Learn More With FlexPod Datacenter For AI - NetApp

Learn Morewith FlexPodDatacenter for AIYou want to use AIand ML to increaserevenue and efficiency.The FlexPod Datacenter for AIsolution with CiscoUCS C480 MLM5 and Cisco UCSC-Series M5 serversstands ready to trainyour models for fasterinsight.The promise of artificial intelligenceDeep learning (DL) and machine learning (ML) techniques offer the potential forunparalleled access to accelerated insights. With the capability to learn from dataand make more informed, faster decisions, your organization is better positioned todeliver innovative products and services in an increasingly competitive marketplace.Whether you need to make discoveries, analyze patterns, detect fraud, improvecustomer relationships, optimize supply chains, or automate processes, DL and MLtechniques can help you use digital information for business advantage.Traditional IT infrastructure falls shortThe evolution of artificial intelligence (AI) continues to push the bounds of traditionalIT infrastructure (Figure 1). Increasingly complex tasks require unprecedentedlevels of computing power and large amounts of scalable storage. An explosion ofdata results in deep learning models that take days or weeks to train. Computingnodes, storage systems, and networks often are unable to handle the data volume,velocity, and variability of AI, ML, and DL applications at scale. These are not the onlychallenges you may face. Do-it-yourselfintegrations are complex. Assembling and integrating off-the-shelf hardware and software components increases complexity and lengthensdeployment times. As a result, valuable data science resources are wasted onsystems integration work that often results in islands of IT resources that aredifficult to manage and require deep expertise to optimize and control. Achievingpredictable and scalable performance is hard. Scaling withtraditional solutions can lead to downtime. These disruptions not only reduce theproductivity of data scientists, they can result in a chain reaction that reducesdeveloper productivity and causes operational expenses to spin out of control.

Look at your data in new waysFlexPod Datacenter for AI AcceleratesAI/ML initiatives with avalidated solution that demystifiesdeployment ScalesAI and ML solutions are failing to keep pace—or if you have not implemented AI orML solutions yet—deploying the FlexPod Datacenter for AI solution with Cisco UCSC-Series Rack Servers can open the door to better insight. This is especially truewhen data gravity, security, and regulatory requirements dictate that model trainingto more than 20 PB ina single namespace to supportvery large learning data sets withONTAP FlexGroups ReducesData stored on your FlexPod infrastructure holds tremendous value. If your existingdata storage capacitybe performed on the premises, where your data lives.FlexPod Datacenter for AI solutionThe FlexPod Datacenter for AI solution provides converged infrastructure thatis optimized for analytic workloads. Building on the popular FlexPod Datacenterplatform, the solution includes Cisco UCS blade and rack servers, Cisco Nexus requirements up to 10 times with9000 Series switches, Cisco UCS 6000 Series Fabric Interconnects, and NetApp deduplication and compressionAFF A-Series flash storage arrays with NetApp ONTAP data management software.techniques Cisco Supportsdevelopment, testing,UCS C480 ML M5 Rack Server. This no-compromise, purpose-built server integrates graphics processing units (GPUs) and high-speedtraining, and inferencinginterconnect technology with fast networking to accelerate deep-learningenvironmentstasks. The server features two CPUs with up to 28 cores each and up toCisco UCS C480 ML M5Rack ServerDesigned for AI/ML deployments, thenew Cisco UCS C480 ML M5 Rackeight NVIDIA Tesla V100-32GB Tensor Core GPUs that are interconnectedwith NVIDIA NVLink for fast communication across GPUs to acceleratecomputation. NVIDIA specifies TensorFlow

M5. The Cisco UCS C240 M5 Rack Server can host up to four NVIDIA T4 Tensor Core GPUs for AI inferencing, or up to two NVIDIA Tesla V100 Tensor Core GPUs for training workloads. The compact, 1RU Cisco UCS C220 M5 Rack Server can host up to two NVIDIA T4 Tensor Core GPUs. NetApp ONTAP. The ONTAP software built into