SlideShare a Scribd company logo
1 of 2
Adaptive SoC Operations Using Policy Based System Control
Network devices often include “tap points” dispersed across the network’s flows that collect analytics
for monitoring and adapting the network’s behavior according to the actual usage, priority, and type of
content passing through it. Policies such as Quality of Service (QoS), Policy Based Routing (PBR), and
even Call Admission Control (CAC) can then be applied based on the analytics that form the policies for
the adaptation.

As the complexity of SoC operations grow, they too are more resembling networks. For example, the
concept of distributed caches with coherency, recently introduced as an innovation in SoC interconnect
technology, resembles the queues in a network device. But where are the equivalentQoS or PBR
“policies” for the SoC that are present in networks and provide the key adaptive decision making
components?

ChipStart’s SSM represents a control plane for SoCs that operates based on software policies. SSM is a
key subsystem IP component that can be added to any SoC to provide the key missing components to
enable adaptive SoC operations.




The figure above represents a typical implementation of a multicore SoC which contains the SSM
Subsystem IP. Software policies are loaded in the SSM Controller, which in turn converts those policies
into commands. These commands are sent to the SSM MCB’s via the SSM bus for further conversion to
signals and messages to the corresponding IP Blocks. However, since SSM supports bidirectional
communications, the IP Blocks, via the SSM MCBs, can also feedback state data to the SSM Controller via
the SSM bus. This creates the infrastructure for adaptation.

For example, each of the data plane caches associated with the IP blocks can be monitored for cache
misses by the SSM MCBs and reported to the SSM Controller. The SSM Controller then can send the
rolled up view of cache utilization as a global view analytic to the host processor. The host processor
selects the appropriate SSM policy from a set of policies optimized for use cases, a decision that is made
in conjunction with the application requirements, and loads the policy into the SSM Controller memory
for execution. The SSM Controller can then work together with the memory scheduler to better
optimize data block retrieval and distribution, driven by the SSM policy. The result, improved cache
utilization and increased system performance. Alternatively more complex polices can be loaded that
allow the SSM Controller itself to make decisions based on operations conditions. minimizing host
processor participation.
While the main benefit is more effective execution of the application, this can also lead to improved
power management (turning on and off IP blocks when caches are empty for example) and more
predictable error recovery.

Another alternative is to add intelligence to the SSM MCBs themselves, localizing the monitoring and
decision making, which is globally managed by the SSM Controller. This is especially effective when the
IP Blocks transition to IP subsystems and hierarchical interconnect structures become a reality. By using
control plane policy commandsto drive arbitrationdecisions for all the interconnects, data path control
globally across the SoC and within the subsystems themselves can be tied efficiently to application
behavior. This effectively creates policy based routing. Congestion can also be detected which in turn
can trigger flow control, using a profile of subsystem behavior, and communication back to the host
processor would enable the application to adapt as well.

SoC architectures which compliment complex data plane interconnects with control plane subsystems
will scale more efficiently and with higher operations reliability. SSM is the industry’s first merchant
subsystem IP designed for adapting control planes on SoCs while abstracting specific device
personalization to software policies. SSM has also been designed such that overhead is minimized and
real estate and power consumption required are both nominal.

More Related Content

Similar to Adaptive SoC Operations Using Policy-Based System Control

Recover First, Resolve Next – Towards Closed Loop Control for Managing Hybrid...
Recover First, Resolve Next – Towards Closed Loop Control for Managing Hybrid...Recover First, Resolve Next – Towards Closed Loop Control for Managing Hybrid...
Recover First, Resolve Next – Towards Closed Loop Control for Managing Hybrid...
Vinay Rajagopal
 
.Net projects 2011 by core ieeeprojects.com
.Net projects 2011 by core ieeeprojects.com .Net projects 2011 by core ieeeprojects.com
.Net projects 2011 by core ieeeprojects.com
msudan92
 
Tech reportese01 09
Tech reportese01 09Tech reportese01 09
Tech reportese01 09
liangflying
 
NMS Projects and POCs completed and ongoing for OSS NAM v 1.5 Linkedin
NMS Projects and POCs completed and ongoing for OSS NAM v 1.5 LinkedinNMS Projects and POCs completed and ongoing for OSS NAM v 1.5 Linkedin
NMS Projects and POCs completed and ongoing for OSS NAM v 1.5 Linkedin
Javier Guillermo, MBA, MSc, PMP
 

Similar to Adaptive SoC Operations Using Policy-Based System Control (20)

2014 IEEE JAVA CLOUD COMPUTING PROJECT A stochastic model to investigate data...
2014 IEEE JAVA CLOUD COMPUTING PROJECT A stochastic model to investigate data...2014 IEEE JAVA CLOUD COMPUTING PROJECT A stochastic model to investigate data...
2014 IEEE JAVA CLOUD COMPUTING PROJECT A stochastic model to investigate data...
 
SSM White Paper NOV-2010
SSM White Paper NOV-2010SSM White Paper NOV-2010
SSM White Paper NOV-2010
 
JPJ1403 A Stochastic Model To Investigate Data Center Performance And QoS I...
JPJ1403   A Stochastic Model To Investigate Data Center Performance And QoS I...JPJ1403   A Stochastic Model To Investigate Data Center Performance And QoS I...
JPJ1403 A Stochastic Model To Investigate Data Center Performance And QoS I...
 
SoC Subsystem Manager Data Sheet
SoC Subsystem Manager Data SheetSoC Subsystem Manager Data Sheet
SoC Subsystem Manager Data Sheet
 
A stochastic model to investigate data center performance and qo s in iaas cl...
A stochastic model to investigate data center performance and qo s in iaas cl...A stochastic model to investigate data center performance and qo s in iaas cl...
A stochastic model to investigate data center performance and qo s in iaas cl...
 
Provable multi copy dynamic data possession in cloud computing systems
Provable multi copy dynamic data possession in cloud computing systemsProvable multi copy dynamic data possession in cloud computing systems
Provable multi copy dynamic data possession in cloud computing systems
 
Middleware with QoS support to control intelligent systems
Middleware with QoS support to control intelligent systemsMiddleware with QoS support to control intelligent systems
Middleware with QoS support to control intelligent systems
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT A stochastic model to investigate dat...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT A stochastic model to investigate dat...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT A stochastic model to investigate dat...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT A stochastic model to investigate dat...
 
A stochastic model to investigate data center performance and qo s in iaas cl...
A stochastic model to investigate data center performance and qo s in iaas cl...A stochastic model to investigate data center performance and qo s in iaas cl...
A stochastic model to investigate data center performance and qo s in iaas cl...
 
JAVA 2013 IEEE CLOUDCOMPUTING PROJECT A stochastic model to investigate data ...
JAVA 2013 IEEE CLOUDCOMPUTING PROJECT A stochastic model to investigate data ...JAVA 2013 IEEE CLOUDCOMPUTING PROJECT A stochastic model to investigate data ...
JAVA 2013 IEEE CLOUDCOMPUTING PROJECT A stochastic model to investigate data ...
 
a stochastic model to investigate data center performance and qo s in iaas cl...
a stochastic model to investigate data center performance and qo s in iaas cl...a stochastic model to investigate data center performance and qo s in iaas cl...
a stochastic model to investigate data center performance and qo s in iaas cl...
 
Cyber physical manufacturing systems
Cyber physical manufacturing systemsCyber physical manufacturing systems
Cyber physical manufacturing systems
 
A stochastic model to investigate data center performance and qos in iaas clo...
A stochastic model to investigate data center performance and qos in iaas clo...A stochastic model to investigate data center performance and qos in iaas clo...
A stochastic model to investigate data center performance and qos in iaas clo...
 
eet_NPU_file.PDF
eet_NPU_file.PDFeet_NPU_file.PDF
eet_NPU_file.PDF
 
Recover First, Resolve Next – Towards Closed Loop Control for Managing Hybrid...
Recover First, Resolve Next – Towards Closed Loop Control for Managing Hybrid...Recover First, Resolve Next – Towards Closed Loop Control for Managing Hybrid...
Recover First, Resolve Next – Towards Closed Loop Control for Managing Hybrid...
 
Robust Fault Tolerance in Content Addressable Memory Interface
Robust Fault Tolerance in Content Addressable Memory InterfaceRobust Fault Tolerance in Content Addressable Memory Interface
Robust Fault Tolerance in Content Addressable Memory Interface
 
Ieee transactions on 2018 network and service management
Ieee transactions on 2018 network and service managementIeee transactions on 2018 network and service management
Ieee transactions on 2018 network and service management
 
.Net projects 2011 by core ieeeprojects.com
.Net projects 2011 by core ieeeprojects.com .Net projects 2011 by core ieeeprojects.com
.Net projects 2011 by core ieeeprojects.com
 
Tech reportese01 09
Tech reportese01 09Tech reportese01 09
Tech reportese01 09
 
NMS Projects and POCs completed and ongoing for OSS NAM v 1.5 Linkedin
NMS Projects and POCs completed and ongoing for OSS NAM v 1.5 LinkedinNMS Projects and POCs completed and ongoing for OSS NAM v 1.5 Linkedin
NMS Projects and POCs completed and ongoing for OSS NAM v 1.5 Linkedin
 

Recently uploaded

Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Joaquim Jorge
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
Earley Information Science
 

Recently uploaded (20)

08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Evaluating the top large language models.pdf
Evaluating the top large language models.pdfEvaluating the top large language models.pdf
Evaluating the top large language models.pdf
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 

Adaptive SoC Operations Using Policy-Based System Control

  • 1. Adaptive SoC Operations Using Policy Based System Control Network devices often include “tap points” dispersed across the network’s flows that collect analytics for monitoring and adapting the network’s behavior according to the actual usage, priority, and type of content passing through it. Policies such as Quality of Service (QoS), Policy Based Routing (PBR), and even Call Admission Control (CAC) can then be applied based on the analytics that form the policies for the adaptation. As the complexity of SoC operations grow, they too are more resembling networks. For example, the concept of distributed caches with coherency, recently introduced as an innovation in SoC interconnect technology, resembles the queues in a network device. But where are the equivalentQoS or PBR “policies” for the SoC that are present in networks and provide the key adaptive decision making components? ChipStart’s SSM represents a control plane for SoCs that operates based on software policies. SSM is a key subsystem IP component that can be added to any SoC to provide the key missing components to enable adaptive SoC operations. The figure above represents a typical implementation of a multicore SoC which contains the SSM Subsystem IP. Software policies are loaded in the SSM Controller, which in turn converts those policies into commands. These commands are sent to the SSM MCB’s via the SSM bus for further conversion to signals and messages to the corresponding IP Blocks. However, since SSM supports bidirectional communications, the IP Blocks, via the SSM MCBs, can also feedback state data to the SSM Controller via the SSM bus. This creates the infrastructure for adaptation. For example, each of the data plane caches associated with the IP blocks can be monitored for cache misses by the SSM MCBs and reported to the SSM Controller. The SSM Controller then can send the rolled up view of cache utilization as a global view analytic to the host processor. The host processor selects the appropriate SSM policy from a set of policies optimized for use cases, a decision that is made in conjunction with the application requirements, and loads the policy into the SSM Controller memory for execution. The SSM Controller can then work together with the memory scheduler to better optimize data block retrieval and distribution, driven by the SSM policy. The result, improved cache utilization and increased system performance. Alternatively more complex polices can be loaded that allow the SSM Controller itself to make decisions based on operations conditions. minimizing host processor participation.
  • 2. While the main benefit is more effective execution of the application, this can also lead to improved power management (turning on and off IP blocks when caches are empty for example) and more predictable error recovery. Another alternative is to add intelligence to the SSM MCBs themselves, localizing the monitoring and decision making, which is globally managed by the SSM Controller. This is especially effective when the IP Blocks transition to IP subsystems and hierarchical interconnect structures become a reality. By using control plane policy commandsto drive arbitrationdecisions for all the interconnects, data path control globally across the SoC and within the subsystems themselves can be tied efficiently to application behavior. This effectively creates policy based routing. Congestion can also be detected which in turn can trigger flow control, using a profile of subsystem behavior, and communication back to the host processor would enable the application to adapt as well. SoC architectures which compliment complex data plane interconnects with control plane subsystems will scale more efficiently and with higher operations reliability. SSM is the industry’s first merchant subsystem IP designed for adapting control planes on SoCs while abstracting specific device personalization to software policies. SSM has also been designed such that overhead is minimized and real estate and power consumption required are both nominal.