm2 pgm2

time

pgm2

Core 1

Core 2

shared memory

…and the many-core is here!● More is better?

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EpophanyTM Multi-core Solution

single core dual core many core

76421

654321

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1 2 3 4 5 6 7

emptycore

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• task scheduling • task partitioning• task scheduling

• local• global

• task partitioning• task scheduling• idle?

1 2 3 4 5 6 7assume 7 tasks:

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New challenges

task0

task1

task2

task3

task4

task5

task6

task7

task8

task9

• Less shared state and data among cores• Locality important when sharing data• More message passing (via powerful interconnects)•Sleep cores when idle to save power

Our efforts wrt. multi/many-core

● New ways to program and analyze● Meng Liu (PhD Student)● Hamid Reza Faragardi (PhD Student)

● New ways to partition and design● Moris Behnam (Senior Lecturer)● Daniel Hallmans (PhD Student)

● New ways to execute● Mikael Åsberg (PhD Student)● Nima M. Khalilzad (PhD Student)

● New ways to communicate and synchronize● Mohammad Ashjaei (PhD Student)● Sara Afshar (PhD Student)

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PhD studen

tPost-doc

Key CORE main research areas (2013): Multi-core and many-core real-time systems Real-time systems scheduling and

synchronization Predictable execution of real-time systems Compositional execution and analysis of real-

time systems

Simulation-based analysis of embedded systems

Stochastic and statistical analysis of real-time systems

Real-time communications Adaptive and reconfigurable real-time

systemsCORE alumni:

The Complex Real-Time Embedded (CORE) research group:

Mikael Åsberg Nima M. Khalilzad Daniel Hallmans Mohammad Ashjaei Sara Afshar Meng Liu

Kristian Sandström Moris Behnam Thomas Nolte Hamid R. FaragardiTBD TBD

Insik Shin Holger Kienle Johan Kraft Farhang Nemati Yue Lu Anders Wall

Embedded real-time systems: A multi-core salvationThomas Nolte, 2013-04-25