18 citations · 36 across the 5 of their papers we have counts for
5 papers
Towards a Scalable and Distributed Infrastructure for Deep Learning Applications
Bita Hasheminezhad, Shahrzad Shirzad, Nanmiao Wu +3
Although recent scaling up approaches to training deep neural networks have proven to be effective, the computational intensity of large and complex models, as well as the availabi…
Supporting OpenMP 5.0 Tasks in hpxMP -- A study of an OpenMP implementation within Task Based Runtime Systems
Tianyi Zhang, Shahrzad Shirzad, Bibek Wagle +3
OpenMP has been the de facto standard for single node parallelism for more than a decade. Recently, asynchronous many-task runtime (AMT) systems have increased in popularity as a n…
Scheduling optimization of parallel linear algebra algorithms using Supervised Learning
G. Laberge, S. Shirzad, P. Diehl +3
Linear algebra algorithms are used widely in a variety of domains, e.g machine learning, numerical physics and video games graphics. For all these applications, loop-level parallel…
An Introduction to hpxMP: A Modern OpenMP Implementation Leveraging HPX, An Asynchronous Many-Task System
Tianyi Zhang, Shahrzad Shirzad, Patrick Diehl +3
Asynchronous Many-task (AMT) runtime systems have gained increasing acceptance in the HPC community due to the performance improvements offered by fine-grained tasking runtime syst…
Asynchronous Execution of Python Code on Task Based Runtime Systems
R. Tohid, Bibek Wagle, Shahrzad Shirzad +9
Despite advancements in the areas of parallel and distributed computing, the complexity of programming on High Performance Computing (HPC) resources has deterred many domain expert…