Archive of posts tagged: Machine Learning
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...
Building Performance Scalable and Composable Machine Learning Accelerators
To meet machine learning (ML) practitioners’ insatiable demand for higher processing power, computer architects have been at the forefront of developing accelerated computing solutions for ML that fundamentally changed the landscape of the computing industry. Given...
Rethinking Neural Network Dataflow in Larger Scales
Deep learning, with its most representative algorithm, deep neural networks, has been the primary driving force for the recent rapid development of high-performance computing systems. Hardware researchers are proposing a large number of specialized chip architectures...Subscribe
