12 citations · 16 across the 12 of their papers we have counts for
6 papers · 1 filter
The benefits of prefetching for large-scale cloud-based neuroimaging analysis workflows
Valerie Hayot-Sasson, Tristan Glatard, Ariel Rokem
To support the growing demands of neuroscience applications, researchers are transitioning to cloud computing for its scalable, robust and elastic infrastructure. Nevertheless, lar…
Modeling the Linux page cache for accurate simulation of data-intensive applications
Hoang-Dung Do, Valerie Hayot-Sasson, Rafael Ferreira da Silva +3
The emergence of Big Data in recent years has resulted in a growing need for efficient data processing solutions. While infrastructures with sufficient compute power are available,…
A performance comparison of Dask and Apache Spark for data-intensive neuroimaging pipelines
Mathieu Dugré, Valérie Hayot-Sasson, Tristan Glatard
In the past few years, neuroimaging has entered the Big Data era due to the joint increase in image resolution, data sharing, and study sizes. However, no particular Big Data engin…
Evaluation of pilot jobs for Apache Spark applications on HPC clusters
Valerie Hayot-Sasson, Tristan Glatard
Big Data has become prominent throughout many scientific fields and, as a result, scientific communities have sought out Big Data frameworks to accelerate the processing of their i…
Performance Evaluation of Big Data Processing Strategies for Neuroimaging
Valérie Hayot-Sasson, Shawn T Brown, Tristan Glatard
Neuroimaging datasets are rapidly growing in size as a result of advancements in image acquisition methods, open-science and data sharing. However, the adoption of Big Data process…
A Serverless Tool for Platform Agnostic Computational Experiment Management
Gregory Kiar, Shawn T Brown, Tristan Glatard +1
Neuroscience has been carried into the domain of big data and high performance computing (HPC) on the backs of initiatives in data collection and an increasingly compute-intensive…