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Lightning Talk: Predicting Optimal Rendering Frequency for In Situ Visualization in GPU–CPU Workflows
DescriptionHigh Performance Computing (HPC) simulations often run on GPUs while in situ rendering tasks are offloaded to CPUs. Deciding how frequently to perform these in situ renderings is a challenge: render too frequently, and the simulation, or producer, oversaturates the rendering pipeline, or consumer; render too sparsely, and the CPU resources remain idle. This project seeks to develop machine learning (ML) models that can predict rendering times based on available system resources as well as simulation parameters. By leveraging ML-driven insight, the goal of this project is to analyze the tradeoffs and determine an optimal rendering interval for simulations such as nekRS instrumented with Ascent, in this instance. and ensure balanced workloads between the simulation and rendering tasks, ultimately improving overall computational efficiency.
Author/Presenters
Event Type
Workshop
TimeSunday, 16 November 202510:35am - 10:45am CST
Location242
AI, Machine Learning, & Deep Learning
Clouds & Distributed Computing
Performance Evaluation, Scalability, & Portability
Scientific & Information Visualization
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