6 citations · 6 across the 9 of their papers we have counts for
6 papers · 1 filter
MIREncoder: Multi-modal IR-based Pretrained Embeddings for Performance Optimizations
Akash Dutta, Ali Jannesari
One of the primary areas of interest in High Performance Computing is the improvement of performance of parallel workloads. Nowadays, compilable source code-based optimization task…
Static Generation of Efficient OpenMP Offload Data Mappings
Luke Marzen, Akash Dutta, Ali Jannesari
Increasing heterogeneity in HPC architectures and compiler advancements have led to OpenMP being frequently used to enable computations on heterogeneous devices. However, the effic…
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…
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…
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…
Learning Intermediate Representations using Graph Neural Networks for NUMA and Prefetchers Optimization
Ali TehraniJamsaz, Mihail Popov, Akash Dutta +2
There is a large space of NUMA and hardware prefetcher configurations that can significantly impact the performance of an application. Previous studies have demonstrated how a mode…