Chapter 9. Multiprocessor Virtualization

1. Chapter 9.Multiprocessor Virtualization Mobile Embedded System Lab. Ki Seok Choi (최기석)

2. Contents • Introduction to Multiprocessor Systems • Multiprocessor Architecture • Types of multiprocessing • Clustered Systems • Shared-Memory Systems • Partitioning of Multiprocessor Systems • Motivation • Mechanisms to Support Partitioning • Types of Partitioning Techniques • Physical Partitioning

3. Introduction to Multiprocessor Systems • What is a Multiprocessor System? • A single system that has multiple processors [Developers.net] • What is the goal? • To solve compute-intensive problems faster [Michael J. Quinn] • To solve larger problems in same amount of time [Michael J. Quinn]

4. Multiprocessor Architecture • Types of multiprocessing system • Clustered system • Shared-memory processing system (SMP) • Hybrids of clustered and SMP system • Distributed shared memory system (DSM) • SMP clusters system

5. Clustered system • A system that has multiple nodes • Each node has • a processor • a memory • I/O devices • an operating system • Good for independent workloads P P M I/O M I/O Network connection for message passing M I/O M I/O P P

6. Shared-memory processing system(SMP) • A system that has • multiple processors • a memory • I/O devices • an operating system • Good for applications with shared data P P P M I/O

7. Hybrids of clustered and shared-memory • Distributed shared memory system (DSM) • Clustered system supporting a single OS image across the multiple processors • Not popular because of the high sensitivity of the performance of applications to the algorithms and data structures • SMP clusters system • Clustered system of nodes • Each node is a small SMP

8. Clustered Systems (1/2) • Cluster = terminal node + server nodes + network • Terminal node – allows the user to access cluster • Server node – executes specific service routines • Network – connects nodes for communication • Example • IBM Parallel Sysplex system • HP Superdome Hyperplex system

9. Clustered Systems (2/2) • Beowulf cluster system (1997) • Inexpensive commodity CPU • Inexpensive commodity disk • Inexpensive 100Mbps ethernet network • Free OS (Linux) • Blade server – denser form of Beowulf cluster • Unnecessary I/O devices are eliminated in each node. • Tight form of node in a thin package is called blade.

10. Shared-memory systems • Many commercial applications are based on shared-memory paradigm. • More convenient to write programs than message-passing paradigm • But, hardware needed to support these systems is more complex than those for message-passing systems. • To maintain coherence in memory locations

11. Memory coherence models • Memory coherence refers to the visibility of a write to a given memory location by all other processors in the system. • Memory coherence is satisfied if the order of writes to a given location by one processor is maintained when observed by any other processor in the system.

12. 50 gets evictedfrom P2 cache P2’s writerequest arrived P2 reads 2@50 P2 requestswrite 2@50 P2 reads 2@cached 50 P2 reads 1@50 50 gets evictedfrom P2 cache P1 requestswrite 1@50 P1 reads 1@cached 50 P1’s writerequest arrived 50 gets evictedfrom P1 cache P1 reads 1@50 P1 reads 2@50 Memory coherence models Assumption : write-through caches and longer delay to P2 cache than P1 cache 0 1 2 P1 sees the order “0-1-1-2”, while P2 sees “0-2-1-2” : violation of memory coherency

13. Memory coherence models • Write Invalidate Protocol • Write to shared data  an invalidate is sent to all caches which snoop and invalidate any copies • Write Broadcast Protocol • Write to shared data  broadcast on bus, processors snoop, and update copies

14. Memory coherence models

15. MPI vs. OpenMP • MPI = “Message Passing Interface” • Standard specification for message-passing libraries • Libraries available on virtually all parallel computers • Free libraries also available for networks of workstations or commodity clusters • OpenMP = “Open Multi Processing” • OpenMP an application programming interface (API) for shared-memory systems • Supports higher performance parallel programming of symmetrical multiprocessors

16. Multiple Processors Applications • Used in servers and high-end desktop systems • Have large amounts of memory and I/O devices • Web servers : manage huge databases and service requests simultaneously • Computational servers : used for large scientific calculations with huge amount of memory and disk capacity

17. Utilization of Multiprocessors • Actual number of physical processors > ideal number of processors needed • Cause 1: limitations of parallelism available in the programs • Cause 2: limitations in the scalability of applications due to the overhead of communication between processors • Multiprocessor system needs to be partitioned to utilize system resources.

18. Partitioning • Two dimensions of partitioning • In time domain • In space domain • Can be mixed together • We can partition the multiprocessing system to several virtual multiprocessing systems. • Virtual architectures are independent to actual platforms. • We focus on several virtual shared-memory systems operating simultaneously on a single shared-memory host system

19. Partitioning of SMP system Virtual Machine 1 Virtual Machine 2 Virtual Machine 3 P P P P P P P P Memory I/O Memory I/O Memory I/O Virtual Machine Monitor P P P P P P P P P Actual SMP hardware Memory I/O

20. Motivation : Workload consolidation • SMP system is widely used. • Advanced cache coherence technology • Ease of programming • But it is very expensive. • Large number of disks • Requirement for high reliability • Need for special environment (by cooling and security) • So functions are distributed to several systems. • Ex) three-tier model (ref. next page)

21. Motivation : Workload consolidation • Three-tier model Database server Application server Application server Application server User PC User PC User PC User PC User PC User PC

22. Motivation : Workload consolidation • Recently, administrative costs of computer centers are critical. • They are dependent on the number of systems. • These cost are lowered by reducing the different types of systems in the center. • So the small systems are integrated to a single large system.

23. Motivation : Workload consolidation • Consolidation model Database server Virtualized App. Server Virtualized App. Server Virtualized App. Server User PC User PC User PC User PC User PC User PC

24. Motivation : Workload consolidation • The consolidation of multiple workstation users on a large remote server • Problem : Need to address the problems of privacy protection and flexibility requirement • Solution : Virtualization of large servers through partitioning of physical resources

25. Motivation : Cluster-based programming model • Recently, inexpensive blade servers are increasing. • Programming tools and applications for clustered platform are rapidly increasing. • SMP system needs to have ability to run cluster-based applications (written with MPI). • The Program using MPI can run unchanged on a partitioned system.

26. Motivation : System Migration • New version of application should be tested before migration.

27. Motivation : Reduction of System Downtime • Upgrade of existing OS requires system to shutdown. • This can be done in a spare partition.

28. Motivation : Heterogeneous Systems • Sometimes the old OS should run while the new one is running.

29. Motivation : Improving System Utilization • The system can be configuredaccording to the changing workload • Configured as a single system image of the whole system for peak workload • Configured as multiple partitions running separate OS for average workload • Capacity planning helps to determine the partition scheme and keep the compute requirement closer to the average workload • Dynamic migration of resources from one partition to another helps improving the utilization of resources

30. Motivation : Multiple Time-zone requirements • It is common for some international company to have geographically distributed branches • It is necessary to bring down the system for maintenance or upgrade at a convenient local time especially at night. • Partition system can make decisions independent of the other regions

31. Motivation : Failure Isolation • Most important feature of partitioning • There are many failures that can be occurred. • Attacks over the network • Malfunctions of software • Hardware failures • Partitioning helps isolate the effects of failure. • Hardware failures may or may not be local to a partition • Depend on the nature of partitioning • Time multiplexed partitioning scheme – not local • Physically partitioning scheme – local

32. Mechanisms to Support Partitioning • VMM is the key part to perform partitioning and can be implemented in different ways • Completely in hardware • Microcode supported by hardware • Software supported by hardware • Make hardware modifications to support virtualization => VMM can operate in a new privilege mode • Advantage: avoid the need to run a guest OS in user mode which will cause performance degradation • Disadvantage: unable to virtualize in a recursive manner

33. Types of Partitioning Techniques • Spectrum of partitioning (N: # of processors) • Types of partitioning are classified according to implementation of VMM • Those with hardware support • Those without hardware support N-way SMP N nodes Clustered

34. Types of Partitioning Techniques Partitioning Techniques With hardware support Without hardware support Physical Partitioning Logical Partitioning SVM-Based Approaches OS-Based Approaches Microprogram Based Hypervisor Based Same ISA Different ISA

35. Types of Partitioning Techniques Partitioning Techniques With hardware support Without hardware support Physical Partitioning Logical Partitioning SVM-Based Approaches OS-Based Approaches Microprogram Based Hypervisor Based Same ISA Different ISA

36. Types of Partitioning Techniques • Physical partitioning • Each OS image uses resources distinct from the ones used by the other OS image. • # of partitions is limited to # of processors • Logical partitioning • OS images share some of the physical resources in a time-multiplexed manner. • # of partitions is not limited to # of processors • Two implementations • VMM in microcode (firmware) • VMM as a codesigned firmware-software layer (hypervisor)

37. Types of Partitioning Techniques Partitioning Techniques With hardware support Without hardware support Physical Partitioning Logical Partitioning SVM-Based Approaches OS-Based Approaches Microprogram Based Hypervisor Based Same ISA Different ISA

38. Types of Partitioning Techniques • System VM-based approach • Multiple OS images on a single system  multiple virtual SMP systems on a single SMP system • The only way to provide a virtual multiprocessing system whose ISA is different from the ISA of the host system • OS based approach • Partitioning of resources among processes (OS function) • Do not provide VM  different OS can not run additionally.

39. Physical Partitioning • Simplest, easiest to implement • Imposes little overhead on an executing application • Allows a partition to own its resources physically • Control of the configuration of each partition is mostly in hardware Receive command Central Control Unit Console of system administrator Send commands HW resource HW resource HW resource

40. Physical Partitioning : Advantages • Failure isolation • Isolation of SW failure • The control unit can reset the partition and reboot the OS for that partition without other partitions affected. • Isolation of HW failure • One physical unit is associated with only one partition. • Can not eliminate single points of failure • Control unit failure  make it smaller and simpler • The crossbar switch connecting different boards make communication paths robust, add redundancy

41. Physical Partitioning : Advantages • Better security isolation • Each partition is protected from the DoS attacks by otherpartitions • System administrator of one partition can not take unauthorized action in other partitions

42. Physical Partitioning : Advantages • Better ability to meet system-level objectives • System-level objectives – results from contracts between system owners and users. • Physical partitioning creates partitions that are fixed and guaranteed independent of time.

43. Physical partitioning : Limitations • System utilization is bad. • Dynamic workload balancing is difficult because of physical constraints placed by fault isolation requirements. • Flexibility in allocating resources to partitions is not good.