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Author: William A. Stein
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= SEP 2: Parallelization Plans For SAGE =
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This is a SAGE enhancement proposal.
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AUTHOR: William Stein
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COPYRIGHT: GNU Free Documentation License, 2007.
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The core SAGE library is a collection of Python and sagex files.
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== Basic Principles ==
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Many of these are motivated by my (Stein's) perspective as the '''maintainer''' and integrated of SAGE, and recruiter of new developers...
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1. Parallel methods should always be viewed as a means to an end -- speedups. Never parallelize any computation except to speed up a calculation beyond what can be done using sequential techniques.
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2. Parallel methods should never completely replace sequential implementations. Parallel algorithms are often very complicated to understand and test, so we need to at a ''minimum'' have a randomized test function that compares with that output of purely sequential code.
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3. Do not write insanely complicated parallel code that nobody can understand or maintain. Because SAGE is an open source system that is widely developed, it is ''crucial'' that it be readable.
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4. It is *crucial* that implementation of parallel methods in SAGE have the following properties:
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* It can be done incrementally. One must be able to start with almost any specific operation or algorithm in SAGE and make a parallel version without having to drastically change code all over SAGE. Any proposed solutions that violate this fail our needs.
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* It doesn't depend on any libraries or tools that are not open source and free, and all dependencies must work on the SAGE target platforms: Linux, OS X, Windows, (and soon Solaris).
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* For any core tools that are needed must be made part of SAGE.
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== Architecture ==
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There are three levels to consider.
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=== 1. Low -- shared memory (mostly multicore desktop/laptop) ===
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Proposed tool: pthread
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Justification:
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* pthread is available on all target platforms and is well supported
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* mature
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* with some thought I think we can make it usable from sagex
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Design issues:
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* Have a global variable nthreads
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Alternative tool: multiple processes and a shared memory segment
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* via UPC -- heavy and hard to build (??) maybe not right for us, because it's mainly for rather uniform computations.
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* via shared pages -- might not be fast enough.
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=== 2. Middle -- homogeneous trusted cluster ===
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Proposed tool: ipython1 (with mpi)
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Justification:
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* This is the hardware that the ipython developers use.
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* It's written in Python, well tested, and will be included in SAGE anyways.
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=== 3. High -- heterogenous task farm (both trusted and untrusted) ===
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Proposed tool: dsage
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Justification:
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* Written in Python to address specific problems we have.
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