Archive of posts tagged: Storage
The New Bottlenecks of ML Training: A Storage Perspective
Machine Learning (ML), specifically Deep Neural Networks (DNNs), is stressing storage systems in new ways, moving the training bottleneck to the data ingestion phase, rather than the actual learning phase. Training these models is data-hungry, resource-intensive, and...
Rethinking Data Storage and Preprocessing for ML
Machine learning (ML) — and in particular deep learning — applications have sparked the development of specialized software frameworks and hardware accelerators. Frameworks like PyTorch and TensorFlow offer a clean abstraction for developing and running...
The Changing World of Storage
The world of storage is changing rapidly. We have exciting new technologies such as Intel DC Persistent Memory, along with new applications such as machine learning and blockchain which place new requirements on storage systems. Researchers are working on new...
From FLOPS to IOPS: The New Bottlenecks of Scientific Computing
More than a decade ago, the pioneering computer scientist Jim Gray envisioned a fourth paradigm of scientific discovery that uses computers to solve data-intensive scientific problems. Today, scientific discovery, whether observational, in-silico or experimental,...Subscribe
