Archive of posts tagged: deep learning
Is It Time To Give Memory Allocator Its Own Room In The House?
Implications of Machine Learning (ML), be the training or inference serving, have steered systems and architecture research accordingly. A significant amount of work is happening in the Systems for ML space ranging from building efficient systems for data...
Graphics Rendering: What’s New and What’s in it for Architects? (Part II)
In Part I of this mini-series, we looked at recent advances in hardware support for ray tracing and how we might ride this wave to think more broadly about general-purpose irregular computing. Part II looks at another rising trend in graphics, i.e., the confluence of...
The Future of Sparsity in Deep Neural Networks
Sparsity in Deep Neural Networks The key characteristic of deep learning is that accuracy empirically scales with the size of the model and the amount of training data. Over the past decade, this property has enabled dramatic improvements in the state of the art...Subscribe
