In this paper, we explore the use of machine learning to compress the data before it is written out. Despite the computational constraints that limit us to ...

Apr 1, 2019 · In this paper, we explore the use of machine learning to compress the data before it is written out.

The main objective of this work is presentation of the new reconstruction procedure (third-order of accuracy in space), together with the procedure for ...

Abstract—The amount of data output from a computer sim- ulation has grown to terabytes and petabytes as increasingly- complex simulations are being run on ...

This paper explores the use of machine learning to compress the data before it is written out and demonstrates that by simply using a better sampling ...

In this paper, we explore the use of machine learning to compress the data before it is written out. Despite the computational constraints that limit us to ...

Oct 22, 2024 · Conference Paper. Learning to Compress Unstructured Mesh Data from Simulations. October 2017. Chandrika Kamath · Read more. Conference Paper ...

Compressing unstructured mesh data from computer simulations is very challenging. Using a test problem from a fusion simulation, we compare three methods on.

Oct 10, 2024 · We present a general framework for compressing unstructured scientific data with known local connectivity. A common application is simulation ...

Compressing unstructured mesh data from computer simulations poses several challenges that are not encountered in the compression of images or videos.