Habana Blog

In the 1.10 release, we’ve upgraded versions of several libraries, including PyTorch 2.0.1, PyTorch Lightning 2.0.0 and TensorFlow 2.12.0. We have added support for EKS 1.25 and OpenShift 4.12

We’re excited to participate in this year’s ISC High Performance Compute 2023 event in Hamburg Germany. This year our team will demonstrate the capabilities of our Habana Gaudi2® processors, which deliver high-performance, high-efficiency deep learning training and inference.

Equus and Habana have teamed up to simplify the process of testing, implementing and deploying AI infrastructure based on Habana Gaudi2 processors. Customers can now leverage Equus Lab-as-a-Service to reach their innovation […]

Announcing a new End-to-End use case showing Training of a semantic segmentation model for Autonomous Driving

In the 1.9 release, we’ve upgraded versions of several libraries, including PyTorch Lightning 1.9.4, DeepSpeed 0.7.7, fairseq 0.12.3, and Horovod v0.27.0.

In this article, you’ll learn how to easily deploy multi-billion parameter language models on Habana Gaudi2 and get a view into the Hugging Face performance evaluation of Gaudi2 and A100 on BLOOMZ.

AWS and Habana collaborated to enable EFA Peer Direct support on the Gaudi-based AWS DL1 instances, offering users significant improvement in multi-instance model training performance.

AI is becoming increasingly important for retail use cases.  It can provide retailers with advanced capabilities to personalize customer experiences, optimize operations, and increase sales.  Habana has published a new Retail use […]

In this article, you will learn how to use Habana® Gaudi®2 to accelerate model training and inference, and train bigger models with 🤗 Optimum Habana.

With Habana’s SynapseAI 1.8.0 release support of DeepSpeed Inference, users can run inference on large language models, including BLOOM 176B.

Our blog today features a Riken white paper, initially prepared and published by the Intel Japan team in collaboration with Kei Taneishi, research scientist with Riken’s Institute of Physical and Chemical Research. […]

We have upgraded versions of several libraries with SynapseAI 1.8.0, including PyTorch 1.13.1, PyTorch Lightning 1.8.6 and TensorFlow 2.11.0 & 2.8.4.

In this post, we show you how to run Habana’s DeepSpeed enabled BERT1.5B model from our Model-References repository.

In this paper we’ll show how Transfer Learning is an efficient way to train an existing model on a new and unique dataset with equivalent accuracy and significantly less training time.

Habana’s Gaudi2 delivers amazing deep learning performance and price advantage for both training as well as large-scale deployments, but to capture these advantages developers need easy, nimble software and the support of […]

This tutorial provides example training scripts to demonstrate different DeepSpeed optimization technologies on HPU. This tutorial will focus on the memory optimization technologies, including Zero Redundancy Optimizer(ZeRO) and Activation Checkpointing.

The SDSC Voyager supercomputer is an innovative AI system designed specifically for science and engineering research at scale.

In this post, we will learn how to run PyTorch stable diffusion inference on Habana Gaudi processor, expressly designed for the purpose of efficiently accelerating AI Deep Learning models.

In training workloads, there may occur some scenarios in which graph re-compilations occur. This can create system latency and slow down the overall training process with multiple iterations of graph compilation. This blog focuses on detecting these graph re-compilations.

In this tutorial we will learn how to write code that automatically detects what type of AI accelerator is installed on the machine (Gaudi, GPU or CPU), and make the needed changes to run the code smoothly.

The Habana® team is excited to be at re:Invent 2022, November 28 – December 1.  We’re proud that Amazon EC2 DL1 instances featuring Habana Labs Gaudi deep learning accelerators are providing an […]

We have upgrade versions of several libraries with SynapseAI 1.7.0, including DeepSpeed 0.7.0, PyTorch Lightning 1.7.7, TensorFlow 2.10.0 & 2.8.3, horovod 0.25.0, libfabric 1.16.1, EKS 1.23, and Open Shift 4.11.

The Habana® team is excited to be in Dallas at SuperComputing 2022. We look forward to sharing the latest performance advances for Gaudi®2, expanded software support and partner solutions from Supermicro, Inspur […]

Today MLCommons® published industry results for their AI training v2.1 benchmark that contained an impressive number of submissions, with over 100 results from a wide array of industry suppliers, with roughly 90% […]

In this tutorial, we will demonstrate fine tuning a GPT2 model on Habana Gaudi AI processors using Hugging Face optimum-habana library with DeepSpeed.

Gaudi and Gaudi2-based Servers Deliver Flexibility with Industry-standard Interoperability State-of-the-art deep learning applications require multiple processors in systems with multiple inter-card links running at high speed and with ample bandwidth. To provide […]

One of the key challenges in Large Language Model (LLM) training is reducing the memory requirements needed for training without sacrificing compute/communication efficiency and model accuracy.

One of the key challenges in Large Language Model (LLM) training is reducing the memory requirements needed for training without sacrificing compute/communication efficiency and model accuracy.  DeepSpeed [2] is a popular deep learning software […]

AI is transforming enterprises with valuable business insights, increased operational efficiencies and enhanced user experiences with innovative applications that can fuel growth. However, enterprise customers are challenged by the daily demands of […]

The Habana team is excited to share with you our deep learning technologies and invite you to see our demos featured at the Intel Innovation 2022 conference happening today and tomorrow at […]

In this post, we will learn how to run PyTorch V-diffusion inference on Habana Gaudi processor, expressly designed for the purpose of efficiently accelerating AI Deep Learning models.  Art Generation with V-diffusion […]

In this post, we will learn how to migrate a TensorFlow EfficientNet model from running initially on a CPU to a Habana Gaudi Training processor, expressly designed for the purpose of efficiently […]

The Habana team is happy to announce the release of SynapseAI® version 1.6.0.  In this release, we introduce preliminary inference capabilities on Gaudi. For further details, refer to the Inference on Gaudi guide.  […]

Much has happened at Habana since our last MLPerf submission in November 2021. We launched Gaudi®2, our second-generation deep learning training processor, and Greco™, our second-generation inference processor. We expanded our software […]

SynapseAI 1.5 brings many improvements, both in usability and in Habana ecosystem support. For PyTorch we removed the need for weight permutation, as well as the need to explicitly call load_habana_module. See […]

The Habana team is excited to have launched our next-gen 7nm training and inference processors, Gaudi2 for training and Greco for inference, this morning on stage at Intel Vision 22.  Sandra Rivera, […]

We are excited to announce the release of SynapseAI 1.4.1. This is the first release that enables SynapseAI training on Habana Gaudi®2 AI processors. With this release we have enabled TensorFlow Resnet50 […]

As demand for deep learning applications grows among enterprises and startups, so does the need for high-performance, yet cost-effective cloud solutions for training DL models. With the Amazon EC2 DL1 Instance, users […]

Powered by deep learning, transformer models deliver state-of-the-art performance on a wide range of machine learning tasks, such as natural language processing, computer vision, speech, and more. However, training them at scale […]

The Habana(R) Labs team is pleased to augment software support for the Gaudi platform with the release of SynapseAI® version 1.4.0. In this release, we have made several version updates. We now support […]

The Habana team is pleased to be collaborating with Grid.ai to make it easier and quicker for developers to train on Gaudi® processors with PyTorch Lightning without any code changes. Grid.ai and […]

Earlier this year, Machine Learning Algorithm Developer, Chaim Rand, evaluated the Amazon EC2 DL1 instance based on the Habana Gaudi processor and demonstrated some of its unique properties. This was a sequel […]

The Habana® Labs team is happy to announce the release of SynapseAI® version 1.3.0. In this release, we have made several version updates. We now support PyTorch 1.10.1 (previously 1.10.0), PyTorch Lightning […]

The Habana® Labs team is happy to announce the release of SynapseAI® version 1.2.0. In addition to many improvements and bug fixes, the new version includes the following new capabilities. SynapseAI software […]

Habana Gaudi’s compute efficiency and integration bring new levels of price-performance to both cloud and on-premise data-center customers.  Cnvrg.io MetaCloud is transforming the way enterprises manage, scale and accelerate AI and data […]

Join Us December 8 & 9 at DDN’s Booth #229, Javits Center At The AI Summit/New York, Habana, in collaboration with the DDN team, will feature our turnkey AI solution, the combination […]

The MLPerf community aims to design fair and useful benchmarks that provide “consistent measurements of accuracy, speed, and efficiency” for machine learning solutions. To that end AI leaders from academia, research labs, […]

A New Hardware and Software Stack for Deep Learning Introduction Demand for high-performance deep learning (DL) training is accelerating with the growing number of applications and services based on image and gesture […]

The numbers behind “up to 40% better price performance” Today, AWS announced the availability of the Amazon EC2 DL1.24xlarge instances, accelerated by Habana Gaudi AI processors. This is the first AI training […]

We are happy to announce the release of SynapseAI version 1.1.0. In addition to many improvements and bug fixes, the new version includes the following new capabilities: We introduced support for PyTorch […]