Use Case Library

Project Catapult Academic Program

The Project Catapult Academic Program is run in collaboration with the Texas Advanced Computing Center (TACC) at The University of Texas at Austin, and Intel. It provides researchers with free access to Microsoft Catapult FPGA systems located at TACC, including 384 Catapult nodes at TACC, and a Catapult shell development kit, tools, and examples for researchers to develop their own FPGA applications to run on the Catapult FAbRIC platform.

iSchool Microsoft Ability Initiative

The Texas iSchool research team proposed two main tasks of (1) introducing the first publicly-available image captioning dataset from people with visual impairments paired with a community AI challenge and workshop, and (2) identifying the values and preferences of people with visual impairments –to inform the design of next-generation image captioning systems and datasets. 

2019 Microsoft Research PhD Fellowship Winner

Jayashree Mohan’s research aims at building the next generation of file systems: crash-consistent, energy-efficient, and IO-efficient. With the advent of storage technologies with limited write cycles, file systems have to be mindful of their IO footprint. Her work identifies the significance of each of these aspects, building tools and infrastructure to evaluate them, and understanding their impact on file system performance as a whole.

University of Washington

When Timothy Durham looks at the human genome, he sees an encyclopedia of precise instructions that tell approximately 31 trillion cells in the human body how to do their jobs.  Figuring out how cells read and interpret these instructions—and how they can misread them—could help researchers unravel the mysteries of what leads to disease and point to cures. This is a complicated ongoing work being performed by thousands of researchers across the globe. Durham, using the power of cloud computing, is now one of them.

University of California

The Algorithms, Machine, and People (AMP) Lab at the University of California Berkeley builds scalable machine learning and data analysis technologies to turn data into information. Among the many experiments run by the AMP Lab, one area of concentration is in the field of genomics and cancer research. Due to the vast amount of data that genome sequencing produces, the AMP Lab leverages Amazon Web Services (AWS) to quickly scale the compute resources needed to analyze the algorithms that are used in genomics work. As a result, researchers are able to use many machines in the cloud simultaneously to process genome data faster and more cost effectively.

UC Santa Cruz

Our collaborators are asking us for the data to be processed as quickly as possible, so they can analyze cancer samples against other cancer samples in the database. Using AWS, we can get the results to them in days instead of months, which could contribute to faster disease diagnoses.