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Highly Optimized Code Generation for Stencil Codes with Computation Reuse for GPUs., , и . J. Comput. Sci. Technol., 31 (6): 1262-1274 (2016)GPURoofline: A Model for Guiding Performance Optimizations on GPUs., , , , , и . Euro-Par, том 7484 из Lecture Notes in Computer Science, стр. 920-932. Springer, (2012)An Insightful Program Performance Tuning Chain for GPU Computing., , , и . ICA3PP (1), том 7439 из Lecture Notes in Computer Science, стр. 502-516. Springer, (2012)MPFFT: An Auto-Tuning FFT Library for OpenCL GPUs., , , , и . J. Comput. Sci. Technol., 28 (1): 90-105 (2013)Optimizing distributed training deployment in heterogeneous GPU clusters., , , , , , , , и . CoNEXT, стр. 93-107. ACM, (2020)Efficient Pipeline Planning for Expedited Distributed DNN Training., , , , , , и . INFOCOM, стр. 340-349. IEEE, (2022)Memristors for neural branch prediction: a case study in strict latency and write endurance challenges., , , , , , , и . Conf. Computing Frontiers, стр. 26:1-26:10. ACM, (2013)Learning beyond Predefined Label Space via Bayesian Nonparametric Topic Modelling., , , , и . CoRR, (2019)Minimal Multi-threading: Finding and Removing Redundant Instructions in Multi-threaded Processors., , , , , , и . MICRO, стр. 337-348. IEEE Computer Society, (2010)Characterizing and Understanding the Bandwidth Behavior of Workloads on Multi-core Processors., , и . Euro-Par, том 5704 из Lecture Notes in Computer Science, стр. 110-121. Springer, (2009)