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Performance Modelling of Deep Learning on Intel Many Integrated Core Architectures
Many complex problems, such as natural language processing or visual obj...
06/04/2019 ∙ by Andre Viebke, et al. ∙
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Customizing Pareto Simulated Annealing for Multi-objective Optimization of Control Cabinet Layout
Determining the optimal location of control cabinet components requires ...
06/04/2019 ∙ by Sabri Pllana, et al. ∙
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HSTREAM: A directive-based language extension for heterogeneous stream computing
Big data streaming applications require utilization of heterogeneous par...
09/25/2018 ∙ by Suejb Memeti, et al. ∙
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Using Meta-heuristics and Machine Learning for Software Optimization of Parallel Computing Systems: A Systematic Literature Review
While the modern parallel computing systems offer high performance, util...
01/29/2018 ∙ by Suejb Memeti, et al. ∙
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Benchmarking OpenCL, OpenACC, OpenMP, and CUDA: programming productivity, performance, and energy consumption
Many modern parallel computing systems are heterogeneous at their node l...
04/18/2017 ∙ by Suejb Memeti, et al. ∙
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CHAOS: A Parallelization Scheme for Training Convolutional Neural Networks on Intel Xeon Phi
Deep learning is an important component of big-data analytic tools and i...
02/25/2017 ∙ by Andre Viebke, et al. ∙
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