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![The Free Lunch is Over: A Fundamental Turn Toward Concurrency in Software Source: http://www.gotw.ca/publications/concurrency-ddj.htm “ The major processor manufacturers and architectures have run out of room with most of their traditional approaches to boosting CPU performance. Instead of driving clock speeds ands straight-line instruction throughput ever higher, they are instead turning en masse to hyperthreading and multicore architectures. […] And that puts us at a fundamental turning point in software development, at least for the next few years...” – Herb Sutter – March 2005](https://image.slidesharecdn.com/tuplespaces-090613163215-phpapp01/85/Concurrent-Programming-with-Ruby-and-Tuple-Spaces-2-320.jpg)
![The Free Lunch is Over: A Fundamental Turn Toward Concurrency in Software Source: http://www.gotw.ca/publications/concurrency-ddj.htm “ The major processor manufacturers and architectures have run out of room with most of their traditional approaches to boosting CPU performance. Instead of driving clock speeds ands straight-line instruction throughput ever higher, they are instead turning en masse to hyperthreading and multicore architectures. […] And that puts us at a fundamental turning point in software development, at least for the next few years...” – Herb Sutter – March 2005](https://image.slidesharecdn.com/tuplespaces-090613163215-phpapp01/75/Concurrent-Programming-with-Ruby-and-Tuple-Spaces-2-2048.jpg)
Uploaded byluccastera
Concurrent Programming with Ruby and Tuple Spaces
The document discusses the challenges and methods of concurrent programming in Ruby, detailing issues with Ruby's threading model and advocating for multi-process approaches due to limitations in thread concurrency. It highlights the use of tuple spaces for inter-process communication, citing various existing libraries and solutions. The author emphasizes the advantages and disadvantages of each method, offering insights into the future of concurrency in Ruby applications.
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Concurrent Programming with Ruby and Tuple Spaces
- 1. Concurrent Programming withRuby and Tuple Spaces Luc Castera Founder / messagepub.com
- 2. The Free Lunchis Over: A Fundamental Turn Toward Concurrency in Software Source: http://www.gotw.ca/publications/concurrency-ddj.htm “ The major processor manufacturers and architectures have run out of room with most of their traditional approaches to boosting CPU performance. Instead of driving clock speeds ands straight-line instruction throughput ever higher, they are instead turning en masse to hyperthreading and multicore architectures. […] And that puts us at a fundamental turning point in software development, at least for the next few years...” – Herb Sutter – March 2005
- 3. Outline 1. Theproblem with Ruby Threads 2. Multiple Ruby Processes 3. Inter-process Communication with TupleSpaces
- 4. PART 1 TheProblem With Threads A closer look at the Ruby threading model
- 5. 3 Types ofThreading Models: 1 : N 1 : 1 M : N
- 6. 3 Types ofThreading Models: 1 : N 1 : 1 M : N Kernel Threads User-Space Threads
- 7. 1 : N-> Green Threads One kernel thread for N user threads aka “lightweight threads”
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- 18. Pros and ConsPros: Thread creation, execution, and cleanup are cheap
- 19. Lots of threadscan be created Cons: Not really parallel because kernel scheduler doesn't know about threads and can't schedule them across CPUs or take advantage of SMP
- 20. Blocking I/O operationcan block all green threads Example: C Extension
- 21. Example: mysql gem(solution: NeverBlock mysqlplus)
- 22.
- 23. 1 : 1-> Native Threads 1 kernel thread for each user thread
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- 25. Pros and ConsPros: Threads can execute on different CPUs (truly parallel)
- 26. Threads do notblock each other Cons: Setup Overhead
- 27. Low limit onnumber of threads
- 28. Linux kernel bugwith lots of threads
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- 31. Global Interpreter LockA Global Interpreter Lock (GIL) is a mutual exclusion lock held by a programming language interpreter thread to avoid sharing code that is not thread-safe with other threads. There is always one GIL for one interpreter process. Usage of a Global Interpreter Lock in a language effectively limits concurrency of a single interpreter process with multiple threads – there is no or very little increase in speed when running the process on a multiprocessor machine. Source: Wikipedia
- 32. A person (maleor female) who intentionally or unintentionally stops the progress of two others getting their game on.
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- 34. “ Concurrency isa myth in Ruby” – Ilya Grigorik
- 35. Unless you are using JRuby.
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- 37. A note onFibers Ruby 1.9 introduces fibers.
- 38. Fibers are greenthreads, but scheduling must be done by the programmer and not the VM.
- 39. Faster and cheaperthen native threads.
- 40. Implemented for Ruby1.8 by Aman Gupta.
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- 44. M : N-> Hybrid Model M kernel threads for N user threads “ best of both worlds”
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- 46. Pros and ConsPros: Take advantage of multiple CPUs
- 47. Not all threadsare blocked by blocking system calls
- 48. Cheap creation, execution,and cleanup Cons: Need scheduler in userland and kernel to work with each other
- 49. Green threads doingblocking I/O operations will block all other green threads sharing same kernel thread
- 50. Difficult to write,maintain, and debug code
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- 52. “ Writing multi-threadedcode is really, really hard. And it is hard because of Shared Memory.” – Jim Weirich The Other Problem with Threads http://rubyconf2008.confreaks.com/what-all-rubyist-should-know-about-threads.html
- 53. Multi-Threaded Code isHard + Concurrency is a myth = FAIL!
- 54. Stop thinking inthreads Design your application to use multiple processes
- 55. PART 2 MultipleRuby Processes
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- 57. Pros and ConsPros: No longer sharing memory
- 58. Take advantage ofmultiple CPUs (Performance)
- 59. Not all threadsare blocked by blocking system calls.
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- 61. Fault-Tolerance Cons: Processcreation, execution and cleanup is expensive
- 62. Uses a lotof memory (loading Ruby VM for every process)
- 63. Need a wayfor processes to communicate!
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- 65. but we willfocus on...
- 66. How do theprocesses communicate?
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- 76. Rails + Mongrel/ThinCluster of application servers (Mongrel, Thin...)
- 77. Communication between processesis done via the database.
- 78. Nanite A self-assemblingfabric of Ruby daemons
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- 81. Revactor Uses theactor model
- 82. Actors are kindalike threads, with messaging baked-in.
- 83. Each Actor hasa mailbox.
- 84. It's like codingerlang in Ruby.
- 85. Messages are passedbetween actors using TCP sockets.
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- 88. “ Erlang providesa sledgehammer for the problems of concurrent programming. But, sometimes you don't need a sledgehammer... just a flyswatter will do.” – Tony Arcieri
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- 90. Journeta Journeta is a dirt simple library for peer discovery and message passing between Ruby applications on a LAN
- 91. Uses UDP Socketsfor IPC
- 92. “ Uses thefucked up Ruby socket API” -> from their RDOC Demo(?)
- 93. PART 3 TupleSpacesI nterprocess Communication with TupleSpaces
- 94. A tuple spaceprovides a repository of tuples that can be accessed concurrently.
- 95. [:add, 1, 2][:result, 79] [:add, 60, 5] [:token] [:search, “linda”] [:where_is, :waldo [:subtract, 10, 2] [:save, 7864] The Blackboard Metaphor
- 96. [:add, 1, 2][:result, 79] [:add, 60, 5] [:token] [:search, “linda”] [:where_is, :waldo [:subtract, 10, 2] [:save, 7864] The Blackboard Metaphor [:add, nil, nil]
- 97. [:add, 1, 2][:result, 79] [:add, 60, 5] [:token] [:search, “linda”] [:where_is, :waldo [:subtract, 10, 2] [:save, 7864] The Blackboard Metaphor [nil]
- 98. [:add, 1, 2][:result, 79] [:add, 60, 5] [:token] [:search, “linda”] [:where_is, :waldo [:subtract, 10, 2] [:save, 7864] The Blackboard Metaphor [:where_is, :waldo]
- 99. About Tuple SpacesFirst implementation was Linda.
- 100. Linda was developedby David Gelernter and Nicholas Carriero at Yale University.
- 101. Implementations exists formost languages.
- 102. The Ruby implementationis Rinda.
- 103. Rinda is abuilt-in library, so no need to install.
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- 113. notify Reads tuple,but does not remove it. Blocking, by default, but takes an additional timeout argument.
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- 118. notify Returns alltuples matching tuple. Does not remove the found tuples.
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- 123. notify Adds TupleTakes an optional timeout parameter
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- 128. notify Atomic Read+ Delete Blocking, by default, but takes an additional timeout argument.
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- 133. notify Registers fornotifications of events: Write
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- 136. Key Features Spacesare shared Space handles details of concurrent access Spaces are persistent If agent process dies, data is still in space
- 137. However, if spaceprocess dies, data is lost (?) Spaces are associative Associative lookups rather than memory location or identifier Spaces are transactionally secure Atomic Operations Spaces allow us to exchange executable content
- 138. A Rinda tuplecan be an array or a hash
- 139. A Rinda tuplecan be an array or a hash ( But let's stick with the array, I like that better! )
- 140. Start a TupleSpace on port 1234
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- 150. This is alsoa TupleSpace
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- 152. Rinda is notpersistent... If it crashes while you have tuples in the space, you lose them all.
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- 154. Introducing Blackboard TupleSpaceimplementation on top of Redis -> Persistent Redis is a really fast key-value database. Like memcached but data is not volatile. Same API -> Plug & Play
- 155. For now, onlysupports: take, read, and write
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- 157. Server Just startthe redis-server: $ redis-server
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- 161. Blackboard: Future Movefrom Redis to a custom based Erlang blackboard implementation.
- 162. I would likethat Erlang implementation to be easily used from other programming languages also.
- 163. So it's reallytwo projects: Blackboard in erlang
- 164. Ruby-library to talkto blackboard in erlang
- 165. Thank you! LucCastera Founder / messagepub.com
- 166. Questions?Feedback? [email_address] www.speakerrate.comLuc Castera Founder / messagepub.com
- 167. Resources / ReferencesPart 1: Threading Models http://timetobleed.com/threading-models-so-many-different-ways-to-get-stuff-done/
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- 178. Resources / ReferencesPart 2: Multiple Processes http://github.com/ezmobius/nanite
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- 185. Resources / ReferencesPart 3: TupleSpaces http://c2.com/cgi/wiki?TupleSpace
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- 191. JavaSpaces Principles, Patterns,and Practice – Freeman, Hupfer, et. al.
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- 193. Things I wishI had time to spend on MPI and Ruby-MPI http://github.com/abedra/mpi-ruby/tree/master Ruby forkoff: http://tinyurl.com/forkoff