Gurdip Singh, Divisional Dean, School of Computing, received funding from the National Science Foundation for the project: "EAGER: Distributed Computing Models and Algorithms for Pervasive Systems ...

As the complexity and scale of scientific, AI, and simulation workloads continue to grow, modern high-performance computing (HPC) systems are evolving into ...

Inference of Billion-Scale Models : In the token generation process, a client locally stores the model's token embeddings, typically constituting a small fraction of the total parameter count and ...

How event-driven design can overcome the challenges of coordinating multiple AI agents to create scalable and efficient reasoning systems. While large language models are useful for chatbots, Q&A ...

Course Description A distributed system is comprised of multiple computing devices interconnected with one another via a loosely-connected network. Almost all computing systems and applications today ...

Another key challenge in the studies is the ability to represent intellectual-property-protected computer code. The most accurate results can be obtained when using models provided by an original ...

The concept of distributed computing is simple enough: You take a very large project, slice it up into pieces, and send out individual pieces to PCs for processing.

The distributed file system can reach a 6.6 TiB/s aggregate read throughput when used in a 180-node cluster, achieving a 3.66 TiB/min throughput on the GraySort benchmark (in a 25-node cluster).

Distributed Inference Computing for EVs & Bots: also difficult to model, but shows some promise if massively scaled. Most of the opportunity here is with EVs – as they have more compute and more ...