Fast Probabilistic Techniques for Dynamic Parallel Addition Parallel Counting a
Fast Probabilistic Techniques for Dynamic Parallel Addition Parallel Counting a
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In our eReader you can find the full English version of the book. Read Fast Probabilistic Techniques for Dynamic Parallel Addition Parallel Counting a Online - link to read the book on full screen. Our eReader also allows you to upload and read Pdf, Txt, ePub and fb2 books. In the Mini eReder on the page below you can quickly view all pages of the book - Read Book Fast Probabilistic Techniques for Dynamic Parallel Addition Parallel Counting a
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En after the m rounds, we call L an m-algorithm for the processor identification problem. (We allow unrestricted local memory per processor. ) An obvious L (which would take 0(n) parallel time) is that consisting of n^i's with €i[j] = 0, jVi and €i(i)= 1 (IrsirSn). Erdos and Renyi [ER, 63] considered a very closely related problem, the "coin-weight" problem. Using their techniques, we show that the m needed is 9(n/logn) and that L is constructive (in fact, there is an easy probabilistic way to ...find L). Let us view L as an mX n matrix of O's and I's. Lemma 2 (see also [ER, 63] ). A matrix L, mXn, of O's and I's is an m- algorithm for the processor identification problem iff: For each pair c, c' of subsets of the set C of columns of L, such that c^^c', if we form the row- sums of the submatrices L(c) and L(c') (consisting of the selected columns) and denote by V^andV*^. The column-vectors, consisting of these row-sums, then ^c^^v Proof sketch: After m-rounds, each processor has a row-sum vector, V, of L.
What to read after Fast Probabilistic Techniques for Dynamic Parallel Addition Parallel Counting a?
You can find similar books in the "Read Also" column, or choose other free books by Paul G Spirakis to read onlineMoreLess
To quickly assess the difficulty of the text, read a short excerpt:
En after the m rounds, we call L an m-algorithm for the processor identification problem. (We allow unrestricted local memory per processor. ) An obvious L (which would take 0(n) parallel time) is that consisting of n^i's with €i[j] = 0, jVi and €i(i)= 1 (IrsirSn). Erdos and Renyi [ER, 63] considered a very closely related problem, the "coin-weight" problem. Using their techniques, we show that the m needed is 9(n/logn) and that L is constructive (in fact, there is an easy probabilistic way to ...find L). Let us view L as an mX n matrix of O's and I's. Lemma 2 (see also [ER, 63] ). A matrix L, mXn, of O's and I's is an m- algorithm for the processor identification problem iff: For each pair c, c' of subsets of the set C of columns of L, such that c^^c', if we form the row- sums of the submatrices L(c) and L(c') (consisting of the selected columns) and denote by V^andV*^. The column-vectors, consisting of these row-sums, then ^c^^v Proof sketch: After m-rounds, each processor has a row-sum vector, V, of L.
What to read after Fast Probabilistic Techniques for Dynamic Parallel Addition Parallel Counting a?
You can find similar books in the "Read Also" column, or choose other free books by Paul G Spirakis to read onlineMoreLess
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