4 citations · 16 across the 14 of their papers we have counts for
9 papers · 1 filter
A Unifying Framework to Enable Artificial Intelligence in High Performance Computing Workflows
Jens Domke, Mohamed Wahib, Anshu Dubey +2
Current trends point to a future where large-scale scientific applications are tightly-coupled HPC/AI hybrids. Hence, we urgently need to invest in creating a seamless, scalable fr…
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…
At the Locus of Performance: Quantifying the Effects of Copious 3D-Stacked Cache on HPC Workloads
Jens Domke, Emil Vatai, Balazs Gerofi +9
Over the last three decades, innovations in the memory subsystem were primarily targeted at overcoming the data movement bottleneck. In this paper, we focus on a specific market tr…
A64FX -- Your Compiler You Must Decide!
Jens Domke
The current number one of the TOP500 list, Supercomputer Fugaku, has demonstrated that CPU-only HPC systems aren't dead and CPUs can be used for more than just being the host contr…
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…
White Paper from Workshop on Large-scale Parallel Numerical Computing Technology (LSPANC 2020): HPC and Computer Arithmetic toward Minimal-Precision Computing
Roman Iakymchuk, Daichi Mukunoki, Artur Podobas +15
In numerical computations, precision of floating-point computations is a key factor to determine the performance (speed and energy-efficiency) as well as the reliability (accuracy…
Double-precision FPUs in High-Performance Computing: an Embarrassment of Riches?
Jens Domke, Kazuaki Matsumura, Mohamed Wahib +6
Among the (uncontended) common wisdom in High-Performance Computing (HPC) is the applications' need for large amount of double-precision support in hardware. Hardware manufacturers…