distributed multi-threading in gnu-prolog
TRANSCRIPT
Distributed Multi-Threading in GNU PrologNuno Morgadinho, Salvador Abreu
{nm, spa}@di.uevora.pt
Departamento de Informática
Évora 2007
Slide ICLP ’07 CICLOPS
• Distributed - one or more computers communicating over a network
• Multi-Threading - more than one thread of execution
• Thread - a flow of execution
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Introduction
Slide ICLP ’07 CICLOPS
• Obtain results faster for problems where performance is critical
• The problem can be divided into smaller tasks which can be carried out simultaneously
• Parallelism
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Introduction
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• PM2 - a distributed multi-threading programming environment
• GNU Prolog - efficient native Prolog compiler
• Combination of both
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What We Present
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• GNU Prolog produces stand-alone executables
• The size of the executables is relatively small
• Doesn’t work with machine independent saved-states
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GNU Prolog and PM2: Why?
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• Established a model for connecting PM2 and GNU Prolog
• The approach doesn’t involve modifications to GNU Prolog neither to PM2
• Compatibility with GNU Prolog libraries is retained
Implementation
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Slide ICLP ’07 CICLOPS
• Tabard - new program that manages distributed instances of GNU Prolog engines
• pm2prolog - new library that allows the development of distributed multithreaded Prolog applications
Approach
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• Allow to execute computations remotely
• Manage the engines responsible for the computations
• Manage the communication involved between the several machines
• Based on distributed memory and explicit message-passing
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Functionality
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Example
:- initialization(init).:- include('pm2prolog').
% thread with rank 0init:- pm2_is_master, !, pm2_max_rank(MaxRank), start_prolog_workers(MaxRank), test_prolog_workers(MaxRank), read_test(MaxRank), stop_prolog_workers.
% thread != 0init:- worker_code.
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• Configuration that specifies the list of machines
• Each machine is mapped to one or more processing nodes or virtual processors (VPs)
Before Running
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• Binary is copied to all machines
• In VP0 (master) a gprolog engine is created
• In the other VPs (workers) a pthread in C is created and stands awaiting messages
Execution Model
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• In the master, now in the Prolog thread, a predicate is called to send a message to every worker
• The workers receive the message, initiate a gprolog engine and the thread stands awaiting more messages to come
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Execution Model
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• In the master, work is distributed throughout the workers through message-passing
• The workers receive tasks which they execute locally. As soon as they finish, they send their results back to the master
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Execution Model
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• The master assembles the work results by reading as many messages as the number of previously sent messages
• The master redistributes work again or orders the workers to finish their execution
• The workers terminate
• The master reiniciates the workers or terminates itself
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Execution Model
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...
READ WRITE
WRITE
Prolog ThreadC Thread Listener
RECEIVE SEND
Message Queue
write_message_queue()
Start_Prolog()
Stop_Prolog()
... ...
thread_send_message/2
thread_get_message/2
pm2_self/1
UNLOCK
LOCK
SOCKET
Inside a Virtual Processor
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Slide ICLP ’07 CICLOPS
• Several VPs per physical machine is possible
Prolog Proc
Node 1
VP 0
Prolog Proc
VP 1
...
Prolog Proc
VP 2
...
Node 2
Prolog Proc
VP 2
Node 3
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• ISO/IEC Draft Technical Report 13211-5:2007, Prolog Multi-Threading Support
• Extensions to take into consideration remote threads
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ISO Support
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• thread_create/2
• vid(Rank, ThreadID)
• Rank - VP identifier
• ThreadID - identifier of the thread inside
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PM2-Prolog Remote Threads
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Experimental Evaluation
0
25
50
75
100
2004 2005 2006 2007
Results obtained with 7x Intel(R) Pentium(R) 4 2.80 Mhz each, Hyperthreading enabled, 512 Mbytes each, Linux 2.4.19 kernel, 100 Mbits TCP/IP Ethernet network
Slide ICLP ’07 CICLOPS
• We presented a distributed multi-threading GNU Prolog system on top of PM2
• First results show that it can obtain substantial speedups, even for real-world
• Proved the approach to be technically possible and can be of use to other implementers
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Conclusions
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• Improving our proposal
• Extend the API with introspection and monitoring predicates
• Experiment with more programs and bigger configurations
• Build our own applications using this technology
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Further Work