13 citations · 25 across the 5 of their papers we have counts for
5 papers
HPAC-ML: A Programming Model for Embedding ML Surrogates in Scientific Applications
Zane Fink, Konstantinos Parasyris, Praneet Rathi +3
Recent advancements in Machine Learning (ML) have substantially improved its predictive and computational abilities, offering promising opportunities for surrogate modeling in scie…
HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU
Zane Fink, Konstantinos Parasyris, Giorgis Georgakoudis +1
The end of Dennard scaling and the slowdown of Moore's law led to a shift in technology trends toward parallel architectures, particularly in HPC systems. To continue providing per…
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…
Performance Evaluation of Python Parallel Programming Models: Charm4Py and mpi4py
Zane Fink, Simeng Liu, Jaemin Choi +2
Python is rapidly becoming the lingua franca of machine learning and scientific computing. With the broad use of frameworks such as Numpy, SciPy, and TensorFlow, scientific computi…
Accelerating Communication for Parallel Programming Models on GPU Systems
Jaemin Choi, Zane Fink, Sam White +3
As an increasing number of leadership-class systems embrace GPU accelerators in the race towards exascale, efficient communication of GPU data is becoming one of the most critical…