Hardware

June 2012 

TM 

Freescale, the Freescale logo, AltiVec, C-5, CodeTEST, CodeWarrior, ColdFire, 

ColdFire+, C-Ware, the Energy Efficient Solutions logo, Kinetis, mobileGT, PowerQUICC, 

Processor Expert, QorIQ, Qorivva, StarCore, Symphony and VortiQa are trademarks of 

Freescale Semiconductor, Inc., Reg. U.S. Pat. & Tm. Off. Airfast, BeeKit, BeeStack, 

CoreNet, Flexis, MagniV, MXC, Platform in a Package, QorIQ Qonverge, QUICC Engine, 

Ready Play, SafeAssure, the SafeAssure logo, SMARTMOS, TurboLink, Vybrid and 

Xtrinsic are trademarks of Freescale Semiconductor, Inc. All other product or service 

names are the property of their respective owners. © 2012 Freescale Semiconductor, Inc. 

. 

Steve Furr 

Software Product Manager

• Service providers increasingly supporting multiple tenants in 

service-oriented networks to maximize resource utilization 

• Content, data volume and increased density stress networks and 

drive demand for multicore processing support 

• Partitioning and virtualization technologies enable the efficient 

management of traffic between multiple tenants 

• Partitioning technologies further enhance the secure and reliable 

operation of tenants so that they are isolated from the effects of 

other tenants 

• QorIQ processors contain features that enable efficient 

partitioning and virtualization on behalf of tenants 

• Freescale provides enablement for key software technologies to 

facilitate different partitioning and virtualization approaches 

TM 

2 

Freescale, the Freescale logo, AltiVec, C-5, CodeTEST, CodeWarrior, ColdFire, ColdFire+, C-Ware, the Energy Efficient Solutions logo, Kinetis, 

mobileGT, PowerQUICC, Processor Expert, QorIQ, Qorivva, StarCore, Symphony and VortiQa are trademarks of Freescale Semiconductor, Inc., 

Reg. U.S. Pat. & Tm. Off. Airfast, BeeKit, BeeStack, CoreNet, Flexis, MagniV, MXC, Platform in a Package, QorIQ Qonverge, QUICC Engine, 

Ready Play, SafeAssure, the SafeAssure logo, SMARTMOS, TurboLink, Vybrid and Xtrinsic are trademarks of Freescale Semiconductor, Inc. All 

other product or service names are the property of their respective owners. © 2012 Freescale Semiconductor, Inc.

• After completing this session you will be able to: 

− Understand the various architectural approaches to partitioning 

and virtualizing network elements for multiple tenants 

− Understand the facilities provided by QorIQ AMP processors in 

support of each approach 

− Map architectural approaches to Freescale software 

technologies 

TM 

3 






• Market Drivers 

• Partitioning & Virtualization Approaches 

• Processor Enablement 

• Software Technologies 

TM 

4 






Streamlined, 

efficient 

resource 

management 

is key 

Tablets 

eReaders 

Smartbooks 

Mobile Devices 

Smartphone 

Residential Gateway 

Smart Meter 

Compute resources required always-on anytime, everywhere 

TM 

Factory HMI 

Medical Devices 

Smart Energy Grid 

Telematics 

Auto Infotainment 

Machine to Machine 

5 

Energy Gateways 

Human Collaboration 

Video/IP Phones 

Wireless Access Points 

Transformation 

of services 

delivery 

Network Centricity 

Touchscreen Printers 

Mobile Computing 

Desktop Computing 






• Service Providers focus on more than bandwidth provisioning – 

increasing network services in the infrastructure: 

− Network Security – Firewall, IPsec VPN, IDS/IPS, Web Application Firewalls. 

− Application Delivery Controllers – To balance the traffic across multiple 

physical/virtual servers. 

− WAN Optimization – To reduce the traffic on WAN links. 

• Multi-tenancy Public Clouds support large number of tenants; 

enables sharing of resources and costs among many network 

service appliances for a large pool of users, allowing: 

− Centralization of infrastructure in locations with lower costs (such as real estate, 

electricity, etc.) 

− Peak-load capacity increases (users need not engineer for highest possible 

load-levels) 

− Utilization and efficiency improvements for systems that are often only 10–20% 

utilized 

• Multi-tenant architectures – a trend in network services appliances 

– requires multicore technology 

The network plays a key role in how the service provider enables scalable, 

on-demand, flexible yet secure bundles of services 

TM 

6 






Increasing number 

of connections 

Multi-tenancy 

& multi-services 

TM 

Ever increasing 

Bandwidth Needs 

High Performance 

Multicore HW Virtualization- 

Enabled Processors 

7 

Increasing types of 

network content 

Low Power 

Low Cost 






• Our Approach 

− Best-in-class 

performance within a 

power envelope 

− Scalability up and 

down with a 

common 

architecture 

− Leading integration 

of communications, 

security, I/O 

requirements 

− Complete software 

environment with 

virtualization 

TM 

Management 

Interfaces 

Standard 

I/O 

128KB 

Backside 

L2 Cache 

Security 

Accelerators 

8 

Power Architecture ® 

E500-mc Core 

32KB 

D-Cache 

32KB 

I-Cache 

Datapath 

Acceleration 

1024KB 

Frontside 

L3 Cache 

1024KB 

Frontside 

L3 Cache 

CORE-NET 

High-Speed 

Interconnect 

Hardware-based Virtualization 

64-bit 

DDR-2/3 

Memory Controller 

64-bit 

DDR-2/3 

Memory Controller 

Debug 

18-Lane 5GHz SERDES 

Designed for performance, power efficiency and scalability 

CPU 

Cores 

DPAA 

Accelerators 

Software 






Requirement Freescale’s Approach 

Multi-Tenancy 

Hardware Partitioning 

• Separate hardware partition (AMP) per 

tenant/OS 

• Cores and peripherals dedicated to partitions 

Single OS Partitioning 

• Data Virtualization 

• Single shared address space between tenants 

• Process based virtualization 

• Set of processes dedicated to a tenant. 

• OS virtualization 

• Domain isolation (file system, net i/f) between 

tenants 

Server Virtualization 

• Separate virtual machine (VM) and OS per tenant 

TM 

9 

Hardware (Cores) 

• Core performance still matters 

• Focus on high performance, high IPC 

Hardware (DPAA) 

• Leveraging data path for traffic management 

• Associations with tenancy 

Hardware (Accelerators) 

• Access to accelerators with minimal overhead 

• Sharing of resources for performance 

Software 

• Access to H/W + User space abstraction 

• Efficient use of resources 

Target: Scalable and Efficient Performance 






C 

P 

U 

C 

P 

U 

VM 

VM 

Multicore Hardware 

VM 

App App App 

OS OS OS 

Embedded Hypervisor 

C 

P 

U 

App 

CP 

U 

Linux 

C 

P 

U 

CP 

U 


Linux ® 

SMP 

App App 

Hardware 

Partitioning / 

supervised AMP, 

failover 

C 

P 

U 

TM 

C 

P 

U 

App App 

C 

P 

U 

C 

P 

U 

Linux 

CP 

U 

CP 

U 

BB 


Unsupervised AMP 

App 

CP 

U 

VM 

App 

OS 

Linux 

CP 

U 


10 

C 

P 

U 

VM 

BB 

Server 

virtualization 

App 

OS 

KVM KVM 

Topaz KVM: Linux-based Hypervisor 

C 

P 

U 

Consolidation, high 

performance 

user space DPA 

engines 

Linux OS 

Convergence 

Leverage both 

KVM & LXC 

OS 

Virtualization 





other product or service names are the property of their respective owners. © 2012 Freescale Semiconductor, Inc. 

C 

P 

U 

C 

P 

U 

COS 

App 

App 

COS 

Linux 


COS 

LXC LXC LXC 

CP 

U 

CP 

U 

USDPAA USDPAA 

Linux 



USDPAA USDPAA 

CP 

U 

CP 

U 

Isolated 

Containers, 

resource control & 

monitoring 

Linux Containers 

C 

P 

U 

C 

P 

U


Multi-Tenancy 



tenant/OS 









tenants 



TM 

Hardware (Cores): 

Large number of cores – Dedicate cores to tenants 

High IPC 

Advanced Cache architecture 

Hardware hypervisor enablement 


Dedicate Ethernet Ports to Processes/Virtual Machine. 

Sharing of Ethernet Port across multiple tenants. 

No Kernel demux of packets – Direct user space access. 

Classification of tenant can be done in HW. 


Engines can be accessed directly from user space. 

Multiple user space daemons can access offload engines. 

No Kernel demux required (large number of FQs). 

Support for large number of connections. 

Software: 

USDPAA , Low level APIs to access HW. 

KVM / QEMU support in Linux distributions. 

UIO Support in Linux to inform interrupts to user space. 

Direct Portal access (Memory mapping). 

HugeTLBFs Support in Linux 


11 






• Frequency does still matter 

• Higher efficiency (IPC) means 

higher performance 

• Cache architecture and size 

impact performance 

• Cache “stashing” and warming 

reduces data access latency 

• Hypervisor hardware improves 

software efficiency 

• Performance monitoring and 

instruction trace are keys to 

multicore debug 

• Vector processing further 

enhancing software performance 

TM 

12 

Branch 

Unit 

Integer 

Unit 

(2) 

e500mc Core 

I-Cache/ 

SRAM 

(32KB) 

Address 

I-Fetcher 

Dispatch Unit 

GPR 

Complete 

Unit 

Ld/St 

Unit 

MMU 

APUs 

Processor Interface Unit 

64 

Read-1 

FPU 

128 

Read-2 

e500mc Core Complex 

CPU 

Cores 

DPAA 

Accelerators 

Software 

D-Cache/ 

SRAM 

(32KB) 

Write 

128 






• Key hardware 

resources are 

accessible by 

hypervisor 

privileged state 

only: 

− MMU 

− Timers 

− Cache control 

− Debug 

resources 

− Interrupt 

Configuration 

• Key resources 

to optimize 

guest OS 

access: 

− LRAT 

TM 

User 

MSR[PR=1][GS=0] 

Kernel/Supervisor 


No Hypervisor 

partition 

App 

OS 

CPU 

Memory 

I/O 

13 

User 


Kernel/Supervisor 


Hypervisor 


With Hypervisor 

partition 

App 

App 

OS 

Hypervisor 

CPU 

Memory 






I/O

• PAMU enforces 

I/O-to-memory 

accesses 

• A key 

component in a 

securely 

partitioned 

system 

TM 

Access 

OK 

CPU 

I/O 

Linux ® OS 

Memory 

PAMU 

14 

CPU CPU CPU 

I/O 

Access 

Denied Memory 

I/O 







Multi-Tenancy 



tenant/OS 









tenants 



TM 



High IPC 





Sharing of Ethernet Port across multiple tenants 




Engines can be accessed directly from user space 


No Kernel demux required (large number of FQs) 

Support for large number of connections 

Software: 




Direct Portal access (Memory mapping) 



15 






• FMAN 

− VLAN-ID and IP address packet 

distribution 

− Protocol field extraction 

− Fairness and traffic prioritization 

− Classify packets 

• QMAN 

− Manage priority of flows 

− Low software overhead queuing 

• BMAN 

− Avoid overhead of S/W managed 

memory pools 

• Queues are serviced by different 

cores for load/work spreading and 

tenancy association 

TM 

16 

Power 

D$ I$ 

Architecture 

L2$ D$ I$ 

® 

D$ Power I$ 

Architecture 

L2$ D$ Core I$ 

D$ I$ 

® 

Core 

D$ I$ 

Frame Manager 

Frame Manager 

1GE 1GE 

10GE 

1GE 1GE 

10GE 

1GE 1GE 

1GE 1GE 

CoreNet 

Coherency Fabric 

Sec 4.0 PME 2 

Queue 

Manager 

Buffer 

Mgr 

Multi-Lanes SERDES 

Any packet to any core to any accelerator or network interface 

without locks or semaphores 

… 

… 

CPU 

Cores 

DPAA 

Accelerators 

Software 







Multi-Tenancy 



tenant/OS 









tenants 



TM 



High IPC 













Software: 







17 






TM 

18 

• Offloads computeintensive 

encryption/ 

decryption, public key, 

security protocol 

− IPsec, SSL/TLS, 

LinkSec, MacSec 

− Public key cryptography 

− Random number 

generation 

− Cryptographic 

authentication 

− Encryption and 

decryption 

CPU 

Cores 

DPAA 

Accelerators 

Software 

− Advanced protocol 

support 







Multi-Tenancy 



tenant/OS 









tenants 



TM 



High IPC 






No Kernel demux of packets – Direct user space access 

. Classification of tenant can be done in HW. 






Software: 







19 






• Freescale Embedded 

Hypervisor 

− A lightweight framework for 

partitioning an SoC 

− Gives you the best of both 

worlds – bare-metal 

performance with enforced 

partitioning and fully 

architected approach to 

meeting AMP requirements 

− Solves many of the headaches 

of running multiple 

unsupervised OSes 

− Threads appear as cores to 

OS 

TM 

Topaz 

20 

I/O 

MMU 

Interrupt 

Controller 

App App 

OS 

CPU CPU CPU 

Memory 

I/O 

App App 

OS 

Memory 






I/O

MMUs 

PAMU 

TM 

Partition 1 Partition 2 

Freescale Embedded Hypervisor 

Device 

Dedication 

Core 0 Core 1 Core 2 Core 3 

DPAA Devices DPAA Devices 

21 






• Linux Containers Overview 

− Containers provide OS-level virtualization 

Provides low overhead, lightweight, secure 

partitioning of Linux applications into different 

domains 

Can control resource utilization of domains – 

CPU, I/O bandwidth 

Linux Containers is based on a collection of 

technologies including kernel and user-space 

components 

TM 

22 






C 

P 

U 

COS 

App 

COS 

Linux 


COS 

LXC LXC LXC 

CP 

U 

USDPAA USDPAA 

CP 

U 

Linux Containers 

C 

P 

U

• KVM is a Linux kernel driver 

• User space tool, QEMU, is used in 

conjunction with KVM 

• Solution is open source 

• Highlights 

− Number of virtual machines is only 

limited by available resources (CPU 

cycles, memory) 

− No or minimal OS changes required 

− Virtual I/O – multiple partitions share 

disk, network interfaces, serial 

− Direct/pass-thru I/O – assign devices 

to partitions 

− ePAPR compliant 

− Interface to debug virtual machines 

TM 

23 

Virtual 

Machine 1 

App 

OS 

QEMU 

kvm 

Virtual 

Machine 1 

App 

OS 

QEMU 

Linux ® Kernel 

App 






Tenants 1-20 Tenant 21 Tenants 50, 51 

PME 

APP 

Drivers 

Kernel Space 

TM 

APP 

Drivers 

ETH SEC PME 

… 

APP 

Drivers 

USDPAA USDPAA USDPAA 

VLAN IDs 

1 - 20 

VLAN ID 

21 

… 

Parse, Classify, Distribute 

Drivers 

… 

User Space 

Network 

Traffic 

ETH SEC 

… 

Kernel Mode App 

VLAN IDs 

50, 51 

DPAA 

24 

• Process Model 

− 1 process, 1 tenant 

− 1 process, N tenants 

− Multi-threaded process 

− Multiple processes, 1 tenant 

• User-space memory mapped DPAA 

access (USDPAA) 

− Access partitioning via portals 

− One portal per process/thread 

− Polling or interrupt based 

• Ingress packet distribution to 

processes 

− HW Parse/Classify/Distribute 

e.g. VLAN-id determines destination 

process/thread 

− Hierarchical Classification – If a tenant 

has multiple processes. 

− Separate packet buffer pools per tenant 

for isolation 

− Zero-copy lockless packet path 

CPU 

Cores 

DPAA 

Accelerators 

Software 






• Multi-tenant deployments are key to enabling efficient and 

scalable service provider networks 

• Multicore processors addressing increased performance, 

security, cost and power reduction and are keys to success 

• Freescale QorIQ multicore networking processors and 

VortiQa software provide the performance scalability 

necessary for virtualization and efficient use of resources 

− Delivering best-in-class multicore power / performance 

TM 

Freescale on Kaixin 

Tag yourself in photos 

and upload your own! 

Session materials will be posted @ www.freescale.com/FTF 

26 

Weibo? 

Please use hashtag 

#FTF2012# 






• URLs: 

− www.freescale.com/virtualization 

• SME Contact information 

− Steve Furr, Software Product Manager 

− steve.furr@freescale.com 

TM 

27 






• By now, you should be able to: 

− Effectively describe, at a high level, partitioning and 

virtualization approaches in service-oriented networks 

− Understand how facilities in QorIQ AMP processors enable 

partitioning and virtualization approaches 

− Understand the distinct Freescale software technologies 

offered for partitioning and virtualization and which to choose 

for specific partitioning and virtualization approaches 

TM 

28

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