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DeepSpeed is an important part of Microsoft's new AI at Scale initiative to enable next-generation AI capabilities at scale, where you can find more information ...

Microsoft Research Blog ... Multi-GPU inference with DeepSpeed for large-scale Transformer models; Compressed training with Progressive ...

06.08.2020 · DeepSpeed Microsoft Research Webinar is now on-demand Direct Link. Updated: August 6, 2020 Twitter Facebook LinkedIn Previous Next

Why Deepspeed?

Z-code, a part of Microsoft Project Turing, consists of a family of multilingual pretrained models that can be used for various downstream ...

11.10.2021 · We are excited to introduce the DeepSpeed- and Megatron-powered Megatron-Turing Natural Language Generation model (MT-NLG), the largest and the most powerful monolithic transformer language model trained to date, with 530 billion parameters. It is the result of a research collaboration between Microsoft and NVIDIA to further parallelize and optimize …

DeepSpeed, part of Microsoft AI at Scale, is a deep learning optimization library that makes distributed training easy, efficient, and effective.

• AI at Scale - Microsoft Research• GitHub - microsoft/DeepSpeed• ZeRO & DeepSpeed: New system optimizations enable training models with over 100 billion parameters - Microsoft Research

Challenges of Training Large Deep Learning Models

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. ... DeepSpeed can train DL models with over a ...

DeepSpeed: Extreme-scale model training for everyone · Microsoft research webinars · 3D parallelism: Scaling to trillion-parameter models · ZeRO- ...

DeepSpeed, part of Microsoft AI at Scale, is a deep learning optimization library that makes distributed training easy, efficient, and effective.

Type: Full-time researcher. Lab/Location: Microsoft Research Lab - Redmond. Research Area: Artificial intelligence, Systems and networking.

Microsoft research webinars. Lectures from Microsoft researchers with live Q&A and on-demand viewing. Register today. Train massive models ...

01.04.2020 · DeepSpeed hands on deep dive: part 1, part 2, part 3; FAQ; Microsoft Research Webinar Registration is free and all videos are available on-demand. ZeRO & Fastest BERT: Increasing the scale and speed of deep learning training in DeepSpeed. DeepSpeed on AzureML

DeepSpeed. DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. DeepSpeed can train DL models with over a hundred billion parameters on current generation of GPU clusters, while achieving over 10x in system performance compared to the state-of-art.

DeepSpeed, part of Microsoft AI at Scale, is a deep learning optimization library that makes distributed training easy, efficient, and effective.

DeepSpeed with 1-bit Adam: 5x less communication and 3.4x faster training. 10x bigger model training on a single GPU with ZeRO-Offload. Powering 10x longer sequences and 6x faster execution through DeepSpeed Sparse Attention. DeepSpeed Microsoft Research Webinar is now on-demand Permalink.

May 19, 2020 · Altogether, the memory savings empower DeepSpeed to improve the scale and speed of deep learning training by an order of magnitude. More concretely, ZeRO-2 allows training models as large as 170 billion parameters up to 10x faster compared to state of the art. Fastest BERT training: While ZeRO-2 optimizes large models during distributed ...

19.05.2020 · Announcing ZeRO-2 from Microsoft, new memory optimizations in DeepSpeed for training large-scale deep learning models. DeepSpeed trains 100B parameter models 10x faster than state-of-the-art. Learn how DeepSpeed sets a BERT training record.

DeepSpeed, part of Microsoft AI at Scale, is a deep learning optimization library that makes distributed training easy, efficient, and effective.

Oct 11, 2021 · We are excited to introduce the DeepSpeed- and Megatron-powered Megatron-Turing Natural Language Generation model (MT-NLG), the largest and the most powerful monolithic transformer language model trained to date, with 530 billion parameters. It is the result of a research collaboration between Microsoft and NVIDIA to further parallelize and optimize the training of very large AI […]