A Domain Decomposition Strategy for Alignment of Multiple Biological Sequences on Multiprocessor Platforms

Multiple Sequences Alignment (MSA) of biological sequences is a fundamental problem in computational biology due to its critical significance in wide ranging applications including haplotype reconstruction, sequence homology, phylogenetic analysis, and prediction of evolutionary origins. The MSA problem is considered NP-hard and known heuristics for the problem do not scale well with increasing number of sequences. On the other hand, with the advent of new breed of fast sequencing techniques it is now possible to generate thousands of sequences very quickly. For rapid sequence analysis, it is therefore desirable to develop fast MSA algorithms that scale well with the increase in the dataset size. In this paper, we present a novel domain decomposition based technique to solve the MSA problem on multiprocessing platforms. The domain decomposition based technique, in addition to yielding better quality, gives enormous advantage in terms of execution time and memory requirements. The proposed strategy allows to decrease the time complexity of any known heuristic of O(N)^x complexity by a factor of O(1/p)^x, where N is the number of sequences, x depends on the underlying heuristic approach, and p is the number of processing nodes. In particular, we propose a highly scalable algorithm, Sample-Align-D, for aligning biological sequences using Muscle system as the underlying heuristic. The proposed algorithm has been implemented on a cluster of workstations using MPI library. Experimental results for different problem sizes are analyzed in terms of quality of alignment, execution time and speed-up.Comment: 36 pages, 17 figures, Accepted manuscript in Journal of Parallel and Distributed Computing(JPDC

Protocol Architecture for Multimedia Applications over ATM Networks

At the data-link layer, ATM offers a number of features, such as high-bandwidth and per-session quality of service (QoS) guarantees, making it particularly attractive to multimedia applications. Unfortunately, many of these features are not visible to applications because of the inadequacies of existing higher-level protocol architectures. Although there is considerable effort underway to tune these protocols for ATM networks, we believe that a new ATM specific protocol stack is essential to effectively exploit all the benefits of ATM. In this paper we describe the semantics of such a protocol stack, and discuss its advantages over traditional protocol architectures from the perspective of multimedia applications. The performance impact of the new protocol architecture is experimentally demonstrated on a video conferencing testbed built around IBM RS/6000s equipped with prototype hardware for video/audio processing, and connected via ATM links. 1 Introduction At the data-link layer,..

Local Load Balancing for Data-parallel Branch-and-bound

INTRODUCTION Branch-and-bound (B&B) is a well-known and general combinatorial optimisation technique that is used especially for NP-hard problems where no special purpose algorithm is known. Because of the high problem complexity, parallel implementations are required for speeding up the computations. Algorithms with high and stable efficiency, i.e., utilisation of the processing elements (PEs), are desired. This can be achieved by load balancing techniques that intervene if the PE utilisation worsens. We use a common version of the sequential B&B formulation as a basis for the parallel algorithm from [8] (see Figure 1). The initialisation is hidden in a function call and is discussed in detail in [1]. The main data structure, the OPEN set, stores single nodes of the search tree. Any search strategy (best-first, depth-first, etc.) can be applied. The dataparallel B&B works quite similarly to the serial algorithm, except that each PE has its own OPEN set. All PEs execute the m