Archive of posts tagged: Cloud computing
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...
Datacenter Architectures: Concerns, Opportunities, and Predictions from an ISCA Mini-Panel
If you were one of the 1700 attendees of the first virtual ISCA last week, you hopefully got a chance to call in to one or more of this year’s mini-panels. Spread across 3 days and many timezones, ISCA hosted 12 mini-panels in total, which ranged in topics from...
What the New Trends in Cloud Software Mean for Architects
The past five years have seen a significant change in the way cloud applications are designed. In place of large monolithic services, where the functionality of an entire application like a social network or search engine was implemented as a single codebase that...
Sure, We Have Systems For ML But How About ML For Systems?
The past few years have seen an unprecedented increase in the number of systems targeting machine learning (ML) applications and deep learning in particular (Jeff Dean has compiled a telling graph on the exponentially increasing number of ML papers). From hardware...Subscribe
