3 papers
cs.DC2023
Performance Optimization using Multimodal Modeling and Heterogeneous GNN
Akash Dutta, Jordi Alcaraz, Ali TehraniJamsaz +3
Growing heterogeneity and configurability in HPC architectures has made auto-tuning applications and runtime parameters on these systems very complex. Users are presented with a mu…
cs.DC2023
ParaGraph: Weighted Graph Representation for Performance Optimization of HPC Kernels
Ali TehraniJamsaz, Alok Mishra, Akash Dutta +3
GPU-based HPC clusters are attracting more scientific application developers due to their extensive parallelism and energy efficiency. In order to achieve portability among a varie…
cs.DC2023
Power Constrained Autotuning using Graph Neural Networks
Akash Dutta, Jee Choi, Ali Jannesari
Recent advances in multi and many-core processors have led to significant improvements in the performance of scientific computing applications. However, the addition of a large num…