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

Cloudian’s new PyTorch connector is built on Nvidia Corp.’s GPUDirect Storage technology and optimized for Nvidia Spectrum-X ...

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

Large scale DNN training tasks are exceedingly compute-intensive and time-consuming, which are usually executed on highly-parallel platforms. Data and model parallelization is a common way to speed up ...

Two June rulings, and more queued up—what legal professionals need to know about the fair use decisions rewriting today’s AI playbook, and the next wave of AI-copyright showdowns.

I encountered a variety of issues while trying to adopt a combination of DistributedDataParallel and DTensor based tensor parallelism. Some specific to DDP+TP, some more general. This seems to be s ...

Distributed training of deep neural networks (DNNs) suffers from efficiency declines in dynamic heterogeneous environments, due to the resource wastage brought by the straggler problem in data ...

Summary Currently, torch's FSDP2 (Fully Sharded Data Parallel 2) does not support having multiple different data types (dtypes) for parameters within the same module. This limitation restricts the ...

A 2024 report from the nonprofit watchdog Epoch AI projected that large language models (LLMs) could run out of fresh, human-generated training data as soon as 2026. Earlier this year, the ...