1 / 51

Distributed Operating Systems CS551

Distributed Operating Systems CS551. Colorado State University at Lockheed-Martin Lecture 4 -- Spring 2001. CS551: Lecture 4. Topics Memory Management Simple Shared Distributed Migration Concurrency Control Mutex and Critical Regions Semaphores Monitors.

onan
Download Presentation

Distributed Operating Systems CS551

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Distributed Operating SystemsCS551 Colorado State University at Lockheed-Martin Lecture 4 -- Spring 2001

  2. CS551: Lecture 4 • Topics • Memory Management • Simple • Shared • Distributed • Migration • Concurrency Control • Mutex and Critical Regions • Semaphores • Monitors CS-551, Lecture 4

  3. Centralized Memory Management • Review • Memory: cache, RAM, auxiliary • Virtual Memory • Pages and Segments • Internal/External Fragmentation • Page Replacement Algorithm • Page Faults => Thrashing • FIFO, NRU, LRU • Second Chance; Lazy (Dirty Pages) CS-551, Lecture 4

  4. Figure 4.1  Fragmentation in Page-Based Memory versus a Segment-Based Memory. (Galli, p.83) CS-551, Lecture 4

  5. Figure 4.2  Algorithms for Choosing Segment Location. (Galli,p.84) CS-551, Lecture 4

  6. Simple Memory Model • Used in parallel NUMA systems • Access times equal for all processors • Too many processors • => thrashing • => need for lots of memory • High performance parallel computers • May not use cache -- to avoid overhead • May not use virtual memory CS-551, Lecture 4

  7. Shared Memory Model • Shared memory can be a means of interprocess communication • Virtual memory with multiple physical memories, caches, and secondary storage • Easy to partition data for parallel processing • Easy migration for load balancing • Example systems: • Amoeba: shared segments on same system • Unix System V: sys/shm.h CS-551, Lecture 4

  8. Shared Memory via Bus P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 Shared Memory CS-551, Lecture 4

  9. Shared Memory Disadvantages • All processors read/write common memory • Requires concurrency control • Processors may be linked by a bus • Too much memory activity may cause bus contention • Bus can be a bottleneck • Each processor may have own cache • => cache coherency (consistency) problems • Snoopy (snooping) cache is a solution CS-551, Lecture 4

  10. Bused Shared Memory w/Caches P1 P2 P3 P4 P5 cache cache cache cache cache cache cache cache cache cache P6 P7 P8 P9 P10 Shared Memory CS-551, Lecture 4

  11. Shared Memory Performance • Try to overlap communication and computation • Try to prefetch data from memory • Try to migrate processes to processors that hold needed data in local memory • Page scanner • Bused shared memory does not scale well • More processors => bus contention • Faster processors => bus contention CS-551, Lecture 4

  12. Figure 4.3  Snoopy Cache.(Galli,p.89) CS-551, Lecture 4

  13. Cache Coherency (Consistency) • Want local caches to have consistent data • If two processor caches contain same data, the data should have the same value • If not, caches are not coherent • But what if one/both processors change the data value? • Mark modified cache value as dirty • Snoopy cache picks up new value as it is written to memory CS-551, Lecture 4

  14. Cache Consistency Protocols • Write-through protocol • Write-back protocol • Write-once protocol • Cache block invalid, dirty, or clean • Cache ownership • All caches snoop • Protocol part of MMU • Performs within a memory cycle CS-551, Lecture 4

  15. Write-through protocol Read-miss • Fetch data from memory to cache Read hit • Fetch data from local cache Write miss • Update data in memory and store in cache Write hit • Update memory and cache • Other local processors invalidate cache entry CS-551, Lecture 4

  16. Distributed Shared Memory • NUMA • Global address space • All memories together form one global memory • True multiprocessors • Maintains directory service • NORMA • Specialized message-passing network • Example: workstations on a LAN CS-551, Lecture 4

  17. Distributed Shared Memory P1 P2 P3 P4 P5 memory memory memory memory memory memory memory memory memory memory memory P6 P7 P8 P9 P10 P11 CS-551, Lecture 4

  18. How to distribute shared data? • How to distribute shared data? • How many readers and writers are allowed for a given set of data? • Two approaches • Replication • Data copied to different processors that need it • Migration • Data moved to different processors that need it CS-551, Lecture 4

  19. Single Reader / Single Writer • No concurrent use of shared data • Data use may be a bottleneck • Static CS-551, Lecture 4

  20. Multiple Reader /Single Writer • Readers may have a invalid copy after the writer writes a new value • Protocol must have an invalidation method • Copy set: list of processors that have a copy of a memory location • Implementation • centralized, distributed, or combination CS-551, Lecture 4

  21. Centralized MR/SW • One server • Processes all requests • Maintains all data and data locations • Increases traffic near server • Potential bottleneck • Server must perform more work than others • Potential bottleneck CS-551, Lecture 4

  22. Figure 4.4  Centralized Server for Multiple Reader/Single Writer DSM.(Galli,p.92) CS-551, Lecture 4

  23. Partially distributed centralization of MR/SW • Distribution of data static • One server receives all requests • Requests sent to processor with desired data • Handles requests • Notifies readers of invalid data CS-551, Lecture 4

  24. Figure 4.5  Partially Distributed Invalidation for Multiple Reader/Single Writer DSM. (Galli, p.92) [Read X as C below] CS-551, Lecture 4

  25. Dynamic distributed MR/SW • Data may move to different processor • Send broadcast message for all requests in order to reach current owner of data • Increases number of messages in system • More overhead • More work for entire system CS-551, Lecture 4

  26. Ffigure 4.6  Dynamic Distributed Multiple Reader/Single Writer DSM.(Galli, P.93) CS-551, Lecture 4

  27. A Static Distributed Method • Data is distributed statically • Data owner • Handles all requests • Notifies readers when their data copy invalid • All processors know where all data is located, since it is statically located CS-551, Lecture 4

  28. Figure 4.7  Dynamic Data Allocation for Multiple Reader/Single Writer DSM.(Galli,p.96) CS-551, Lecture 4

  29. Multiple Readers/Multiple Writers • Complex algorithms • Use sequencers • Time read • Time written • May be centralized or distributed CS-551, Lecture 4

  30. DSM Performance Issues • Thrashing (in a DSM): “when multiple locations desire to modify a common data set” (Galli) • False sharing: Two or more processors fighting to write to the same page, but not the same data • One solution: temporarily freeze a page so one processor can get some work done on it • Another: proper block size (= page size?) CS-551, Lecture 4

  31. More DSM Performance Issues • Data location (compiler?) • Data access patterns • Synchronization • Real-time systems issue? • Implementation: • Hardware? • Software? CS-551, Lecture 4

  32. Mach Operating System • Uses virtual memory, distributed shared memory • Mach kernel supports memory objects • “a contiguous repository of data, indexed by byte, upon which various operations, such as read and write, can be performed. Memory objects act as a secondary storage …. Mach allows several primitives to map a virtual memory object into an address space of a task. …In Mach, every task has a separate address space.”(Singhal & Shivaratri, 1994) CS-551, Lecture 4

  33. Memory Migration • Time-consuming • Moving virtual memory from one processor to another • When? • How much? CS-551, Lecture 4

  34. MM: Stop and Copy • Least efficient method • Simple • Halt process execution (freeze time) while moving entire process address space and data to new location • Unacceptable to real-time and interactive systems CS-551, Lecture 4

  35. Figure 4.8  Stop-and-Copy Memory Migration. (Galli,p.99) CS-551, Lecture 4

  36. Concurrent Copy • Process continues execution while being copied to new location • Some migrated pages may become dirty • Send over more recent versions of pages • At some point, stop execution and migrate remaining data • Algorithms include dirty page ratio and/or time criteria to decide when to stop • Wastes time and space CS-551, Lecture 4

  37. Figure 4.9  Concurrent-Copy Memory Migration. (Galli,p.99) CS-551, Lecture 4

  38. Copy on Reference • Process stops • All process state information is moved • Process resumes at new location • Other process pages are moved only when accessed by process • Alternate may have virtual memory pages transferred to file server, then moved as needed to new process location CS-551, Lecture 4

  39. Figure 4.10Copy-on-Reference Memory Migration. (Galli,p.100) CS-551, Lecture 4

  40. Table 4.1 Memory Management Choices Available for Advanced Systems. (Galli,p.101) CS-551, Lecture 4

  41. Table 4.2 Performance Choices for Memory Management.(Galli,p.101) CS-551, Lecture 4

  42. Concurrency Control (Chapter 5) • Topics • Mutual Exclusion and Critical Regions • Semaphores • Monitors • Locks • Software Lock Control • Token-Passing Mutual Exclusion • Deadlocks CS-551, Lecture 4

  43. Critical Region • “the portion of code or program accessing a shared resource” • Must prevent concurrent execution by more than one process at a time • Mutex: mutual exclusion CS-551, Lecture 4

  44. Figure 5.1  Critical Regions Protecting a Shared Variable.(Galli,p.106) CS-551, Lecture 4

  45. Mutual Exclusion • Three-point test (Galli) • Solution must ensure that two processes do not enter critical regions at same time • Solution must prevent interference from processes not attempting to enter their critical regions • Solution must prevent starvation CS-551, Lecture 4

  46. Critical Section Solutions • Recall: Silberschatz & Galvin • A solution to the critical section problem must show that • mutual exclusion is preserved • progress requirement is satisfied • bounded-waiting requirement is met CS-551, Lecture 4

  47. Figure 5.2  Example Utilizing Semaphores. (Galli,p.109) CS-551, Lecture 4

  48. Figure 5.3  Atomic Swap. (Galli,p.114) CS-551, Lecture 4

  49. Figure 5.4  Centralized Lock Manager. (Galli,p.116) CS-551, Lecture 4

  50. Figure 5.5  Resource Allocation Graph. (Galli,p.120) CS-551, Lecture 4

More Related