
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...