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#12 | |
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Bamboozled!
"πΊππ·π·π"
May 2003
Down not across
10,753 Posts |
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Paul |
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#13 |
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Jan 2004
7·19 Posts |
i'd like to know how is going the end of 811, how is the estimated time remaining to fully complete that project.
thanks. |
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#14 | |
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Jun 2003
The Texas Hill Country
32×112 Posts |
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#15 | |
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Banned
"Luigi"
Aug 2002
Team Italia
113178 Posts |
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Would it be time-consuming as well to explain how the matrix is built up? Luigi |
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#16 |
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Jan 2004
7×19 Posts |
i know Wacky and Paul are pretty busy at this time, but like ET_, i'd like to know more details on how the huge matrix is build and wanna know more details about it.
Thanks. |
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#17 | |
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Nov 2003
22×5×373 Posts |
Quote:
Relations are collected of the form II p_i ^a_i * B1 * B2 = phi(II P_i^b_i * B3 * B4) mod N where p_i and P_i are primes in the factor bases and B1, B2, B3, B4 are the large primes. The B's lie outside the factor bases and some/all of them might equal 1. To find a square we must find a set of these relations which, when multiplied together result in every prime in the product having an even exponent. Thus, if a value of B appears only ONCE it can never be part of a square. Before the matrix is constructed, the data is filtered. All relations which have a value of B that appears only once are discarded. Then pairs of relations having the same B values are combined together. Furthermore if B appears (say) 3 times, we can combine these 3 relations into two pairs. etc. This filtering can be done in several ways. I have code that uses intelligent Gaussian elimination to combine the relations with large primes. But it is old, flaky, and written in Fortran. The newest CWI filter code uses graph clique algorithms to combine the relations with matching large primes. The matrix is then formed by taking the combined relations, reducing the exponents mod 2 and inserting them as columns into a large bit matrix. The size of the matrix comes from two sources: the factor base primes and the combined large primes. The time to solve the matrix is proportional to N^2 d where N is the number of columns and d is the average number of bits that are lit in each column. Note that d/N is *very* small. Typically d might be about 120 while Paul estimates N ~ 10M for M811. Note that part of the objective of the filtering process is to reduce N while keeping the matrix sparse. Combining relations together reduces N, but increases d. Hope this helps. Bob |
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