以多项式基数2索引的集合表示的数字的2的补加的快速乘法,存储为大规模并行计算的整数列表

Mark Stocks
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引用次数: 0

摘要

我们演示了一种基于以整数列表形式存储的多项式基数2索引集表示的数字的乘法方法。'多项式integerindex乘法'方法是一组在python代码中实现的算法。在一定的位范围内,我们证明了该方法比数论变换(NTT)和Karatsuba都快。也在python代码中实现,用于与多项式基数2integer方法进行比较。我们证明了可以将任何整数或实数表示为整数索引的列表,表示以2为基数的有限级数。整数索引表示的有限序列可以存储并分布在多个cpu / gpu上。我们证明了加法和乘法运算可以应用于索引整数表示上的两个补加运算,并且可以完全分布在给定的CPU / GPU架构上。我们演示了完全分布式的算术运算,使得“多项式整数索引乘法”方法克服了当前并行乘法方法的局限性。即,需要共享共同的核心内存和共同的磁盘,用于计算结果和中间结果。
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Fast multiplication by two's complement addition of numbers represented as a set of polynomial radix 2 indexes, stored as an integer list for massively parallel computation
We demonstrate a multiplication method based on numbers represented as set of polynomial radix 2 indices stored as an integer list. The 'polynomial integer index multiplication' method is a set of algorithms implemented in python code. We demonstrate the method to be faster than both the Number Theoretic Transform (NTT) and Karatsuba for multiplication within a certain bit range. Also implemented in python code for comparison purposes with the polynomial radix 2 integer method. We demonstrate that it is possible to express any integer or real number as a list of integer indices, representing a finite series in base two. The finite series of integer index representation of a number can then be stored and distributed across multiple CPUs / GPUs. We show that operations of addition and multiplication can be applied as two's complement additions operating on the index integer representations and can be fully distributed across a given CPU / GPU architecture. We demonstrate fully distributed arithmetic operations such that the 'polynomial integer index multiplication' method overcomes the current limitation of parallel multiplication methods. Ie, the need to share common core memory and common disk for the calculation of results and intermediate results.
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