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The GPU as an indirection engine for a fast information retrieval., and . Int. J. Electron. Bus., 3 (3/4): 316-327 (2005)New data-parallel language features for sparse matrix computations., , , and . IPPS, page 742-749. IEEE Computer Society, (1995)CUDA Achievements and GPU Challenges Ahead.. AMDO, volume 9756 of Lecture Notes in Computer Science, page 207-217. Springer, (2016)High Performance Computation of Moments for an Accurate Classification of Bone Tissue Images., and . HPCC, page 593-598. IEEE, (2011)High-performance signal processing on emerging many-core architectures using cuda., and . ICME, page 1825-1828. IEEE, (2009)Pathological Image Analysis Using the GPU: Stroma Classification for Neuroblastoma., , , , , and . BIBM, page 78-88. IEEE Computer Society, (2007)Dense and Sparse Matrix-Vector Multiplication on Maxwell GPUs with PyCUDA., , and . CARLA, volume 697 of Communications in Computer and Information Science, page 219-229. (2016)Compile and Run-Time Support for the Parallelization of Sparse Matrix Updating Algorithms., , and . J. Supercomput., 17 (3): 263-276 (2000)Parallel WZ factorization on mesh multiprocessors., , and . Microprocess. Microprogramming, 38 (1-5): 319-326 (1993)Energy-based tuning of convolutional neural networks on multi-GPUs., , , , and . Concurr. Comput. Pract. Exp., (2019)