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» Modular Resultant Algorithm for Graphics Processors
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INTENSIVE
2009
IEEE
14 years 2 months ago
Accelerating K-Means on the Graphics Processor via CUDA
In this paper an optimized k-means implementation on the graphics processing unit (GPU) is presented. NVIDIA’s Compute Unified Device Architecture (CUDA), available from the G8...
Mario Zechner, Michael Granitzer
SIGMOD
2007
ACM
196views Database» more  SIGMOD 2007»
14 years 7 months ago
GPUQP: query co-processing using graphics processors
We present GPUQP, a relational query engine that employs both CPUs and GPUs (Graphics Processing Units) for in-memory query co-processing. GPUs are commodity processors traditiona...
Rui Fang, Bingsheng He, Mian Lu, Ke Yang, Naga K. ...
IPPS
2009
IEEE
14 years 2 months ago
Multi-dimensional characterization of temporal data mining on graphics processors
Through the algorthmic design patterns of data parallelism and task parallelism, the graphics processing unit (GPU) offers the potential to vastly accelerate discovery and innovat...
Jeremy S. Archuleta, Yong Cao, Thomas Scogland, Wu...
WWW
2008
ACM
14 years 8 months ago
Using graphics processors for high-performance IR query processing
Web search engines are facing formidable performance challenges due to data sizes and query loads. The major engines have to process tens of thousands of queries per second over t...
Shuai Ding, Jinru He, Hao Yan, Torsten Suel
CORR
2007
Springer
173views Education» more  CORR 2007»
13 years 7 months ago
Computing modular polynomials in quasi-linear time
We analyse and compare the complexity of several algorithms for computing modular polynomials. We show that an algorithm relying on floating point evaluation of modular functions...
Andreas Enge