CARUSO

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CARUSO an Approach Towards a Network of Low
Power Autonomic Systems on Chips for Embedded
Real-time Applications

• Uwe Brinkschulte, Jürgen Becker
• University of Karlsruhe, Germany
• Theo Ungerer
• University of Augsburg, Germany

WPDRTS 04, Santa Fe, April 2004
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Outline of the Presentation

• Motivation
• CARUSO Principle Goals
• State of the Art
• Research Objectives
• CARUSO System Architecture
• CARUSO Roadmap
• Conclusions

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1. Motivation
Systems on Chip (SoC) state of the art to build
embedded computing systems with limitations in
space and power consumption
In contrast to microcontroller solutions, the
entire system is integrated on a single chip
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1. Motivation

• SoC can be used to build complex distributed
  embedded systems, e.g.
• Distributed Robot Control
• Robot Swarms
• Complex Image Processing
• ...
• Designed in conventional style, these systems
  require a lot of effort for configuration,
  optimization, maintenance, ...

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2. CARUSO Principle Goals

• CARUSO
• Connective Autonomic Real-time Ultra-Low-Power
  System on
• Chip
• is a new SoC project
• is work-in-progress
• is a joint venture of several research
  groups/topics
• aims to simplify the development and operation of
  complex embedded systems.
• integrates hardware and software for high
  performance embedded computing with respect to
  other requirements

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2. CARUSO Principle Goals

• Autonomic Computingself-Organization,
  self-Configuration, self-Optimization,self-Protec
  tion, self-Healinggt robust, flexible, adaptive
  embedded systems minimum human interaction
• Connectivityto form dynamic ad-hoc networksgt
  cooperation of multiple small computing
  components self-healing, self-optimization
• Real-timesoft-, firm- and hard real-time gt is
  a key feature for many embedded applications

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2. CARUSO Principle Goals

• Ultra Low Poweroptimization of overall and
  single node power consumptiongt increase battery
  life time, adapt to a changing environment (e.g.
  the distribution of available solar energy in a
  distributed network is location dependant and
  might change)
• Cost and Spacereduction of development and
  operational costs, reduction of required spacegt
  fit the upcoming ubiquitous applications
• Performanceuse the latest processor techniques
  (multithreading, reconfigurable hardware,
  power-aware architectures)gt get a good
  performance / power consumption trade-off

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2. CARUSO Principle Goals
Basic idea do not treat each requirement
isolated, but try to explore (and exploit) the
relationship and interactions between
them Example Optimizing the overall energy
consumption of the distributed system including
hardware, software and middleware gt increase of
the optimization space (compared to optimizing
a single node) additional global knowledge about
task distribution, real- time constraints and
execution history can be used
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2. CARUSO Principle Goals

• Main project focus
• to realize a hardware and software architecture
  for CARUSO
• Covered research topics
• multithreaded processor architectures
• reconfigurable SoC
• energy efficient hardware and software design
• helper threads
• real-time systems and middleware
• autonomic computing

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2. CARUSO Principle Goals

• A sketch of our solutions (more details later)
• a multithreaded processor core
• real-time thread scheduling in hardware
• a reconfigurable unit with reconfigurable
  multi-grain data paths
• helper threads for local system monitoring and
  autonomic management
• middleware for global service distribution,
  system monitoring and autonomic management
• energy management based on real-time scheduling,
  service distribution and the local and global
  system monitoring
• a demo application an optical tracking system

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3. State of the Art

• Multithreaded Processor Architectures
• support the execution of multithreaded programs
  by special hardware
• multiple register sets, multiple program
  counters, special pipeline design (thread tag)
• classes of hardware multithreading
• cycle-by-cycle interleaving
• block interleaving
• simultaneous multithreading
• main purpose latency hiding
• newly introduced to several high-end processors
  (e.g. Pentium 4), signal processors and
  microcontrollers (e.g. TriCore 2)

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3. State of the Art

• Multithreaded Processor Architectures
• the Komodo project explored hardware
  multithreading for real-time applications
• multithreaded Java microcontroller, 6 threads,
  block interleaving, 0-cycle context switch
• real-time scheduling in hardware (FPP, EDF, LLF,
  GP)
• GP Guaranteed Percentage Scheduling, assigns
  each thread a guaranteed percentage of the
  processor power in an interval of 100 clock
  cycles
• offers a strict timing isolation of the threads

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3. State of the Art

• still unexplored combining a multithreaded
  processor core with reconfigurable hardware on a
  SoC

Multithreaded Processor Architectures
GP Scheduling
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3. State of the Art

• Reconfigurable SoC
• contains a processor core and a reconfigurable
  part
• the reconfigurable part increases the performance
  and adapts the SoC to a specific task

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3. State of the Art

• Reconfigurable SoC
• classes of reconfiguration
• static (once)
• dynamic (during run-time)
• fine grain (gates)
• coarse grain (function blocks)
• multi grain (data paths between function blocks)
• example HoneyComb, multi grain dynamic
  reconfiguration on a SoC

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3. State of the Art

• to be explored the relationship between dynamic
  reconfiguration, a multithreaded processor core,
  autonomic computing and energy consumption

Reconfigurable SoC
HoneyComb Architecture start node routing
node occupied paths adaptivly routed connection
of distance i
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3. State of the Art

• Energy Efficient Design
• electrical level
• frequency and voltage scaling
• pipeline gating
• microarchitectural level
• reducing external bus transfers
• dynamic power management
• architectural level
• increasing the code density
• static power management

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3. State of the Art

• Energy Efficient Design
• for multithreaded processors
• not much research done yet
• main approach avoid energy consuming speculation
  misses
• for real-time applications
• exploit the time constraints to save energy
• many approaches exploit the deadlines in EDF
• in the Komodo project exploit the
• worst-case/real-case gap in EDF
• requested percentages in GP

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3. State of the Art

• to be explored benefits by combining known
  techniques with new approaches triggered by
  hardware reconfiguration, hardware multithreading
  and middleware

Energy Efficient Design
Energy saving in GP
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3. State of the Art

• Helper Threads
• threads which are separated from the normal
  control flow
• support system management on a multithreaded
  processor core
• branch prediction
• trap handling
• cache preloading
• real-time garbage collection
• real-time debugging,

• to be explored are helper threads a suitable way
  to handle self-management and self-organization
  in autonomic computing?

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3. State of the Art

• Real-time Middleware
• middleware for distributed real-time and embedded
  systems is state of the art (RT-CORBA,
  MinimumCORBA, OSA, )
• new challenges
• reconfigurable SoC
• a component might be realized in software or
  hardware
• middleware has to manage, reconfigure or migrate
  such components in real-time

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3. State of the Art

• Real-time Middleware
• new challenges (cont.)
• autonomic computing
• middleware will be a key component
• responsible for self-x in a distributed system
• energy saving
• find an energy-optimal distribution for the
  current situation
• reduce the resource needs

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3. State of the Art

• Autonomic Computing
• introduced by IBM to simplify the management of
  IT systems
• computing systems should behave like organic
  entities
• self-x properties (self-organizing,
  self-configuring, self-healing, self-protecting,
  self-optimizing, )
• looks like a promising idea to support tomorrows
  embedded and distributed systems (complexity,
  dependability, )

• applying this to SoC needs further exploration

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4. Research Objectives

• Main CARUSO research focus
• exploit the synergy between the different
  requirements and attributes
• Basic research questions

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4. Research Objectives

• Autonomic Computing
• Which interrelationships exist between
  self-optimization, self-protecting, self-healing
  and self-reconfiguration?
• How can this be supported by constructing dynamic
  networks of SoCs?
• What is the influence of the Autonomic Computing
  principles on the real-time properties of the
  system?
• What are the advantages of the dynamic hardware
  reconfiguration feature available in the SoC for
  Autonomic Computing?
• What is the influence of the multithreaded
  processor core?

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4. Research Objectives

• Energy Consumption
• Does the overall optimization of the distributed
  system consisting of hardware, software,
  middleware and configware lead to better results
  than the optimization of the single components?
• Can known time constraints in distributed systems
  be used as additional information source for
  resource usage and an energy-optimal
  distribution?
• Is the possibility of software- and
  hardware-reconfiguration usable to reduce the
  energy consumption?
• And again, what is the influence of the
  multithreaded processor core?

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4. Research Objectives

• Connectivity
• What are the necessary features of the middleware
  in such a system?
• How can middleware support energy saving and
  Autonomic Computing?
• How the middleware is affected by the dynamic
  hardware reconfiguration feature of the
  processing nodes?
• What kind of communication links are necessary
  for an optimal system performance?

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4. Research Objectives

• Real-time
• What is the impact of hard-real-time requirement
  on the architecture of the reconfigurable SoC and
  its multithreaded processor core?
• How the real-time behavior is affected by dynamic
  hardware reconfiguration, Autonomic Computing and
  energy saving?
• Can the real-time constraints deliver any
  additional information to support the
  requirements mentioned above?
• How real-time scheduling is influenced?

• A lot of questions to be answered!

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5. CARUSO System Architecture
Example Applications Optical Tracking System,
Robot Swarms
Global Autonomic Manager
Global Resource Manager
Global Monitoring
Authentification
API
Real-time Middleware Core
Local Autonomic Manager
Local Resource Manager
Local Monitoring
Security Manager
Communication
HW Power-Management
Reconfigurable Peripherals
Reconfigurable Coprocessor
Multithreaded Processor Core
CARUSO Node
CARUSO Node
CARUSO Node
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5. CARUSO System Architecture

• Autonomic Principles (self-X)
• closed control loop
• Monitoring Autonomic Mgmt Resource Mgmt

• local level autonomic management on chip
• global level distributed autonomic management
• monitoring affects the chip, the system software,
  the middleware and the application

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5. CARUSO System Architecture
CARUSO Chip
Dynamic Adaptive Datapaths
Multithreaded Processor Core (SMT)
Memory
EventUnit
Real-time Thread Scheduler
IntelligentDatapathCoupling
ExecutionUnits
VirtualMemoryManager
ExtensionHardwareController
EventCoupling
Standard Input/Output
Peripheral On-DemandHardware
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5. CARUSO System Architecture

• The integration of a multithreaded processor core
  in a
• reconfigurable SoC is a key idea of this project
• It enables the main project goals
• autonomic computing supported by helper threads
  gt local and global autonomic manager gt Self-X
  properties
• energy consumption monitored by helper threads
  gt local and global power management, load
  balancing, deactivation

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5. CARUSO System Architecture

• real-time constraints monitored by helper threads
  gt system reconfiguration, power management
• real-time scheduling supported by multithreaded
  hardwaregt fast context switch, isolation, power
  aware scheduling
• high performance/low power by hardware
  multithreading and hardware reconfigurationgt
  latencies caused by reconfiguration or other
  events are bridged by switching to another
  thread,gt avoids speculation

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5. CARUSO System Architecture

• Application Optical Tracking System
• augmented reality gt tracking of camera
  position and angle
• can be done by detection of characteristics in
  key frames
• problems real-time, precision, energy
  efficiency

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5. CARUSO System Architecture

• Solution network of autonomic SoC

Selection of characteristics
Buffer
Correspondance analysis
Backward tracking
Keyframe selection
Projective reconstruction
Measure ofQualtity
Self-calibration
Video signal
Measure ofQualtity
Translation,Rotation
Calibration-matrix
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5. CARUSO System Architecture

• Application robot swarm
• (e.g. cleaning the floor)
• cooperation
• real-time requirements
• limited energy resources
• highly dynamic
• failures of single robots
• gt autonomic behavior

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6. CARUSO Roadmap

• Planned project duration 3 years
• First year
• basic HW design (multithreaded processor core,
  reconfigurable datapaths) in SystemC
• basic helper threads
• basic RT middleware
• Second year
• hardware prototype in FPGA
• basic local autonomic functions
• basic global autonomic functions
• Third year
• hardware optimization, ASIC synthesis
• extended local and global autonomic functions
• sample application integration
• evaluation

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7. Conclusions

• we propose a new SoC approach
• general ideas
• emphase connectivity, autonomic computing
  principles (self-X), real-time and low-power
• explore and exploit the relationship between the
  different requirements
• hardware ideas
• combine reconfigurable hardware with a
  multithreaded processor core to support
• autonomic management (HW reconfiguration, helper
  threads)
• power management (power aware scheduling in HW,
  multithreading instead of speculation, latency
  bridging)
• real-time (RT scheduling in HW, isolation)

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7. Conclusions

• software ideas
• local autonomic management is done by a closed
  control loop using the helper threads
• global, distributed autonomic management is done
  by a closed control loop using middleware
• the middleware is responsible for
• connectivity
• handling the global autonomic principles (self-x)
• global reconfiguration in HW and SW
• optimization of the global energy consumption
• global real-time properties
• the work has just begun!