mutiprocessor systems chapter8 ph.d .ppt
- 1. Multiple Processor Systems Chapter 8 8.1 Multiprocessors 8.2 Multicomputers 8.3 Distributed systems
- 2. Multiprocessor Systems • Continuous need for faster computers – shared memory model – message passing multiprocessor – wide area distributed system
- 3. Multiprocessors Definition: A computer system in which two or more CPUs share full access to a common RAM
- 4. 4 Multiprocessor Hardware (1) Bus-based multiprocessors
- 5. Multiprocessor Hardware (2) • UMA Multiprocessor using a crossbar switch
- 6. Multiprocessor Hardware (3) • UMA multiprocessors using multistage switching networks can be built from 2x2 switches (a) 2x2 switch (b) Message format
- 7. Multiprocessor Hardware (4) • Omega Switching Network
- 8. Multiprocessor Hardware (5) NUMA Multiprocessor Characteristics 1. Single address space visible to all CPUs 2. Access to remote memory via commands - LOAD - STORE 3. Access to remote memory slower than to local
- 9. Multiprocessor Hardware (6) (a) 256-node directory based multiprocessor (b) Fields of 32-bit memory address (c) Directory at node 36
- 10. Multiprocessor OS Types (1) Each CPU has its own operating system Bus
- 11. Multiprocessor OS Types (2) Master-Slave multiprocessors Bus
- 12. Multiprocessor OS Types (3) • Symmetric Multiprocessors – SMP multiprocessor model Bus
- 13. Multiprocessor Synchronization (1) TSL instruction can fail if bus already locked
- 14. Multiprocessor Synchronization (2) Multiple locks used to avoid cache thrashing
- 15. Multiprocessor Synchronization (3) Spinning versus Switching • In some cases CPU must wait – waits to acquire ready list • In other cases a choice exists – spinning wastes CPU cycles – switching uses up CPU cycles also – possible to make separate decision each time locked mutex encountered
- 16. Multiprocessor Scheduling (1) • Timesharing – note use of single data structure for scheduling
- 17. Multiprocessor Scheduling (2) • Space sharing – multiple threads at same time across multiple CPUs
- 18. Multiprocessor Scheduling (3) • Problem with communication between two threads – both belong to process A – both running out of phase
- 19. Multiprocessor Scheduling (4) • Solution: Gang Scheduling 1. Groups of related threads scheduled as a unit (a gang) 2. All members of gang run simultaneously • on different timeshared CPUs 3. All gang members start and end time slices together
- 20. Multiprocessor Scheduling (5) Gang Scheduling
- 21. Multicomputers • Definition: Tightly-coupled CPUs that do not share memory • Also known as – cluster computers – clusters of workstations (COWs)
- 22. Multicomputer Hardware (1) • Interconnection topologies (a) single switch (b) ring (c) grid (d) double torus (e) cube (f) hypercube
- 23. Multicomputer Hardware (2) • Switching scheme – store-and-forward packet switching
- 24. Multicomputer Hardware (3) Network interface boards in a multicomputer
- 25. Low-Level Communication Software (1) • If several processes running on node – need network access to send packets … • Map interface board to all process that need it • If kernel needs access to network … • Use two network boards – one to user space, one to kernel
- 26. Low-Level Communication Software (2) Node to Network Interface Communication • Use send & receive rings • coordinates main CPU with on-board CPU
- 27. User Level Communication Software • Minimum services provided – send and receive commands • These are blocking (synchronous) calls (a) Blocking send call (b) Nonblocking send call
- 28. Remote Procedure Call (1) • Steps in making a remote procedure call – the stubs are shaded gray
- 29. Remote Procedure Call (2) Implementation Issues • Cannot pass pointers – call by reference becomes copy-restore (but might fail) • Weakly typed languages – client stub cannot determine size • Not always possible to determine parameter types • Cannot use global variables – may get moved to remote machine
- 30. Distributed Shared Memory (1) • Note layers where it can be implemented – hardware – operating system – user-level software
- 31. Distributed Shared Memory (2) Replication (a) Pages distributed on 4 machines (b) CPU 0 reads page 10 (c) CPU 1 reads page 10
- 32. Distributed Shared Memory (3) • False Sharing • Must also achieve sequential consistency
- 33. Multicomputer Scheduling Load Balancing (1) • Graph-theoretic deterministic algorithm Process
- 34. Load Balancing (2) • Sender-initiated distributed heuristic algorithm – overloaded sender
- 35. Load Balancing (3) • Receiver-initiated distributed heuristic algorithm – under loaded receiver
- 36. Distributed Systems (1) Comparison of three kinds of multiple CPU systems
- 37. Distributed Systems (2) Achieving uniformity with middleware
- 38. Network Hardware (1) • Ethernet (a) classic Ethernet (b) switched Ethernet Computer (a) (b)
- 39. Network Hardware (2) The Internet
- 40. Network Services and Protocols (1) Network Services
- 41. Network Services and Protocols (2) • Internet Protocol • Transmission Control Protocol • Interaction of protocols
- 42. Document-Based Middleware (1) • The Web – a big directed graph of documents
- 43. Document-Based Middleware (2) How the browser gets a page 1. Asks DNS for IP address 2. DNS replies with IP address 3. Browser makes connection 4. Sends request for specified page 5. Server sends file 6. TCP connection released 7. Browser displays text 8. Browser fetches, displays images
- 44. File System-Based Middleware (1) • Transfer Models (a) upload/download model (b) remote access model (a) (b)
- 45. File System-Based Middleware (2) Naming Transparency (b) Clients have same view of file system (c) Alternatively, clients with different view
- 46. File System-Based Middleware (3) • Semantics of File sharing – (a) single processor gives sequential consistency – (b) distributed system may return obsolete value
- 47. File System-Based Middleware (4) • AFS – Andrew File System – workstations grouped into cells – note position of venus and vice Client's view
- 48. Shared Object-Based Middleware (1) • Main elements of CORBA based system – Common Object Request Broker Architecture
- 49. Shared Object-Based Middleware (2) • Scaling to large systems – replicated objects – flexibility • Globe – designed to scale to a billion users – a trillion objects around the world
- 50. Shared Object-Based Middleware (3) Globe structured object
- 51. Shared Object-Based Middleware (4) • A distributed shared object in Globe – can have its state copied on multiple computers at once
- 52. Shared Object-Based Middleware (5) Internal structure of a Globe object
- 53. Coordination-Based Middleware (1) • Linda – independent processes – communicate via abstract tuple space • Tuple – like a structure in C, record in Pascal 1. Operations: out, in, read, eval
- 54. Coordination-Based Middleware (2) Publish-Subscribe architecture
- 55. Coordination-Based Middleware (3) • Jini - based on Linda model – devices plugged into a network – offer, use services • Jini Methods 1. read 2. write 3. take 4. notify