Thinking About Lots of Things at Once without Getting Confused: Parallelism in Act 1
As advances in computer architecture and changing economics make feasible machines with large-scale parallelism, Artificial Intelligence will require new ways of thinking about computation that can exploit parallelism effectively. We present the actor model of computation as being appropriate...
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| Language: | en_US |
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2004
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| Online Access: | http://hdl.handle.net/1721.1/6351 |
| _version_ | 1826213794298200064 |
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| author | Lieberman, Henry |
| author_facet | Lieberman, Henry |
| author_sort | Lieberman, Henry |
| collection | MIT |
| description | As advances in computer architecture and changing economics make feasible machines with large-scale parallelism, Artificial Intelligence will require new ways of thinking about computation that can exploit parallelism effectively. We present the actor model of computation as being appropriate for parallel systems, since it organizes knowledge as active objects acting independently, and communicating by message passing. We describe the parallel constructs in our experimental actor interpreter Act 1. Futures create concurrency, by dynamically allocating processing resources much as Lisp dynamically allocates passive storage. Serializers restrict concurrency by constraining the order in which events take place, and have changeable local state. Using the actor model allows parallelism and synchronization to be implemented transparently, so that parallel or synchronized resources can be used as easily as their serial counterparts. |
| first_indexed | 2024-09-23T15:54:38Z |
| id | mit-1721.1/6351 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:54:38Z |
| publishDate | 2004 |
| record_format | dspace |
| spelling | mit-1721.1/63512019-04-10T18:32:45Z Thinking About Lots of Things at Once without Getting Confused: Parallelism in Act 1 Lieberman, Henry As advances in computer architecture and changing economics make feasible machines with large-scale parallelism, Artificial Intelligence will require new ways of thinking about computation that can exploit parallelism effectively. We present the actor model of computation as being appropriate for parallel systems, since it organizes knowledge as active objects acting independently, and communicating by message passing. We describe the parallel constructs in our experimental actor interpreter Act 1. Futures create concurrency, by dynamically allocating processing resources much as Lisp dynamically allocates passive storage. Serializers restrict concurrency by constraining the order in which events take place, and have changeable local state. Using the actor model allows parallelism and synchronization to be implemented transparently, so that parallel or synchronized resources can be used as easily as their serial counterparts. 2004-10-04T14:52:47Z 2004-10-04T14:52:47Z 1981-05-01 AIM-626 http://hdl.handle.net/1721.1/6351 en_US AIM-626 9335532 bytes 6589579 bytes application/postscript application/pdf application/postscript application/pdf |
| spellingShingle | Lieberman, Henry Thinking About Lots of Things at Once without Getting Confused: Parallelism in Act 1 |
| title | Thinking About Lots of Things at Once without Getting Confused: Parallelism in Act 1 |
| title_full | Thinking About Lots of Things at Once without Getting Confused: Parallelism in Act 1 |
| title_fullStr | Thinking About Lots of Things at Once without Getting Confused: Parallelism in Act 1 |
| title_full_unstemmed | Thinking About Lots of Things at Once without Getting Confused: Parallelism in Act 1 |
| title_short | Thinking About Lots of Things at Once without Getting Confused: Parallelism in Act 1 |
| title_sort | thinking about lots of things at once without getting confused parallelism in act 1 |
| url | http://hdl.handle.net/1721.1/6351 |
| work_keys_str_mv | AT liebermanhenry thinkingaboutlotsofthingsatoncewithoutgettingconfusedparallelisminact1 |