Warehouse-Scale and Parallel Computing

Photo of Lingjia Tang

Creating more efficient data centers for AI

Tang’s project will redesign data center systems to support large-scale use of hardware accelerators to meet future computational demand.|Short Read
Prof. Mosharaf Chowdhury

Chowdhury receives VMWare Award to further research on cluster-wide memory efficiency

Chowdhury’s work has produced important results that can make memory in data centers both cheaper and more efficient. |Short Read
Large-scale data center

Chowdhury wins NSF CAREER award for making memory cheaper, more efficient in big data centers

Chowdhury connects all unused memory in a data cluster and treats it as a single unit.|Short Read
GPU cluster

Two solutions for GPU efficiency can boost AI performance

Chowdhury's lab multiplied the number of jobs a GPU cluster can finish in a set amount of time|Medium Read
Baris Kasikci

Speeding up code with clever data manipulation

Kasikci presents a method to improve a program’s ability to use data in a straightforward, efficient way|Short Read

Student earns Microsoft Fellowship for research in a new computing paradigm

Kassa is developing a framework that will look at the computations of an application and decide in real time which components will best handle it|Short Read
Large-scale data center

Designing a flexible future for massive data centers

A new approach recreates the power of a large server by linking up and pooling the resources of smaller computers with fast networking technology.|Medium Read
data center

Tracking and mitigating tail latency in data centers

High tail latency has been identified as one of the key challenges facing modern data center design.|Medium Read
top picks

Two papers by Michigan researchers chosen as IEEE Micro Top Picks

The two papers from Michigan introduced the Sirius personal digital assistant and the MBus bus for modular microcomputing systems.|Short Read