9 citations · 19 across the 7 of their papers we have counts for
4 papers · 1 filter
Myths and Legends in High-Performance Computing
Satoshi Matsuoka, Jens Domke, Mohamed Wahib +2
In this thought-provoking article, we discuss certain myths and legends that are folklore among members of the high-performance computing community. We gathered these myths from co…
Preparing for the Future -- Rethinking Proxy Apps
Satoshi Matsuoka, Jens Domke, Mohamed Wahib +5
A considerable amount of research and engineering went into designing proxy applications, which represent common high-performance computing workloads, to co-design and evaluate the…
Matrix Engines for High Performance Computing:A Paragon of Performance or Grasping at Straws?
Jens Domke, Emil Vatai, Aleksandr Drozd +8
Matrix engines or units, in different forms and affinities, are becoming a reality in modern processors; CPUs and otherwise. The current and dominant algorithmic approach to Deep L…
Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMA
Mohamed Wahib, Haoyu Zhang, Truong Thao Nguyen +5
The dedicated memory of hardware accelerators can be insufficient to store all weights and/or intermediate states of large deep learning models. Although model parallelism is a via…