Introducing New Performance Tiers for Azure Managed Lustre: Enhancing HPC Workloads
Building upon the success of its General Availability (GA) launch last month, we’re excited to unveil two new performance tiers for Azure Managed Lustre (AMLFS): 40MB/s per TiB and 500MB/s per TiB. This blog post explores the specifics of these new tiers and how they embody a customer-centric approach to innovation.
Deploy NDm_v4 (A100) Kubernetes Cluster
We show how to deploy an optimal NDm_v4 (A100) AKS cluster, making sure that all 8 GPU and 8 InfiniBand devices available on each vritual machine come up correctly and are available to deliver optimal performance. A multi-node NCCL allreduce job is executed on the NDmv4 AKS cluster to verify its deployed/configured correctly.
Ramp up with me...on HPC: What is high-performance computing (HPC)?
Over the next several months, let’s take a journey together and learn about the different use cases. Join me as I dive into each use case and for some of them, I’ll even try my hand at the workload for the first time. We’ll talk about what went well, and any what issues I ran into. And maybe, you’ll get to hear a little about our customers and partners along the way.Running GPU accelerated workloads with NVIDIA GPU Operator on AKS
The focus of this article will be on getting NVIDIA GPUs managed and configured in the best way on Azure Kuberentes Services using NVIDIA GPU Operator for HPC/AI workloads requiring a high degree of customization and granular control over the compute-resources configuration
Azure announces new AI optimized VM series featuring AMD’s flagship MI300X GPU
In our relentless pursuit of pushing the boundaries of artificial intelligence, we understand that cutting-edge infrastructure and expertise is needed to harness the full potential of advanced AI. At Microsoft, we've amassed a decade of experience in supercomputing and have consistently supported the most demanding AI training and generative inferencing workloads. Today, we're excited to announce the latest milestone in our journey. We’ve created a virtual machine (VM) with an unprecedented 1.5 TB of high bandwidth memory (HBM) that leverages the power of AMD’s flagship MI300X GPU. Our Azure VMs powered with the MI300X GPU give customers even more choices for AI optimized VMs.Performance considerations for large scale deep learning training on Azure NDv4 (A100) series
Modern DL training jobs require large Clusters of multi-GPUs with high floating-point performance connected with high bandwidth, low latency networks. The Azure NDv4 VM series is designed specifically for these types of workloads. We will be focusing on HPC+AI Clusters built with the ND96asr_v4 virtual machine type and providing specific optimization recommendations to get the best performance.
Performance at Scale: The Role of Interconnects in Azure HPC & AI Infrastructure
Microsoft Azure’s high-performance computing (HPC) & AI infrastructure is designed from the ground up to support the world’s most demanding workloads. High-performance AI workloads are bandwidth-hungry and latency-sensitive. As models scale in size and complexity, the efficiency of the interconnect fabric—how CPUs, GPUs, and storage communicate—becomes a critical factor in overall system performance. Even with the fastest GPUs, poor interconnect design can lead to bottlenecks, underutilized hardware, and extended time-to-results. In this blog post, we will highlight one of the key enabling features for running large-scale distributed workloads on Azure: a highly tuned HPC-class interconnect. Azure has invested years of system-level engineering of the InfiniBand interconnect, into ready-to-use configurations for customers available on Azure’s HB-series and N-series virtual machine (VMs).
