In this paper, we have used Compute Unified Device Architecture (CUDA) GPU to accelerate pairwise sequence alignment using the Smith-Waterman (SW) algorithm. Smith-Waterman(SW) is by far the best algorithm for its accuracy in similarity scoring.But the executing time of this algorithm is too long in sequence alignment.So we describe a multi-threaded parallel design and implementation of the Smith-Waterman (SW) on CUDA to reduce execution time.And according the architecure of CUDA,we have divided the computation of a whole pairwise sequence alignment scoring matrix into multiple sub-matrices,using 32 threads to process on submatrice,more over we optimized memory distribution scheme, and used reduction to find the maximum element of the alignment scoring matrix.We experiment the algorimthm on GeForce 9600 GT,connet to Windows xp 64-bit system.The results show this mplementation achieves more better performance than the other parallel implementation on the Graphics Processing Unit.
Active storage can largely reduce the network traffic and application execution time. In this paper, we present the design and implementation of an active storage architecture called Oasa for object-based storage system. Compared with previous work, Oasa has the following features.(1) It provides a flexible and efficient way for user to process data. User functions can process data of one user object or multiple objects at a time. (2) Oasa supports multiple patterns of user functions: both the input and output of the functions can a) come from network or disk or b) go to network or disk. (3) It keeps compatible with the current T10 OSD standard and requires little extra modification to execute user functions. Using the extended OSD commands, user can conveniently create, delete, associate and execute user functions with user objects. We also evaluate the performance of Oasa by running a typical application-data selection. It is a representative data analysis application widely used in solving real problems. Experimental results show that when the proposed active storage functions are enabled for object-based storage system, the client can obtain upto 61.9% reduction of application execution time.
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