As someone who has spent the better part of two decades optimizing distributed systems—from early MapReduce clusters to ...

11. Open Platform for Enterprise AI (OPEA) OPEA is a framework that can be used to provide a variety of common generative AI ...

Developed by Meta, PyTorch is a popular machine learning library that helps develop and train neural networks.

Distributed data-parallel training (DDP) is prevalent in large-scale deep learning. To increase the training throughput and scalability, high-performance collective communication methods such as ...

Originally driven by Intel’s now-defunct Optane storage class memory, Parallelstore offers massive parallel file storage targeted at artificial intelligence training use cases on Google Cloud.

EDDIS is a novel distributed deep learning library designed to efficiently utilize heterogeneous GPU resources for training deep neural networks (DNNs), addressing scalability and communication ...

Using various communication libraries, the following distributed training strategies are developed: Data Parallelism (DP): In distributed training, each GPU worker handles a portion of the data and ...

NeuroMesh (nmesh.io), a trailblazer in artificial intelligence, announces the rollout of its distributed AI training protocol, poised to revolutionize global access and collaboration in AI development ...

Zhang, L., et al. (2021) Data Parallel Distributed Training for Sequence-to-Sequence Models. Proceedings of the Institute of Electrical and Electronics Engineers International Conference on Big Data, ...