Hashing is critical for high performance computer architecture. Hashing is used extensively in hardware applications, such as page tables, for address translation. Bit extraction and exclusive ORing hashing "methods" are two commonly used hashing functions for hardware applications. There is no study of the performance of these functions and no mention anywhere of the practical performance of the hashing functions in comparison with the theoretical performance prediction of hashing schemes. In this paper, we show that, by choosing hashing functions at random from a particular class, called H/sub 3/, of hashing functions, the analytical performance of hashing can be achieved in practice on real-life data. Our results about the expected worst case performance of hashing are of special significance, as they provide evidence for earlier theoretical predictions.
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机译：哈希对于高性能计算机体系结构至关重要。哈希在硬件应用程序（例如页表）中广泛用于地址转换。位提取和异或ORing哈希“方法”是硬件应用程序中两个常用的哈希函数。与散列方案的理论性能预测相比，没有研究这些函数的性能，也没有提及散列函数的实际性能。在本文中，我们表明，通过从特定类别的哈希函数H / sub 3 /中随机选择哈希函数，可以在实际数据中实际实现哈希的分析性能。我们有关哈希的最坏情况预期性能的结果具有特殊意义，因为它们为早期的理论预测提供了证据。
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