Archive of posts tagged: Datacenters
Calling for the Return of Non-Virtualized Microprocessor Systems
Sharing computing resources in a microprocessor among multiple tenants (users, tasks) through virtualization, as currently done in datacenters, edge, and embedded environments, conflicts with the need to provide security, isolation, and performance stability. This...
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...
Computation Pushdown across Layers in the Storage Hierarchy
The memory and storage hierarchy deepens in modern systems. To mitigate the low performance of memory/storage devices at the bottom of the hierarchy, near-data processing has been studied across different memory and storage devices as a means to reduce access latency...
The Time is Ripe for Disaggregated Systems
Despite being hidden from the end user, datacenters are ubiquitous in today’s life. Massive datacenter installations are the driving force behind social networking, search, streaming services, e-commerce, cloud, and the gig economy. Today’s datacenters are as...Subscribe
