Stochastic gradient descent (SGD) is the most prevalent algorithm for training Deep Neural
Networks (DNN). SGD iterates the input data set in each training epoch processing data …

Monitoring and analyzing I/O behaviors is critical to the efficient utilization of parallel storage
systems. Unfortunately, with increasing I/O requirements and resource contention, I/O …

As I/O demand of scientific applications increases, identifying, predicting, and analyzing I/O
behaviors is critical to ensure parallel storage systems are efficiently utilized. This paper …

Automatic Speech Recognition (ASR) is an essential task in the field of artificial intelligence.
With the widespread application of deep learning (DL), end-to-end ASR systems have …

The analysis of microstructurally distinct cytoarchitectonic areas in the human brain provides
the foundation to associate functional, physiological, genetic, molecular, and connectivity …

The segregation of the human brain in cytoarchitectonic areas is an important prerequisite
for the allocation of functional imaging, physiological, connectivity, molecular and genetic …

High Performance Computing is now a strategic resource as it allows to simulate complex
phenomena in order to better understand them. While ten years ago, HPC was mostly used …

Abstract Researchers within the Human Brain Project and related projects have in the last
couple of years expanded their needs for high-performance computing infrastructures. The …

The use of Deep Learning methods is identified as a key opportunity for enabling processing
of extreme-scale scientific datasets. Efficient processing of these datasets thus requires the …

Deep Learning (DL) has become fundamental to the advancement of several areas, such as
computer vision, natural language processing and expert systems. Utilizing DL techniques …