Humans can remember various types of information, including facts, dates, events and even intricate narratives. Understanding ...

In parallel distributed data processing frameworks like Spark and Flink, task scheduling has a great impact on cluster performance. Though task Scheduling has proven to be an NP-complete problem, a ...

According to the distributed paradigm, the CHARM model allows examining the specific functions of the connections between neurons of brain regions that are distant from each other.

Parallel processing, an integral element of modern computing, allows for more efficiency in a wide range of applications.

Welcome to the Sixth IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (ParSocial 2022). This year the workshop highlights novel algorithms and models that leverage ...

Parallel Processing: Form Activation = Semantic Similarity × Association Weight Given distributed semantic representations and parallel spread of activation, a multitude of forms partially matching ...

The team believes Alpa can democratize distributed model-parallel learning and accelerate the adoption of emerging large deep learning models, and they plan to make Alpa’s source code publicly ...

Due to the large size and computational complexities of the models and data, the performance of networks is reduced. Parallel and distributed deep learning approaches can be helpful in improving the ...