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Orchestrate Your AI Workload with Cisco Hyperflex, Powered by NVIDIA GPUs
- 1. Michael Balint, NVIDIA Applied Solutions Engineer, June 2018 ORCHESTRATE YOUR AI WORKLOAD WITH HYPERFLEX, POWERED BY NVIDIA GPUS
- 2. 2 AGENDA Rise of GPU computing Value of Volta GPU GPU Aware Kubernetes on HyperFlex
- 3. 3 A NEW ERA OF COMPUTING PC INTERNET WinTel, Yahoo! 1 billion PC users 1995 2005 2015 MOBILE-CLOUD iPhone, Amazon AWS 2.5 billion mobile users AI & IOT Deep Learning, GPU 100s of billions of devices
- 4. 4 1980 1990 2000 2010 2020 GPU-Computing perf 1.5X per year 1000X by 2025 RISE OF GPU COMPUTING Original data up to the year 2010 collected and plotted by M. Horowitz, F. Labonte, O. Shacham, K. Olukotun, L. Hammond, and C. Batten New plot and data collected for 2010-2015 by K. Rupp 102 103 104 105 106 107 Single-threaded perf 1.5X per year 1.1X per year APPLICATIONS SYSTEMS ALGORITHMS CUDA ARCHITECTURE
- 5. 5 TESLA V100 WORLD’S MOST ADVANCED DATA CENTER GPU 5,120 CUDA cores 640 NEW Tensor cores 7.8 FP64 TFLOPS | 15.7 FP32 TFLOPS | 125 Tensor TFLOPS 20MB SM RF | 16MB Cache 16GB/ 32GB HBM2 @ 900GB/s | 300GB/s NVLink
- 6. 6 REVOLUTIONARY AI PERFORMANCE 3X Faster DL Training Performance 3X Reduction in Time to Train Over P100 0 10 20 1X V100 1X P100 2X CPU Relative Time to Train Improvements (LSTM) Neural Machine Translation Training for 13 Epochs |German ->English, WMT15 subset | CPU = 2x Xeon E5 2699 V4 15 Days 18 Hours 6 Hours Over 80X DL Training Performance in 3 Years 1x K80 cuDNN2 4x M40 cuDNN3 8x P100 cuDNN6 8x V100 cuDNN7 0x 20x 40x 60x 80x 100x Q1 15 Q3 15 Q2 17 Q2 16 Exponential Performance over time (GoogleNet) SpeedupvsK80 GoogleNet Training Performance on versions of cuDNN Vs 1x K80 cuDNN2
- 7. 7 HYPERFLEX INFRASTRUCTURE FOR ENTERPRISE KUBERNETES Simple Install & Management Resiliency & Availability Scalability • Automated Hyperflex installer • Infrastructure ready to consume (create virtual machines) in less than an hour • Management through native HyperFlex Connect or vCenter plugin • Distributed filesystem ensures data written evenly across all nodes in cluster • No hotspots, no data locality • HyperFlex automatically replicates data locally across nodes • Ensures high availability and fault tolerance • Scale HyperFlex cluster to 64 nodes • Maximum of 32 HyperFlex converged nodes, all-flash or hybrid • Maximum of 32 HyperFlex compute-only nodes
- 8. 8 IaaS HyperFlex Compute/Storage HyperFlex Network ACI Nexus 9k standalone On prem Kubernetes Cisco Container Platform Container Networking Contiv VPP, ACI-CNI Container Storage HyperFlex Flex driver Turnkey Kubernetes • Simple & Seamless Day0 & DayN K8S operations integrated into HyperFlex • HyperFlex IaaS Enterprise Storage • Scale-out, HA Filesystem • Data protection, efficiency and resiliency Enterprise Networking & Security • Multi-tenant architecture, Micro-segmentation, Security policies Common Platform for Legacy & Modern Apps • Co-existence of VMs and containers on same platform DevOps Ready IT • Enable developer agility with IT & security policies • Avoid Shadow IT Turnkey Appliance for Enterprise Kubernetes Cisco Container Platform Single vendor Support • Fully supported by Cisco Global TAC • Single throat to choke for entire stack CISCO CONTAINER PLATFORM FOR HYPERFLEX
- 9. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public 9 Control Plane Data Plane VM VM VM Control Plane Kubernetes Automation Orchestration Operations HX Connect Cluster/ Machine Controllers VM VM VM Cluster 1 Kubernetes Cluster1 Workloads Cluster1 Ops Pod Pod Pod VM VM VM Cluster 2 Kubernetes Cluster2 Workloads Cluster2 Ops Pod Pod Pod Kubernetes Fluentd Prometheus Kibana Hyperflex Contiv Networking (Nexus 9K/ACI) HyperFlex IaaS (VMware, Compute, Storage) CISCO CONTAINER PLATFORM
- 10. 10 KUBERNETES ON NVIDIA GPUs Deploy and manage multi node, hybrid cloud infrastructure for GPU-accelerated applications • Orchestrate resources on heterogeneous GPU clusters, including DGX Systems and NVIDIA GPU-enabled cloud service providers • Optimize GPU cluster utilization with active health monitoring • Deploy wide range of applications using multiple container technologies such as Docker and CRI-O GPU-Aware Automation and Orchestration
- 11. 11 ORCHESTRATE AI WORKLOADS WITH KUBERNETES AND CISCO HYPERFLEX Support for NVIDIA Tesla V100, the most advanced data center GPU ever built Leverage Kubernetes on NVIDIA GPUs to automate and orchestrate AI workloads on Cisco HyperFlex Maximize utilization across hyperconverged infrastructure
- 12. 12 POWERING THE DEEP LEARNING ECOSYSTEM NVIDIA SDK Accelerates Every Major Framework COMPUTER VISION OBJECT DETECTION IMAGE CLASSIFICATION SPEECH & AUDIO VOICE RECOGNITION LANGUAGE TRANSLATION NATURAL LANGUAGE PROCESSING RECOMMENDATION ENGINES SENTIMENT ANALYSIS DEEP LEARNING FRAMEWORKS Mocha.jl NVIDIA DEEP LEARNING SDK developer.nvidia.com/deep-learning-software
Editor's Notes
- The evolution of computing drives industrial and societal change Each era of computing was triggered by a revolutionary new computing model ~1995: PC-Internet era kicked off by Microsoft-Intel PC, Netscape, and Yahoo — made computing available to 1 billion PC users ~2006: Mobile-cloud era ignited by the iPhone and Amazon AWS — computing available to 2.5 billion mobile users Today: GPU Deep Learning has ignited a new wave of computing where software can learn and machines can reason. Eventually, there will be trillions of intelligent devices — the era of AI is here.