Title : 
Multipattern string matching on a GPU
         
        
            Author : 
Zha, Xinyan ; Sahni, Sartaj
         
        
            Author_Institution : 
Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA
         
        
        
            fDate : 
June 28 2011-July 1 2011
         
        
        
        
            Abstract : 
We develop GPU adaptations of the Aho-Corasick string matching algorithm for the the case when all data reside initially in the GPU memory and the results are to be left in this memory. We consider several refinements to a base GPU implementation and measure the performance gain from each refinement. Experiments conducted on an NVIDIA Tesla GT200 GPU that has 240 cores running off of a Xeon 2.8GHz quad-core host CPU show that our Aho-Corasick GPU adaptation achieves a speedup between 8.5 and 9.5 relative to a single-thread CPU implementation and between 2.4 and 3.2 relative to the best multithreaded implementation.
         
        
            Keywords : 
computer graphic equipment; coprocessors; multi-threading; multiprocessing systems; string matching; Aho-Corasick string matching algorithm; GPU memory; NVIDIA Tesla GT200 GPU; Xeon 2.8GHz quad core host CPU; multipattern string matching; multithreaded implementation; single thread CPU implementation; Arrays; Bandwidth; Doped fiber amplifiers; Graphics processing unit; Instruction sets; Memory management; Registers; Aho-Corasick; CUDA; GPU; Multipattern string matching;
         
        
        
        
            Conference_Titel : 
Computers and Communications (ISCC), 2011 IEEE Symposium on
         
        
            Conference_Location : 
Kerkyra
         
        
        
            Print_ISBN : 
978-1-4577-0680-6
         
        
            Electronic_ISBN : 
1530-1346
         
        
        
            DOI : 
10.1109/ISCC.2011.5983790