Crossing the Performance Chasm with OpenPOWER Dr. Srini Chari Cabot Partners/IBM chari@cabotpartners.com #OpenPOWERSummit Join the conversation at #OpenPOWERSummit 1
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Agenda Key Technology Trends Cloud, HPC, Analytics, Social, Mobile and Internet of Things Centered Around Data Open Innovation Vital for Value Creation Data-Centric HPC Growing Rapidly Client Considerations in HPC Systems Evaluations System Attributes Impacting Real Life Performance Why the LINPACK Benchmark is Inadequate IBM Data Centric Approach and Solutions Why OpenPOWER Examples of Performance Gains Key Takeaways Join the conversation at #OpenPOWERSummit 3
Key Intertwined Technology Trends Join the conversation at #OpenPOWERSummit 4
Key Intertwined Technology Trends Cloud, High Performance Computing, Analytics, Social, Mobile and IoT Enterprise cloud growth - $7B (214) to $25B (217) Annual growth: Smart phones 2%. Mobile data 81% IoT at 12B today reaching over 1 Trillion in a decade Social media users - 1.79B (214) to 2.44B (218) DATA 2.5 exabytes (1 18 bytes) created daily. Individuals create 7% and enterprises manage 8% Annual spending 3% to reach $114B in 218 Join the conversation at #OpenPOWERSummit 5
What IT Must Consider to Deal with Data Volume Variety Velocity Veracity Vulnerability Visualize Virtualize V 8 Value Join the conversation at #OpenPOWERSummit 6
Extracting Value From Data with HPC Requires Open Innovation across the stack Join the conversation at #OpenPOWERSummit 7
HPC Drives Value Across Many Industries Overall HPC servers growing ~ 6.4% annually Traditional HPC Risk Analytics Life Sciences Oil and Gas Data-Centric HPC growing ~ 23.5% Emergency Response Fraud and Threat Detection Enhance Customer Experience Join the conversation at #OpenPOWERSummit 8
Considerations to Evaluate HPC Systems Not Just Point Benchmarks But Workflows Across the HPC Data Life Cycle Example in Seismic Processing Join the conversation at #OpenPOWERSummit 9
Total Value of Ownership Framework Holistic Cost Benefit Analysis for Entire HPC Workflow Value Delivered Business Value: e.g. customer revenues, new business models, compliance regulations, better products, increased business insight, faster time to market, and new breakthrough capability Operational Value: e.g. faster time to results, more accurate analyses, more users supported, improved user productivity, better capacity planning IT Value: e.g. improved system utilization, manageability, administration, and provisioning, scalability, reduced downtime, access to robust proven technology and expertise. Costs Incurred IT /Data Center Capital e.g. new servers, storage, networks, power distribution units, chillers, etc. Data Center Facilities e.g. land, buildings, containers, etc. Operational Costs: e.g. labor, energy, maintenance, software license, applications, etc. Other Costs: e.g. system management, deployment and training, downtime, migration, etc. Join the conversation at #OpenPOWERSummit 1
What Impacts Traditional HPC Performance Computer Aided Engineering Life Sciences Network Bandwidth Flops/Core Cores Structures Crash Fluids Network Bandwidth Flops/Core Quantum Chemistry Molecular Modeling Bioinformatics Cores Network Latency Memory Capacity Network Latency Memory Capacity I/O Performance Memory Bandwidth I/O Performance Memory Bandwidth Network Bandwidth Financial Services Low Latency Trading Flops/Core Monte Carlo Risk Analytics Cores Network Bandwidth Energy and Environmental Sciences Flops/Core Cores Reservoir Seismic Weather Network Latency Memory Capacity Network Latency Memory Capacity I/O Performance Memory Bandwidth I/O Performance Memory Bandwidth Join the conversation at #OpenPOWERSummit 11
Why LINPACK is Inadequate Most HPC Analytics Involve Sparse Matrices but LINPACK Solves Dense Matrix Problems LINPACK vs. HPC Analytics Flops/Core LINPACK Network Bandwidth HPC Analytics Cores Network Latency Memory Capacity I/O Performance Memory Bandwidth Join the conversation at #OpenPOWERSummit 12
Data Centric System Traditional System Design IBM s Data Centric Approach and Solutions Join the conversation at #OpenPOWERSummit 13
Major HPC Win for OpenPOWER Join the conversation at #OpenPOWERSummit 14
Performance / Core Performance / Core Key Benchmarks*: POWER8 2-2.5X Better 8 SPECint_rate26 (greater is better) 1.8 x Performance 6 SPECfp_rate26 (greater is better) 2.1 x Performance 7 6 5 5 4 4 3 3 2 2 1 1 Dell PowerEdge T62 2s/36c/72t Intel Xeon Haswell POWER S824 2s/24c/192t IBM POWER8 Dell PowerEdge T62 2s/36c/72t Intel Xeon Haswell POWER S824 2s/24c/192t IBM POWER8 Stream Triad (greater is better) 2.9 x Performance Terasort Big Data Hadoop (greater is better) Relative System Performance 35 3. GB/s 3 25 2 15 2.5 2. 1.5 2.5x 1 1. 5.5 Intel Xeon Haswell 2s/24c/48t IBM POWER8 2s/24c/192t. POWER8 Cisco Join the conversation at #OpenPOWERSummit 15
Max Paths (1 min) Nanoseconds / day Application Performance with POWER8* 1.4 2.6 X better Molecular Dynamics - NAMD apoa1 (greater is better) 1.4 x Performance 3 2.5 2 1.5 3 2.5 2 1.5 Seismic RTM (greater is better) 2.6 x Performance 2.6x 1 1.5.5 Intel E5-269 V3 2s/24c/2.6GHz Intel Xeon Haswell POWER S824L 2s/24c/3.6GHz IBM POWER8 Intel E5-269 V3 2s/24c/2.6GHz Intel Xeon Haswell POWER S822L 2s/24c/3.358GHz IBM POWER8 STAC A2 Options Pricing (greater is better) 2.7 x Performance PostGreSQL (higher is better) 3.E+7 2.5E+7 2.E+7 1.5E+7 1.E+7 5.E+6.E+ 4 x Intel E7-489 v2 2.8 GHz /1TB Intel Ivy Bridge EX Power S824 2s/24c/3.52GHz/1TB Join the conversation at #OpenPOWERSummit 16
Key Takeaways HPC is becoming more data-centric Traditional system evaluations based on point benchmarks such as LINPACK are inadequate Focus evaluation on cost-benefit analysis of workflow across HPC data lifecycle Many system features impact HPC performance Benefits of OpenPOWER HPC Offerings: Deliver Choice and Flexibility Minimize Costly Data Motion for Entire Workflow Accelerate Compute and Data Intensive Tasks with Lower TCO Provide Investment Protection Join the conversation at #OpenPOWERSummit 17
*Appendix - Additional Benchmark Detail SPECcpu (int_rate & fp_rate) SPECcpu26 results are based on best published results on E5-2699 v3 from the top 5 Intel system vendors (HP, Oracle, Lenovo, Dell, Fujitsu) submitted as of 9/8/214. For more information go to http://www.specbench.org/cpu26/results/. The IBM POWER8 published data is based on Power S824 2s/24c/3.5GHz POWER8. The x86 Xeon published data is based on Dell PowerEdge T62 2s/36c/2.3GHz E5-2699 v3. Hadoop Tersort IBM Analytics Stack: IBM Power System S822L; 8 nodes each with 24 cores / 192 threads, POWER8; 3.GHz, 512 GB memory, RHEL 6.5, InfoSphere BigInsights 3. Cisco Stack: 16 high-density Cisco UCS C24 M3 Rack Servers each with 16 cores / 32 threads, Intel Xeon E5-2665; 2.4 GHz, 256 GB of memory, Cisco UCS VIC 1225, and LSI 9266 8i with 24 1-TB SATA 72-rpm disk running Apache Hadoop open source distribution. Stream Triad The Stream Triad results are based on results reported in published papers. IBM POWER8: http://www.dcs.warwick.ac.uk/~sdh/pmbs14/pmbs14/workshop_schedule_files/2-performancepower8.pdf Intel Xeon E5-26 v3 http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=cb8qfjaa&url=http%3a%2f%2fdownload.boston.co.uk%2fd ownloads%2f9%2f3%2fc%2f93c22fd-d6d-46a4-9124-28c9e32f2533%2fintel- Whitepaper.pdf&ei=mLgBVbysL8KrggT774CICw&usg=AFQjCNFal5q5Vz2- ly6zbsakz2qppad1fg&sig2=3lzkttxekpvs2qw9ndxgfq&bvm=bv.8792726,d.exy STAC and all STAC names are trademarks or registered trademarks of Securities Technology Analysis Center LLC. https://stacresearch.com/system/files/asset/files/stac-a2%2intel%2composer%2on%24%2x%2ivt%2ex%2-%2intc1459.pdf Join the conversation at #OpenPOWERSummit 18