Publication 1997 Issue No. 1 - January Abstract - Time-Optimal Domain-Specific Querying on Enhanced Meshes
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Time-Optimal Domain-Specific Querying on Enhanced Meshes
January 1997 (vol. 8 no. 1)
pp. 13-24
 ASCII Text x Venkatavasu Bokka, Himabindu Gurla, Stephan Olariu, James L. Schwing, Larry Wilson, "Time-Optimal Domain-Specific Querying on Enhanced Meshes," IEEE Transactions on Parallel and Distributed Systems, vol. 8, no. 1, pp. 13-24, January, 1997.
 BibTex x @article{ 10.1109/71.569651,author = {Venkatavasu Bokka and Himabindu Gurla and Stephan Olariu and James L. Schwing and Larry Wilson},title = {Time-Optimal Domain-Specific Querying on Enhanced Meshes},journal ={IEEE Transactions on Parallel and Distributed Systems},volume = {8},number = {1},issn = {1045-9219},year = {1997},pages = {13-24},doi = {http://doi.ieeecomputersociety.org/10.1109/71.569651},publisher = {IEEE Computer Society},address = {Los Alamitos, CA, USA},}
 RefWorks Procite/RefMan/Endnote x TY - JOURJO - IEEE Transactions on Parallel and Distributed SystemsTI - Time-Optimal Domain-Specific Querying on Enhanced MeshesIS - 1SN - 1045-9219SP13EP24EPD - 13-24A1 - Venkatavasu Bokka, A1 - Himabindu Gurla, A1 - Stephan Olariu, A1 - James L. Schwing, A1 - Larry Wilson, PY - 1997KW - SearchingKW - rankingKW - parallel algorithmsKW - time-optimal algorithmsKW - enhanced meshesKW - VLSIKW - database designKW - pattern recognitionKW - robotics.VL - 8JA - IEEE Transactions on Parallel and Distributed SystemsER -

Abstract—Query processing is a crucial component of various application domains including information retrieval, database design and management, pattern recognition, robotics, and VLSI. Many of these applications involve data stored in a matrix satisfying a number of properties. One property that occurs time and again specifies that the rows and the columns of the matrix are independently sorted. It is customary to refer to such a matrix as sorted. An instance of the Batched Searching and Ranking problem, (BSR, for short) involves a sorted matrix A of items from a totally ordered universe, along with a collection Q of queries. Q is an arbitrary mix of the following query types: For a search query qj, one is interested in an item of A that is closest to qj; for a rank query qj one is interested in the number of items of A that are strictly smaller than qj. The BSR problem asks for solving all queries in Q. In this work, we consider the BSR problem in the following context: The matrix A is pretiled, one item per processor, onto an enhanced mesh of size $\sqrt n\times \sqrt n$; the m queries are stored, one per processor, in the first ${{m \over {\sqrt n}}}$ columns of the platform. Our main contribution is twofold. First, we show that any algorithm that solves the BSR problem must take at least $\Omega ({\rm max\{log}n,\sqrt m\})$ time in the worst case. Second, we show that this time lower bound is tight on meshes of size $\sqrt n\times \sqrt n$ enhanced with multiple broadcasting, by exhibiting an algorithm solving the BSR problem in $\Theta ({\rm max\{log}\!\!n,\sqrt m\})$ time on such a platform.

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Index Terms:
Searching, ranking, parallel algorithms, time-optimal algorithms, enhanced meshes, VLSI, database design, pattern recognition, robotics.
Citation:
Venkatavasu Bokka, Himabindu Gurla, Stephan Olariu, James L. Schwing, Larry Wilson, "Time-Optimal Domain-Specific Querying on Enhanced Meshes," IEEE Transactions on Parallel and Distributed Systems, vol. 8, no. 1, pp. 13-24, Jan. 1997, doi:10.1109/71.569651