To make distributed systems algorithms more accessible and usable ... and end users are not exposed to the details of distributed computing mechanisms. User-Friendly APIs and Community Support ...

Abstract: Distributed statistical learning algorithms are performing many machine learning tasks in a distributed environment. Some scenarios where data sharing is desired among many parties and it ...

these algorithms have been foundational in organizing and managing data. However, the advent of multi-core processors and distributed computing brings a new dimension to these algorithms: the ...

The Parallel & Distributed Computing Lab (PDCL) conducts research at the intersection ... We further develop system-aware parallel graph algorithms that enable runtime optimizations for faster and ...

Abstract: This thesis aims to explore the optimization strategies of distributed algorithms in cloud computing environment. With the rapid development of cloud computing, traditional distributed ...

Our modern world relies on “distributed computing,” which shares the computational load among multiple different machines. The technique passes data back and forth in an elaborate choreography of ...

MASc alumnus Nan Li and Prof. Golab publish a paper on Detectable Sequential Specifications in the 35th International Symposium on Distributed Computing (DISC'21).

To improve computational efficiency, the algorithm employs a distributed computing framework, efficiently distributing computational tasks across multiple computing units. Through a parallel ...

a quantum algorithm designed to quickly find solutions within large datasets. The method achieved a 71% success rate, ...