MPI (Message Passing Interface) is the de facto standard distributed communications framework ... in this series discussed an exascale-capable machine learning algorithm and how the Lustre file system ...

Climate volatility and rising energy demand have resulted in unprecedented challenges throughout the world. Unfortunat ...

Jensen Huang, Nvidia CEO, emphasized the collaborative aspect between chip architecture, systems ... challenges and opportunities for distributed machine learning going forward.

Client/Server distribution and the nature of the client (end user device) itself are important factors in understanding distributed architecture ... improve operational analytics by using AI and ...

Despite existing data management standards like MIAPPE and FAIR, challenges persist in machine learning (ML ... participation. This distributed ledger-based system not only offers financial ...

Google today announced the launch of version 0.8 of TensorFlow, its open source library for doing the hard computation work that makes machine learning ... The company says distributed computing ...

A new communication-collective system ... of AI and machine learning models continues to increase, training requires several servers or nodes to work together in a process called distributed ...

Instrumenting these systems and then applying machine learning might yield insight that could allow us to do enterprise architecture better -- 'this system is a hot spot,' 'this system doesn't ...

By integrating LoRa technology with distributed machine learning, the network connectivity of green intelligent transportation systems can be optimized. Applying LoRa technology to the monitoring ...