Archive of posts tagged: Machine Learning
The Different Facets of Large-Scale GPU Cluster Scheduling for ML Jobs
Machine Learning (ML) training is an important workload in enterprise clusters and cloud data centers today. Products like virtual assistants, chatbots, and web search which are an integral part of our life now, are empowered by the innovations in ML and AI research....
5 Guidelines for Research in ML for Systems
It was more than 10 years ago that I first started studying machine learning (ML). Serendipitously, I ended up leveraging ML techniques developed for biological sequence analysis for optimizing storage systems. In the recent past, I have focused on optimizing and...
From Application Specific to General Purpose (Again)
With Dennard scaling discontinued, application-specific hardware accelerators are ubiquitous in modern computers to offer more efficient task processing. Famous examples include Google’s Tensor Processing Units (TPUs) and Apple’s Neural Engines for...
Numerical Encoding for DNN Accelerators
DNN training is emerging as a popular compute-intensive workload. This blog post provides an overview of the recent research on numerical encoding formats for DNN training, and presents the Hybrid Block Floating-Point (HBFP) format which reduces silicon provisioning...Subscribe
