activity
20222026
most citedQuantifying Overheads in Charm++ and HPX using Task Bench

12 citations · 12 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

StormNet: Improving storm surge predictions with a GNN-based spatio-temporal offset forecasting model

Noujoud Nader, Stefanos Giaremis, Clint Dawson +3

Storm surge forecasting remains a critical challenge in mitigating the impacts of tropical cyclones on coastal regions, particularly given recent trends of rapid intensification an…

cs.DC2026

Overcoming Latency-bound Limitations of Distributed Graph Algorithms using the HPX Runtime System

Karame Mohammadiporshokooh, Panagiotis Syskakis, Andrew Lumsdaine +1

Graph processing at scale presents many challenges, including the irregular structure of graphs, the latency-bound nature of graph algorithms, and the overhead associated with dist…

cs.DC2026

An Initial Evaluation of Distributed Graph Algorithms using NWGraph and HPX

Karame Mohammadiporshokooh, Panagiotis Syskakis, Hartmut Kaiser

Graphs are central to modeling relationships in scientific computing, data analysis, and AI/ML, but their growing scale can exceed the memory and compute capacity of single nodes,…

cs.DC2025

A New Execution Model and Executor for Adaptively Optimizing the Performance of Parallel Algorithms Using HPX Runtime System

Karame Mohammadiporshokooh, Steven R. Brandt, Hartmut Kaiser

Developing parallel algorithms efficiently requires careful management of concurrency across diverse hardware architectures. C++ executors provide a standardized interface that sim…

cs.DC2022★ 12 cited

Quantifying Overheads in Charm++ and HPX using Task Bench

Nanmiao Wu, Ioannis Gonidelis, Simeng Liu +6

Asynchronous Many-Task (AMT) runtime systems take advantage of multi-core architectures with light-weight threads, asynchronous executions, and smart scheduling. In this paper, we…