Panasas: High Performance Storage for the Engineering Workflow



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9. LS-DYNA Forum, Bamberg 2010 IT / Performance Panasas: High Performance Storage for the Engineering Workflow E. Jassaud, W. Szoecs Panasas / transtec AG 2010 Copyright by DYNAmore GmbH N - I - 9

High-Performance Storage for the Engineering Workflow Terry Rush Regional Manager, Northern Europe.

Why is storage performance important? Example - Progression of a Single Job CAE Profile with non-parallel I/O 1998: Desktops single thread -- compute-bound read = 10 min compute = 14 hrs write = 35 min 5% I/O 2003: SMP Servers 8-way I/O significant 10 min 1.75 hrs 35 min 30% I/O 2008: HPC Clusters 32-way I/O-bound growing bottleneck 10 min 26 min 35 min 63% I/O NOTE: Schematic only, hardware and CAE software advances have been made on non-parallel I/O 2

The I/O problem 50000 90M Cell Simulation Elapsed Time in Seconds 37500 25000 12500 64-way 128-way 192-way Lower is better 37572 16357 10667 Linear Scalability 90 M Cells Solver scales linear as # of cores increase 0 0 0 0 0 0 0 0 0 0 File Read Solve File Write Total Time Source: Barb Hutchings Presentation at SC07, Nov 2007, Reno, NV

Read & Write Time increases with Core Count 50000 90M Cell Simulation Elapsed Time in Seconds 37500 25000 12500 0 64-way 128-way 192-way Lower is better 37572 16357 Linear Scalability 9670 10667 11288 6848 7676 4120 4453 0 0 0 90 M Cells Read and write I/O times increase with # of cores File Read Solve File Write Total Time Source: Barb Hutchings Presentation at SC07, Nov 2007, Reno, NV

Bigger cluster does not mean faster jobs 50000 90M Cell Simulation Elapsed Time in Seconds 37500 25000 12500 0 64-way 128-way 192-way Lower is better 37572 16357 Linear Scalability 9670 10667 11288 6848 7676 4120 4453 46145 3088131625 90 M Cells File Read Solve File Write Total Time Source: Barb Hutchings Presentation at SC07, Nov 2007, Reno, NV

Serial verses Parallel Serial I/O Schematic Parallel I/O Schematic Head node Compute Nodes Storage (Serial) Compute Nodes Storage (Parallel) 6

Parallel storage I/O returns scalability 50000 46145 90M Cell Simulation 64-way 128-way 192-way Elapsed Time in Seconds 37500 25000 12500 3088131625 38656 17442 11759 Lower is 90 M Cells better ~2x PanFS gains vs. serial I/O ~3x about 3x on 192 cores 0 v6.2-1 Write v12 PanFS - 1 Write v6.2-100 W 0 0 Source: Barb Hutchings Presentation at SC07, Nov 2007, Reno, NV

Two Measures of Performance Single wide-parallel job vs. multiple instances of less-parallel jobs Often referenced in HPC industry as capability vs. capacity computing Both important, but multi-user capacity computing more common in practice Example: parameter studies and design optimization usually based on capacity computing since it would be economically impractical with capability approach File system performance characteristics for capability vs. capacity Capability: Many cores writing to a large single file Capacity: A few cores writing into a single file, but multiple instances PanFS scales I/O for the capability job, and provides multi-level scalable I/O for the capacity jobs (each job parallel I/O -- multiple jobs writing to PanFS in parallel) NFS has single, serial data path for all capacity and capability solution writes Capability Computing Capacity Computing Compute nodes PanFS and storage Single Large Job Multiple Job Instances

What is Parallel Storage? Parallel NAS: Next Generation of HPC File System Server NFS Clustered NFS File Server File Server File Server Parallel NFS DAS: Direct Attached Storage NAS: Network Attached Storage Clustered Storage: Multiple NAS file servers managed as one Parallel Storage: File servers not in data path. Performance bottleneck eliminated.

Typical Complex Parallel Storage Configuration Linux Clients FC SAN OSS Object Storage Servers Controllers GE/10GE/IB Network 10GE/IB FC FC SAN OSS Object Storage Servers Controllers FC SAN MDS Metadata Server (Active/Passive) OSS Object Storage Servers Controllers

Panasas Solution Linux Clients Integrated solution -Panasas File System -Panasas HW and SW -Panasas Service/Support -Single management point GE/10GE/IB Network Simplified Manageability -Easy and quick to install -Single Fabric -Single Web GUI/CLI -Automatic capacity Balancing Scalable Performance -Scalable Metadata -Scalable NFS/CIFS -Scalable Reconstruction -Scalable Clients -Scalable BW High Availability -Metadata failover -NFS failover -Snapshots -NDMP 11

What else besides fast I/O? Single Global Namespace for Easy Management Remove artificial, physical and logical boundaries Eliminates need to maintain mount scripts or move data Cluster 1 Cluster 3 Cluster 1 Cluster 3 Cluster 2 Cluster 2 Single Global Namespace Archived Files Cluster 2 Results Cluster 3 Results Traditional Storage Networks Panasas Storage Cluster 12

Removing Silos of Storage Historic technical computing storage problem Multiple applications and users across the workflow creates costly and inefficient storage silos by application and by vendor Supercomputing HPC Linux Cluster Technical Apps Linux/Windows/Unix High Capacity Store Linux/Windows/Unix High Throughput Sequential I/O Low $/GB Massive Capacity High IOPs Random I/O 13

Removing Silos of Storage single global file system High performance scale-out NAS solutions PanFS Storage Operating System delivers exceptional performance, scalability & manageability The Technical Enterprise Supercomputing HPC Linux Cluster Archive Linux/Windows/Unix Technical Apps Linux/Windows/Unix PanFS High Throughput Sequential I/O Low $/GB Massive Archive High IOPs Random I/O 14

Typical Panasas Parallel Storage Workflow: Engineering Compute Cluster(s) Panasas Parallel Storage Unix/Windows Desktops Clustered NFS or CIFS Serial or Parallel I/O with pnfs Typical Applications: Abaqus, Nastran, FLUENT, STAR-CD, etc. Single Global Namespace with single or multiple volumes /work, /home.. Typical Applications: ProEngineer, CATIA, etc. 15

Unified Parallel Storage for the Engineering Workflow Panasas Unified Parallel Storage for Leverage of HPC investments Performance that meets growing I/O demands Management simplicity and configuration flexibility for all workloads Scalability for fast and easy non-disruptive growth Reliability and data integrity for long term storage NFS/CIFS Parallel I/O Data Access Panasas Unified Storage Computation

Panasas Overview Founded April 1999 by Prof. Garth Gibson, CTO Locations US: HQ in Fremont, CA Development center in Pittsburgh, PA EMEA: Sales offices in UK, France & Germany APAC: Sales offices in China & Japan First Customer Shipments October 2003, now serving over 400 customer sites with over 500,000 server clients in twenty-seven countries 13 patents issued, others pending Key Investors Speed with Simplicity and Reliability - Parallel File System and Parallel Storage Appliance Solutions

Broad Industry and Business-Critical Application Support Energy Government Universities Aerospace Seismic Processing Reservoir Simulation Interpretation Imaging & Search Stockpile Stewardship Weather Forecasting High Energy Physics Molecular Dynamics Quantum Mechanics Fluid Dynamics (CFD) Structural Mechanics Finite Element Analysis Finance Industrial Mfg Automotive Bio/Pharma Credit Analysis Risk Analysis Portfolio Optimization EDA Simulation Optical Correction Thermal Mechanics Crash Analysis Fluid Dynamics Acoustic Analysis BioInformatics Computation Chemistry Molecular Modeling 18

Customer Success Highlights Almost half the Formula One teams use Panasas Five of the top six Oil & Gas companies in the world use Panasas Every Intel chip since 2006 has been designed using Panasas The world s first Petascale system, RoadRunner, uses Panasas The world s three largest genomic data centres use Panasas The largest aircraft manufacturer in the world uses Panasas Leading Universities including Cambridge, Oxford, Stanford & Yale use Panasas The world s largest Hedge Fund uses Panasas for risk analysis Energy Automotive Aerospace Bio Science Pharma Finance University Research Government

20 Some Panasas Customers

Panasas Differentiation Leader in high performance parallel storage for businesscritical applications Optimized for demanding storage applications in the energy, government, finance, manufacturing, bioscience and core research sectors Panasas PanFS Parallel file system with integrated RAID protection Most scalable performance in the industry Appliance-like scalable hardware architecture for large-scale storage deployments Highly integrated management suite 21

Integrated RAID Reliability RAID Implementation Object RAID Benefit System intelligently assigns RAID levels based on file size Automatic transitioning from RAID 1 to RAID 5 without re-striping High performance file reconstruction (vs. drive sector reconstruction) Per File RAID Rebuild in hours Parallel rebuild all blade sets participate in RAID rebuilds RAID within the individual drive as well as across drives Horizontal (Blade) and Vertical (Disk) Parity RAID Improves internal ECC capabilities Predicatively solves media errors Significantly lowers drive failure probability Only Panasas includes RAID data protection as a component of its file system 22

Appliance-Like, Modular Hardware Design DirectorBlade Add blades, chassis, or entire racks, without system disruption, to extend performance and capacity StorageBlade 11-slot, 4U Chassis CPU, cache, network Manages system activity Clustered metadata services CPU, cache, data storage Enables parallel reads/writes Advanced caching algorithms 23 40U Rack Up to 10 chassis Up to 400TB (currently) Capacity expansion from 40TB to 4PB Aggregate performance scales from 1.5GB/s to 150GB/s, the highest performance available 10GbE & IB networks Additional storage seamlessly integrates Field replaceable Low TCO Rear of Chassis

Panasas Hardware Technology Multi-core Intel Processor Large DRAM Cache Multi-core Intel Processor Enterprise Class 2TB SATA Drive I/O Servers Large DRAM Cache RAID Controller SATA Drive Intel SSD Enterprise Class Large DRAM Cache 2TB SATA Drives 60 Drives per 4U Shelf Multi-core Intel Processor PAS DirectorBlade PAS PAS PAS 7 & 9 HC StorageBlade 8

Panasas Product Family Same Panasas software, management interface, single name space SSD PAS HC PAS 7 PAS 8 PAS 9 (Per 42U Rack) (Per 4U Shelf) (Per 4U Shelf) (Per 4U Shelf) - 960TBs Raw Capacity - 40TBs Raw Capacity - 40TBs Raw Capacity - 600MB/sec Aggregate B/W - 5GB/sec Aggregate B/W - 350MB/sec Aggregate B/W - 600MB/sec Aggregate B/W - Unlimited Scalability - RAID 6 - RAID 1, 5 & 10 - RAID 1, 5 & 10 - RAID 1, 5 & 10 - Unlimited Scalability - Unlimited Scalability - HA & Snapshots - HA & Snapshots - Entry Level $/GB 500TBs+ - Entry Level $/GB Sub 500TB - Unlimited Scalability - 21,000 IOPS

High-Performance Storage for the Engineering Workflow the Panasas Difference 26

Thank You! www.panasas.com See us on stand 1 27