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CUSTOMER USE CASES

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Target Environments and Applications

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• Users seeking to simplify cluster complexities

• Applications that use large memory footprint (even with one processor)

• Applications that need multiple processors and shared memory

Manufacturing

CSM (Computational Structural Mechanics)

ABAQUS/ExplicitABAQUS/StandardANSYS MechanicalLSTC LS-DYNAALTAIR RadiossNASTRAN

CFD (Computational Fluid

Dynamics)

FLUENTANSYS CFXSTAR-CDAVL FIRETgrid

OtherinTrace OpenRT

Life Sciences

GaussianVASPAMBERSchrödinger JaguarSchrödinger GlideNAMDDOCKGAMESSGOLDmpiBLASTGROMACSMOLPROOpenEye FREDOpenEye OMEGASCM ADFHMMER

Energy

Schlumberger ECLIPSEParadigm GeoDepth3DGEO 3DPSDMNorsar 3D

OthersThe MathWorks MATLABROctaveWolfram MATHEMATICAISC STAR-P

EDA

MentorCadenceSynopsys

Finance

WombatKX

Weather Forecasting

MM5WRF

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SIMPLICITY

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3.1

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Customer Use Cases

• Customer: School of Engineering – University of Alabama

• Current platform: None. Just getting into HPC

• Problems:– Compute requirements were growing as number of users/students was growing

– No in-house skills to run x86 InfiniBand cluster

– Limited operational budget to hire additional sys-admin resources

• Applications: Commercial application (mostly Fluent and MATLAB)

• Solution:– 4 full blade chassis, each aggregated as a single system with 128 cores and 384 GB RAM and 5 TB of

internal storage

– Total: 64 physical nodes, 512 cores, 20TB storage - running as a cluster of 4 ‘Fat-Nodes’

• Benefits:– Low OPEX:

• No additional IT required for day-to-day operations

• The need to manage only 4 ‘Fat-Nodes’

• Internal storage is embedded in each ‘Fat-Node’

– Simplicity: InfiniBand performance without the complexityof managing such a solution

ENGINEERING FACULTY

LARGE SCALE DEPLOYMENTWITHOUT THE COMPLEXITY

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Customer Use Cases

• Customer: Mid-size Engineering Services Company

• Current platform: Multiple 2-socket workstations

• Problems:– Existing models (Abaqus) grow fast and can’t fit the engineers workstation

– Interested in running apps in batch at night

– No in-house skills to run x86 InfiniBand cluster (although the application runs nicely on InfiniBand cluster) . Can’t afford RISC systems

• Solution:– 4 Intel dual-processor Xeon systems to provide 128GB RAM, 8 sockets (16 cores) single virtual system

running Linux with vSMP Foundation

• Benefits:– Performance: Solution significantly faster than existing workstations. Performance is comparable to

cluster performance (using vendor benchmarks).

– Low OPEX: No IT required for day-to-day operation

– Versatility: Batch mode at night. Daytime jobs are executed on the systemwhile using the workstation for display only. Multi-user environment withperfect scaling – and sharing without performance degradation.

– Investment protection: Expected to expand the system by adding additional4 nodes (to a total of 256GB RAM, 32 cores)

ENGINEERING SERVICES COMPANY

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INNOVATION WITHOUT

COMPLEXITY

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SIMPLIFYING INTER-PROCESS

COMMUNICATION

Customer Use Cases

• Customer: Hedge Fund

• Current platform: Multiple 4-Socket Servers

• Problems:– A single 4-socket server did not provide enough performance required for customer business targets

– Multiple 4-socket servers required complex decomposition and introduced challenges in transferring data between processes in a short and deterministic time (low latency and small jitters)

• Ethernet based solution could not provide this / IB solution is too complex to manage and program for

– Co-location at exchanges for a solution comprised of multiple systems is complicate

• Applications: KX, WOMBAT, home-grown code

• Solution:– 16 Intel dual-processor Xeon systems to provide 0.5TB RAM, 32 sockets (128 cores) single virtual

system running Linux with vSMP Foundation

• Benefits:– Reduced latency and latency variance

– Simpler solution: Deploy and management of a single system

– Better utilization: Single system reduces resources fragmentation

– Simpler programming model: No need for specific InfiniBandprogramming

FINANCIAL SERVICES

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FLEXIBILITY

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3.2

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COST EFFECTIVE FLEXIBLE SOLUTION WITH HIGH

UTILIZATION

Customer Use Cases

• Customer: Hosted HPC resource provider

• Current platform: Clusters and SMP machines

• Problems:– Need to run MPI as well as OpenMP (shared memory) codes

– Large shared memory jobs require dedicated proprietary hardware

– Low utilization on shared memory systems

• Applications: A variety of commercial codes

• Solution:– Original: 4 systems, total of 8 sockets (32 cores) and 128GB RAM

– Solution was extended to 16 nodes

• Benefits:– Utilization: Rely on standard commodity hardware

– Flexibility: Using same system for both shared memoryand cluster benchmarks, resulting in high utilization

HOSTED HPC RESOURCE PROVIDER

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ELASTIC VM SOLUTION AIMED FOR DATA

INTENSIVE COMPUTING

Customer Use Cases

• Customer: San Diego Supercomputer Center (SDSC)

• Current platform: 8-socket AMD systems

• Problems:– Require an infrastructure for data intensive computing

– Need large memory system (TBs in size), depending on job need

– Require the ability to access quickly large amounts of storage

• Applications: A variety of data intensive codes (Astronomy, Genomics, Data Mining, etc..)

• Solution:– Initial Deployment: 4 ‘Super Nodes’, each with 768GB RAM, 128 cores, 10TB internal storage

– Complete Deployment (2011): 1,024 servers with vSMP Foundation for Cloud. Could be aggregated up to 32 ‘Super Nodes’ each nodes is 32 servers, resulting in 2TB RAM and 8TB of SSDs

– On demand allocation using web-request and fast (<10 minutes) provisioning

• Benefits:– Flexibility: Provision multiple ’Super Nodes’ of various

sizes according to need

– Performance: Extremely fast hierarchical memory solution: RAM Aggregated RAM Aggregated SSDs

SUPER COMPUTER CENTER

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CAPABILITY

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3.3

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Customer Use Cases

• Customer: Global Energy Company

• Current platform: x86 grid

• Problems:– Using in-house single-threaded simulation tools in throughput mode. Each simulation

memory footprint has grown over the years and sometimes (10%) exceeds 32GB.

– Application runs on x86 only

– Used to reschedule failed runs on large-memory systems

• Solution:– 6 Intel dual-processor Xeon systems to provide 192GB RAM, 12 sockets (48 cores) single virtual

system running Linux with vSMP Foundation

• Benefits:– Versatility: Both large and small workloads used concurrently on the same system

– Utilization: Higher utilization compared to grid due to lower infrastructure fragmentation

– Investment protection: Solution expanded by 100% since initial installation

GLOBAL ENERGY COMPANY

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SINGLE INFRASTRUCTURE FOR HORIZONTAL ANDVERTICAL APPLICATION SCALING – PLUG & PLAY

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SCALEUPAT SCALEOUT

PRICING

Customer Use Cases

• Customer: Formula1 team

• Current platform: Large-memory Itanium-based system

• Problems:– Need to generate large mesh as part of pre-processing of whole-car

simulation (FLUENT TGrid)

– Mesh requirements are ~200GB in size

– Expect to grow significantly within 12 months after initial deployment

– Would like to standardize on x86 architecture due to lower costs and open standards

• Solution:– 12 Intel dual-processor Xeon systems to provide 384GB RAM single virtual system running Linux with

vSMP Foundation

• Benefits:– Better performance: Solution evaluated and found to be faster than

alternative systems (x86 and non-x86)

– Cost: Significant savings compared to alternative system

– Versatility: Also being used to run FLUENT (MPI) as part of large cluster

– Investment protection: Solution can grow

FORMULA1 TEAM

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SIMPLE AND FLEXIBLE COST

EFFECTIVE SOLUTION

Customer Use Cases

• Customer: Weather forecasting service provider

• Current platform: SGI Altix with 32 cores

• Problems:– Need to run MPI as well as OpenMP codes

– System needs to be deployed remotely, and hence needs to be simple to manage

– Data processing flow is complex and requires transferring large amounts of data between steps

• Applications: MM5, WRF, MAWSIP, Home-grown code for data transformation

• Solution:– 4 Intel Nehalem dual socket blades, total of 8 sockets (32 cores) and 192GB RAM

– Internal storage

– Solution was extended to 8 blades, total of 16 sockets (64 cores) and 384GB RAM

• Benefits:– Performance: 2.5 X better performance on same # of cores (32)

– Simpler solution: Significantly reduced capital expense, allowedthe customer to have a higher # of cores

– Simplicity: Simple to manage by domain experts (weather forecast scientists)

– Dataflow remains within the system, leveraging internal storage

WEATHER FORECASTING SERVICE PROVIDER

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Customer Use Cases

• Customer: Large European semiconductor manufacturer

• Current platform: Proprietary large shared memory system + compute grid

• Problems:– Dedicated and proprietary systems were expensive

– Utilization and efficiency of the existing large memory system was low for throughput jobs

– The mix of throughput and large memory jobs required maintaining 2 separate environments

• Solution:– 8 Intel dual-socket (quad-core) Xeon systems to provide 300GB RAM single virtual system running

Linux with vSMP Foundation

• Benefits:– The ability to run large memory jobs when required

– Flexibility: Switch to between large memory and throughput jobs in an efficient way on the fly

– Consistency: Underlying hardware is aligned with standard hardware used for the rest of the compute grid

– Better utilization: Having a single system reduces resources fragmentation

– Performance: Leverage most recent Intel CPUs for large-memory jobs

SEMICONDUCTOR MANUFACTURER

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FLEXIBLE SYSTEM FOR THROUGHPUT AND LARGE MEMORY JOBS

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LARGE MEMORY FOR MULTI-THREADED PROGRAMMING

Customer Use Cases

• Customer: Medical Research Institute

• Current platform: HP Superdome System

• Problems:– Need to perform high performance image processing on very large MRI scans

– Scanned data for a single run is currently over 200GB. Memory requirements are expected to grow significantly with the introduction of full body scan with more sensors

– Would like to use and commercial tools for faster development

– Would like to standardize on x86 architecture due to lower costs and open standards

• Applications: Siemens CT processing, MATLAB, BLAS, Home-grown code, …

• Solution:– 16 Intel dual-processor Xeon systems to provide 1TB RAM, 32 sockets (128 cores) single virtual

system running Linux with vSMP Foundation

• Benefits:– Better performance: Solution evaluated and found to be faster

than any other alternative system

– Cost: Significant savings compared to alternative system (orderof magnitude)

– Versatility: Also being used for MPI jobs as part of large cluster

MEDICAL RESEARCH INSTITUTE

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SHARED MEMORY MULTI-THREADED PROGRAMMING

Customer Use Cases

• Customer: RWTH Aachen - Polytechnic University

• Current platform: 4 socket x86 server

• Problems:– Need to run auto-parallelized code (using OpenMP) with high core count

– Other solution found not to work:• Cannot afford proprietary SMP

• Cluster-OpenMP proved not to scale

– Has to use OpenMP for faster development (machine generated Fortran code)

• Applications: Home-grown codes (SHEMAT Suite, FIRE, …)

• Solution:– 13 Intel dual-processor Xeon systems to provide 26 sockets (104 cores)

– Single virtual system running Linux with vSMP Foundation

• Benefits:– Performance: Solution scales at over 95% efficiency

to 104 cores with OpenMP codes

– Cost: Significant savings compared to alternative solutions

– System scale: Largest x86 system available

ACADEMIC RESEARCH

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