Using meta-heuristics and machine learning for software optimization of parallel computing systems: a systematic literature review
While modern parallel computing systems offer high performance, utilizing these powerful
computing resources to the highest possible extent demands advanced knowledge of …
computing resources to the highest possible extent demands advanced knowledge of …
A review of machine learning and meta-heuristic methods for scheduling parallel computing systems
Optimized software execution on parallel computing systems demands consideration of
many parameters at run-time. Determining the optimal set of parameters in a given …
many parameters at run-time. Determining the optimal set of parameters in a given …
Performance modelling of deep learning on intel many integrated core architectures
Many complex problems, such as natural language processing or visual object detection,
are solved using deep learning. However, efficient training of complex deep convolutional …
are solved using deep learning. However, efficient training of complex deep convolutional …
Stochastic bounds for markov chains on intel Xeon Phi coprocessor
J Bylina - Parallel Processing and Applied Mathematics: 12th …, 2018 - Springer
The author presents an approach to find stochastic bounds for Markov chains with the use of
Intel Xeon Phi coprocessor. A known algorithm is adapted to study the potential of the MIC …
Intel Xeon Phi coprocessor. A known algorithm is adapted to study the potential of the MIC …
A kmer-based parallel algorithm for pattern searching in DNA sequences on shared-memory model
F Kaniwa - 2018 - search.proquest.com
The explosive growth of biological sequences over the last decade has consequently led to
a lot of research on effective techniques for storing and analysing this big data. Generating …
a lot of research on effective techniques for storing and analysing this big data. Generating …