MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring

no code implementations • 11 Jan 2024 • Qian Gong, Jieyang Chen, Ben Whitney, Xin Liang, Viktor Reshniak, Tania Banerjee, Jaemoon Lee, Anand Rangarajan, Lipeng Wan, Nicolas Vidal, Qing Liu, Ana Gainaru, Norbert Podhorszki, Richard Archibald, Sanjay Ranka, Scott Klasky

We describe MGARD, a software providing MultiGrid Adaptive Reduction for floating-point scientific data on structured and unstructured grids.

Data Compression Management

Scalable Hybrid Learning Techniques for Scientific Data Compression

1 code implementation • 21 Dec 2022 • Tania Banerjee, Jong Choi, Jaemoon Lee, Qian Gong, Jieyang Chen, Scott Klasky, Anand Rangarajan, Sanjay Ranka

Data compression is becoming critical for storing scientific data because many scientific applications need to store large amounts of data and post process this data for scientific discovery.

Data Compression Video Compression

Expressing linear equality constraints in feedforward neural networks

1 code implementation • 8 Nov 2022 • Anand Rangarajan, Pan He, Jaemoon Lee, Tania Banerjee, Sanjay Ranka

Elimination of the auxiliary variables leads to a dual minimization problem on the Lagrange multipliers introduced to satisfy the linear constraints.

Multi-Label Classification

SparsePipe: Parallel Deep Learning for 3D Point Clouds

no code implementations • 27 Dec 2020 • Keke Zhai, Pan He, Tania Banerjee, Anand Rangarajan, Sanjay Ranka

Besides, it suitably partitions the model when the GPUs are heterogeneous such that the computing is load-balanced with reduced communication overhead.