Archive of posts tagged: Machine Learning
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...
Multi-Modal On-Device AI: Heterogeneous Computing Once More?
What is Multi-modal AI? Prior research on developing on-device AI solutions have primarily focused on improving the TOPS (Tera Operations Per Second) or TOPS/Watt of AI accelerators by leveraging sparsity, quantization, or efficient neural network architectures...
A Case for Optical Deep Neural Networks
Deep Neural Networks have been a major focus for computer architects in the recent past due to the massive parallelism available in computation, combined with the massive amount of data re-use. While the proposed architectures have inspired industry innovations such...
Architecture Innovation Accelerates Artificial Intelligence
[Editor’s Note: This article originally appeared on the blogs of the HLF and the CCC and is re-posted here with permission.] As part of the first day of the Virtual Heidelberg Laureate Forum (HLF) David A. Patterson, who won the 2017 ACM A.M Turing Award “for...Subscribe
