One of the central issues in router performance is IP address lookup based on longest prefix matching. IP address lookup algorithms can be evaluated on a number of metrics-lookup time, update time, memory usage, and to a less important extent, the time to construct the data structure used to support lookups and updates. Many of the existing methods are geared toward optimizing a specific metric, and do not scale well with the ever expanding routing tables and the forthcoming IPv6 where the IP addresses are 128 bits long. In contrast, our effort is directed at simultaneously optimizing multiple metrics and provide solutions that scale to IPv6, with its longer addresses and much larger routing tables. In this paper, we present two IP address lookup schemes-Elevator-Stairs algorithm and logW-Elevators algorithm. For a routing table with N prefixes, The Elevator-Stairs algorithm uses optimal O(N) memory, and achieves better lookup and update times than other methods with similar memory requirements. The logW-Elevators algorithm gives O(logW) lookup time, where W is the length of an IP address, while improving upon update time and memory usage. Experimental results using the MAE-West router with 29 487 prefixes show that the Elevator-Stairs algorithm gives an average throughput of 15.7 Million lookups per second (Mlps) using 459KB of memory, and the logW-Elevators algorithm gives an average throughput of 21.41Mlps with a memory usage of 1259KB.

Current biological sequence comparison tools utilize full database searches to find approximate matches between a database and a query. A new approach to sequence comparisons can be performed by indexing the database using a novel indexing scheme. An indexed scheme can immediately eliminate highly mismatched sequences thereby improving performance and accuracy. iBlast is proposed as an indexed version of BLAST. In its initial implementation, iBlast uses a sequence-based index to catalog genomic databases in an NCR Teradata RDBMS. Several types of indexes and querying methods are explored to determine the most efficient solution utilizing the parallel nature of the Teradata system. Significant speedups were obtained and are explained in further detail in this paper. Future indexing methods based on prokaryotic and eukaryotic genome structures are also proposed.

IP address lookup algorithms can be evaluated on a number of metrics lookup time, update time, memory usage, and to a lesser extent, the time to construct the data structure used to support lookups and updates. Many of the existing methods are geared towards optimizing a specific metric, and hence do not scale well with the ever expanding routing tables and the forthcoming IPv6 with 128 bit long IP address. In contrast, our effort is directed at simultaneously optimizing multiple metrics and provide solutions that scale well to IPv6. In this paper, we present two IP address lookup schemes Elevator - Stairs algorithm and logW - Elevators algorithm. For a routing table with N prefixes, The Elevator - Stairs algorithm uses optimal O(N) memory, and achieves better lookup and update times than other methods with similar memory requirements. The logW - Elevators algorithm gives O(log W) lookup time, where W is the length of an IP address, while improving upon update time and memory usage. Experimental results using the MAE-West router with 29,487 prefixes show that the Elevator - Stairs algorithm gives an average throughput of 15.7 Million lookups per second (Mlps) using 459 KB of memory, and the logW - Elevators algorithm gives an average throughput of 21.41 Mlps with a memory usage of 1259 KB.

We present faster sequential and parallel algorithms for computing the solvent accessible surface area (ASA) of protein molecules. The ASA is computed by finding the exposed surface areas of the spheres obtained by increasing the van der Waals radii of the atoms with the van der Waals radius of the solvent. Using domain specific knowledge, we show that the number of sphere intersections is only O(n), where n is the number of atoms in the protein molecule. For computing sphere intersections, we present hash-based algorithms that run in O(n) expected sequential time and O(n/p) expected parallel time and sort-based algorithms that run in worst-case O(n log n) sequential time and O(n log n/p) parallel time. These are significant improvements over previously known algorithms which take O(n/sup 2/) time sequentially and O(n/sup 2//p) time in parallel. We present a Monte Carlo algorithm for computing the solvent accessible surface area. The basic idea is to generate points uniformly at random on the surface of spheres obtained by increasing the van der Waals radii of the atoms with the van der Waals radius of the solvent molecule and to test the points for accessibility. We also provide error bounds as a function of the sample size. Experimental verification of the algorithms is carried out using an IBM SP-2.

The Fast Multipole Method (FMM) is a robust technique for the rapid evaluation of the combined effect of pairwise interactions of n data sources. Parallel computation of the FMM is considered a challenging problem due to the dependence of the computation on the distribution of the data sources, usually resulting in dynamic data decomposition and load balancing problems. In this paper, we present the first provably efficient and distribution-independent parallel algorithm for the FMM on distributed memory parallel computers. Our algorithm does not require any dynamic data decomposition or load balancing step. We present our algorithm in terms of a few basic and well understood primitive operations such as sorting and parallel prefix.