this memory core, five random-memory locations are readable in a single clock cycle. So performing 35 concurrent memory operations requires seven parallel memory cores, each with one-seventh of the required array size, as Figure 5b illustrates. Because the basic Bloom filter allows any hash function to map to any bit in the vector, it is possible that for some member, more than five hash functions map to the same memory segment, thereby exceeding the lookup capacity of this memory core. We can solve this problem by restricting the range of each hash function to a given memory, preventing memory contention

Current multicore computers differ in many hardware characteristics. Software developers thus hand-tune their parallel programs for a specific platform to achieve the best performance; this is tedious and leads to non-portable code. Although the software architecture also requires adaptation to achieve best performance, it is rarely modified because of the additional implementation effort. The Tunable Architectures approach proposed in this paper automates the architecture adaptation of parallel programs and uses an auto-tuner to find the best-performing software architecture for a particular machine. We introduce a new architecture description language based on parallel patterns and a framework to express architecture variants in a generic way. Several case studies demonstrate significant performance improvements due to architecture tuning and show the applicability of our approach to industrial applications. Software developers are exposed to less parallel programming complexity, thus making the approach attractive for experts as well as inexperienced parallel programmers.

We propose a new optimization paradigm for solving intractable combinatorial problems. The technique, named Probabilistic Constructive (PC), combines the advantages of both constructive and probabilistic algorithms. The constructive aspect provides relatively short runtime and makes the technique amenable for the inclusion of insights through heuristic rules. The probabilistic nature facilitates a flexible trade-off between runtime and the quality of solution. In addition to presenting the generic technique, we apply it to the Maximal Independent Set problem. Extensive experimentation indicates that the new approach provides very attractive trade-offs between the quality of the solution and runtime, often outperforming the best previously published approaches. 1.

We study the optimal distance ` opt in random networks in the presence of disorder implemented by assigning random weights to the links. The optimal distance between two nodes is the length of the path for which the sum of weights along the path (\cost") is a minimum. We study the case of strong disorder for which the distribution of weights is so broad that its sum along any path is dominated by the largest link weight in the path. We nd that in random graphs, ` opt scales as N , where N is the number of nodes in the network. Thus, ` opt increases dramatically compared to the known small world result for the minimum distance `, which scales as log N . We also nd the functional form fro the probability distribution P (l opt ) of optimal paths. In addition we show how the problem of strong disorder on a random network can be mapped onto a percolation problem on the Cayley tree and using this mapping, obtain the probability distribution of the maximal weight on the optimal path.

Abstract: We propose a dynamic programming method to design efficient algorithms to analyze the genetic variation of gene of interest from different isolates, to search for the pattern and rule of changes in their DNA/protein sequences. In many cases we can achieve linear time (O(n)) time bound for the worst case time complexity, instead of the cubic time (O(n 3)) for a brute-force approach, where n is the length of the sequence. We apply our algorithms to the analysis of N-linked glycosylation sites of all published gp120 variable regions (V1 to V5) of the envelope glycoproteins of HIV-1 virus and find that there is a strong positive correlation between the length of the region and the number of glycosylation sites in the V1 and V4 loops. Key-Words: bioinformatics, dynamic programming, protein sequences, HIV virus, envelope glycoprotein. 1.

A multi-user detector with scalable complexity that achieves the maximum likelihood (ML) solution for two users and gives good sub-optimal performance for a higher number of users is proposed. The key idea is to construct a look-up table based on the geometric structure of the signal constellation, and then perform fast decoding based on the lookup table. The proposed detector is near-far resistant and its performance is consistently better than existing sub-optimal detectors when the number of users is greater than the number of dimensions. The robustness of the detector against noise can be controlled at the expense of higher complexity. 1.

In this paper, we introduce the Routing of Multi-rate Traffic (RMT) problem that arises in current backbone networks required to carry the new 40Gb/s traffic streams. The RMT problem is informally defined as the process of finding the best routing which maximizes the total bandwidth carried in the network, for a set of sessions, within a given TDM equipment budget. We propose a two-phase iterative optimization scheme (two-phase RMT). This scheme first obtains a basis solution used in routing 40Gb/s traffic only on OC-768 capable links without the use of TDM equipment. In the second phase, an iterative routing, re-routing, and resource allocation step is used to optimize the total bandwidth carried in the network while allowing 40Gb/s traffic to be routed on OC-768 incapable links by the proper installation of TDM multiplexors and demultiplexers at some strategic locations in the network. Numerical results demonstrate the performance of the proposed approach on a mesh-type heterogeneous topology.