By Guy D’Hauwers, atNorth The original definition of artificial intelligence was the ability of computers to perform tasks that people usually did. However, as the technology continues to develop it is apparent that there are many situations whereby computers can collate up-to-the minute data to provide analysis that no human could feasibly do. This isn’t to say that computers can, or will, replace human jobs, but rather that they provide a better service that transforms the way in which tasks are carried out across business today.
Exxact Partners Offers Run:ai for GPU Clusters in AI Workloads
November 30, 2022 by
FREMONT, CA — Nov. 30, 2022 — Exxact Corporation, a provider of high-performance computing (HPC), artificial intelligence (AI), and data center solutions, now offers Run:ai in their solutions. This groundbreaking Kubernetes-based orchestration tool incorporates an AI-dedicated, high-performant super-scheduler tailored for managing GPU resources in AI clusters. Run:ai dynamically optimizes hardware utilization for AI workloads, enabling clusters […]
Deep Learning GPU Cluster
December 14, 2020 by
In this whitepaper, “Deep Learning GPU Cluster,” our friends over at Lambda walk you through the Lambda Echelon multi-node cluster reference design: a node design, a rack design, and an entire cluster level architecture. This document is for technical decision-makers and engineers. You’ll learn about the Echelon’s compute, storage, networking, power distribution, and thermal design. This is not a cluster administration handbook, this is a high level technical overview of one possible system architecture.
SkyScale: GPU Cloud Computing with a Difference
August 9, 2018 by
In this guest post, Tim Miller, president of SkyScale, covers how GPU cloud computing is on the fast track to crossing the chasm to widespread adoption for HPC applications. “Two good examples of very different markets adopting GPU computing and where cloud usage makes sense are artificial intelligence and high quality rendering.”
GPU Clusters for High-Performance Computing
August 31, 2016 by Leave a Comment
Large-scale GPU clusters are gaining popularity in the scientific computing community. However, their deployment and production use are associated with a number of new challenges. In this paper, we present our efforts to address some of the challenges with building and running GPU clusters in HPC environments. We touch upon such issues as balanced cluster […]
Managing High Performance GPU Clusters
August 31, 2016 by Leave a Comment
To fully take advantage of NVIDIA GPUs requires several sound strategies. The goal of any HPC resource should be to increase the productivity of researchers and engineers because minimizing time to solution is the goal of many leading HPC installations. Keeping users and developers focused on applications is one of the way to increase productivity and minimize wasted time.
