Topics include: binning, scatter/gather, cut-off summation, bin design, thread coarsening and binning, horizontal vs. vertical scaling, shared memory programming, message passing, data sharing models, ...

However, it is still confronted with challenges in parallel algorithm design and performance optimization at the same time.

Parallel algorithm design is not easily reduced to simple recipes. Rather, it requires the sort of integrative thought that is commonly referred to as “creativity.” However, it can benefit from a ...

The team designed a fully dynamic APSP algorithm in the MPC model with low round complexity that is faster than all the existing static parallel APSP algorithms.

Students taking the course for COMP_SCI 368 credit will work on labs that utilize advanced parallel programming, data layout, and algorithm decomposition concepts. Students taking the course for ...

Parallel tempering is a generic Markov chain Monte Carlo sampling method which allows good mixing with multimodal target distributions, where conventional Metropolis-Hastings algorithms often fail.

Microsoft has created a new position to help companies deploying AI to learn how to prioritize ethical principles including fairness, accountability and transparency in the development of the ...