Numenta’s Post

Unlock the potential of multiple GPUs for your #machinelearning projects with #vSphere 8 and @NVIDIA NVSwitch! Discover how #VMware takes the vendor device group concept to the next level, enabling seamless integration of up to 8 GPUs for data scientists and developers. Read the article to stay ahead in the world of high-performance computing! https://lnkd.in/eBpzEjPJ #vSphere #NVIDIA

Chris J Gully, Luke Huckaba, Patryk Wolsza, and I recently compiled AI performance data for Intel AMX CPUs. Based on these results, Dave Morera published a configuration guide to help you run AI workloads without using GPUs. If you're interested in learning more about the hardware you need to support different types of workloads, check out the guide here: https://lnkd.in/giBxvsSz. #AI #Intel #AMX #CPUs #VMware #AIworkloads

As part of a full day of sessions at AI Field Day #AIFD4 brought to you by Intel Corporation, Earl Ruby of VMware presented a practical exploration of AI deployment without GPUs, focusing on the utilization of Intel Advanced Matrix Extensions (#AMX) CPUs in partnership with VMware. The collaborative effort, VMware Private AI with Intel, facilitates the construction and deployment of secure AI models by leveraging VMware Cloud Foundation and integrating 4th Generation Intel #Xeon Scalable Processors with built-in accelerators. Ruby provided a clear explanation of the technology behind AMX CPUs, demonstrating their capability to efficiently accelerate AI and machine learning workloads within a virtualized environment, eliminating the need for separate GPU accelerators. The session delved into the operational benefits of Private AI, emphasizing critical aspects like data privacy, intellectual property protection, and the seamless integration of established security tools within the vSphere environment. Ruby showcased tangible performance improvements achieved by Large Language Models (LLMs) running on AMX CPUs, highlighting increased speed and efficiency compared to older CPUs lacking AMX technology. In a subsequent presentation, Ruby expanded the discussion to cover the deployment of AI models with VMware Tanzu Kubernetes on vSphere, offering a practical guide for setting up Tanzu to run AI/ML workloads using AMX CPUs. The demonstration included real-time video processing with #OpenVINO on vSphere 8, illustrating the power of AMX and OpenVINO's model compression for reduced memory and compute requirements. The session concluded with the presentation of performance results from Llama 2's 7 billion LLM inference on a single fourth-gen Xeon CPU, showcasing its ability to deliver inference with an average latency under 100 milliseconds – a milestone suitable for meeting chatbot response time requirements. To learn more about this pragmatic approach to AI deployment, watch the full session on the Tech Field Day website and watch for more from Keith Townsend of The Futurum Group!

Anyone heading to Santa Clara next week for the SNIA Developer Conference? It seems that no discussion on digital infrastructure is complete these days without touching on AI—so we've got just the right presentation for you: AI and storage, a perfect match. At SDC 24, MangoBoost's Chief Product Officer Eriko Nurvitadhi and AMD's Storage and Networking Architect Craig Carlson are co-presenting on how the MangoBoost DPU fully accelerates direct, Ethernet-based communications between AMD GPUs and remote, network-attached, disaggregated storage servers using NVMe-over-TCP and peer-to-peer communications. In this talk, MangoBoost and AMD will present the following: • A tutorial on the trends in AI, such as Large Language Models (LLMs), larger datasets, storage-optimized AI frameworks, which drive demands for high-speed storage systems for GPUs. • An overview of AMD’s GPU systems. • A discussion on how DPUs can improve GPU systems efficiencies, specifically in accessing storage servers. • Case studies of modern LLMs AI workloads on AMD MI300X GPU server using open-source AMD ROCm software, where MangoBoost DPU fully accelerates Ethernet-based, direct GPU-storage communications, resulting in reduced CPU utilizations and improvements in performance and scalability. Find out more about the presentation below, and stay tuned for updates! #SNIA #Storage #SNIADeveloperConference #SDC #DataProcessingUnit #DPU #AMD #MI300X #GPU #NAS #NVMe #TCP

Intel Xeon Processors Accelerate GenAI Workloads with Aible For customers running GenAI workloads, Aible’s serverless solutions lower costs, embed intelligence and improve efficiency for RAG and fine-tuning on Intel Xeon processors. #GenAI #IntelXeon #AIInnovation #EnterpriseAI #CloudComputing Read more: https://lnkd.in/ettX6KUT

As our Bare Metal Cloud platform advances, so do our GPU offerings. Sign up for early access to pre-configured servers with the latest 4th Gen Intel® Xeon™ Scalable CPUs and dual Intel Max 1100 GPUs. With minimal effort and lead time, you can optimize end-to-end AI and analytics pipelines on a low-latency, high-throughput network. Join our preorder program and be the first to try these next-gen GPU technologies. Message me for more details! #BareMetalCloud #GPUs #AI #Analytics #IntelXeon #IntelMax #NextGenTechnologies

🔔🔔🔔 #MDPIfutureinternet [New Published Papers in 2024] Title: Analyzing GPU Performance in Virtualized Environments: A Case Study Authors: Adel Belkhiri, and Michel Dagenais Please read at: https://lnkd.in/gG2dmdt2 Keywords: #GPU #virtualization; GVT-g; performance analysis; #softwaretracing via Future Internet MDPI

Optimize your performance and reduce the cost of running #AI workloads by powering them entirely with CPUs. With Aible’s serverless computing and the efficiency of #IntelXeon processors, you can improve your end-to-end process. Read the release to learn how to tap into enhanced AI. https://intel.ly/3XG7cpo #IAmIntel

While RAG is often implemented using GPUs and accelerators to leverage their parallel processing capabilities, Aible’s serverless technique, combined with Intel® Xeon® Scalable processors, allows RAG use cases to be powered entirely by CPUs. #ai #inference #serverless #iamintel

This is MAJOR! AI workloads are expensive and require fine-tuned performance...luckily, Intel Corporation and Aible have your back. The Xeon processors that power over 95% of the world's cloud computing workloads can also power AI workloads with great efficiency. Check out the link below to learn how Aible + Intel are making AI workloads more efficient! #iamintel Kim Goodrich