revolutionising high performance computing

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revolutionising high

performance computing

With supermicro solutions

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nvidia

®

tesla

®

gpus are revolutionizing

computing

The high performance computing (HPC) industry’s need for computation is increasing, as large and complex computational problems become commonplace across many industry segments. Traditional CPU technology, however, is no longer capable of scaling in performance sufficiently to address this demand.

The parallel processing capability of the GPU allows it to divide complex computing tasks into thousands of smaller tasks that can be run concurrently. This ability is enabling computational scientists and researchers to address some of the world’s most challenging computational problems up to several orders of magnitude faster.

Conventional CPU computing architecture can no longer support the growing HPC needs.

Source: Hennesse]y &Patteson, CAAQA, 4th Edition. 10000

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100x performance advantage

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25% year

52% year

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CPU GPU

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hybrid

computing

latest gpu superserver

®

_{, superBlade}

®

_and

nvidia

®

_{maximus™ certified superWorkstation}

solutions from supermicro

®

accelerating research, scietific, engineering, computational finance

and design applications

1u superserver®

1027Gr-TQF

up to 4x gpus

2027Gr-TrF

up to 6x gpus

SBI-7127rG

up to 20x gpus

7047Gr-TrF

4x nvidia tesla gpus 1x nvidia Quadro gpu

2u superserver® _{7u superBlade}® _{superWorkstation}

Super Micro Computer, Inc. (NASDAQ: SMCI), a global leader in high-performance, high-efficiency server technology and green computing, will showcase its latest graphics processing unit (GPU) enabled X9 server and workstation solutions at the NVIDIA GPU Technology Conference (GTC) May 14-17 in San Jose, CA. Supermicro®_{s GPU solutions}

support Intel®_Xeon®_{E5-2600 processors and feature}

greater memory capacity (up to 256GB for servers and 512GB in workstations), higher performance I/O and connectivity with PCI-E 3.0, 10GbE and 4x QDr (40Gb) InfiniBand support (GPU SuperBlade) as well as innovative energy efficient power saving technologies. Supermicro X9 solutions also feature the highest density GPU computing available today. The non-blocking architecture supports 4 GPUs per 1U in a standard, short depth 32”, rack chassis. The SuperBlade can fit 30 GPUs in 7U- another industry

These select GPU enabled servers and workstations are a sampling of Supermicro’s vast array of GPU solutions. Visit us at the San Jose McEnery Convention Center, May 14-17 in GTC Booth #75 to see Supermicro’s latest GPU products. For a complete look at Supermicro’s extensive line of high

performance, high efficiency GPU solutions, visit

www.supermicro.com/GPU or go to

www.supermicro.com/SuperWorkstations to keep up with Supermicro’s evolving line of NVIDIA Maximus powered SuperWorkstations.

first from Supermicro®_{. Combined with the latest}

GPUs based on NVIDIA Kepler architecture, the X9 platform offers industry professionals one of the most powerful, accelerated and ‘green’ computing solutions available on the market.

“Supermicro®_{is transforming the high performance}

computing landscape with our advanced, high-density GPU server and workstation platforms,” said Charles Liang, President and CEO of Supermicro®_.

“At GTC, we are showcasing our new generation X9 SuperServer®_{, SuperBlade}TM_{and latest NVIDIA}

Maximus certified SuperWorkstation systems which deliver groundbreaking performance, reliability, scalability and efficiency. Our expanding lines of GPU-based computing solutions empower scientists, engineers, designers and many other professionals with the most cost-effective access to supercomputing performance.”

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NVIDIA®_TESLATM / HybrID coMpuTINg SoLuTIoNS 2010

SUPE

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superWorkstations

server grade performance for multimedia,

engineering, and scientific applications

performance. efficiency.

expandaBility. reliaBility

• Optimized Solutions:

Video Editing, Digital Content Creation, MCAD, CAE, Financial, SW Development, Scientific, Oil and Gas

• Whisper-Quiet 21dB Acoustics models

• Up to Redundant Platinum Level (95%+) Digital

Power Supplies

• Best Value for your IT Investment

• Up to 512 GB DDR3 memory and 8 Hot-Swap HDDs • Up to 5 GPUs supported with PCI-E 3.0

• Server-Grade Design for 24x7 Operation

The 7047Gr-TrF is Supermicro’s latest high-end, enterprise-class X9 SuperWorkstation, with NVIDIA Maximus certification. This system accelerates

design and visualization tasks with an NVIDIA Quadro

GPU, while providing dedicated processing power for simultaneous compute intensive tasks such as simulation and rendering with up to four NVIDIA Tesla C2075 GPUs. The upcoming 7047Gr-TPrF SuperWorkstation supports passively cooled GPUs making it ideal for high performance trading (HPT) applications. X9 systems feature dual Intel®_Xeon® E5-2600 family processors, maximized memory and

non-blocking native PCI-E 3.0 configurations along

with redundant Platinum level high-efficiency (94%+)

power supplies.

www.supermicro.com/SuperWorkstations

7047gr-trf

• NVIDIA®_{Maximus™ Certified supporting NVIDIA}®

Quadro®_{and up to 4 NVIDIA}®_Tesla®_{for real-time}

3D design, visualization, simulation and accelerated

rendering

• GPU Server for Mission-critical applications, enterprise

server, large database, e-business, on-line transaction processing, oil & gas, medical applications

• Dual Intel®_Xeon®_{processor E5-2600 family; Socket r}

(LGA 2011)

• 8 Hot-swap 3.5“ SATA HDD Bays, 3x 5.25“ peripheral

drive bays, 1x 3.5“ fixed drive bay

• 16 DIMMs support up to 512GB DDR3 1600MHz reg.

ECC memory

• 4 (x16) PCI-E 3.0 (support 4 double width GPU cards), 2 (x8) PCI-E 3.0 (1 in x16), and 1 (x4) PCI-E 2.0 (in x8)

slot

• I/O ports: 2 GbE, 1 Video, 1 COM/Serial, 9 USB 2.0 • System management: Built-in Server management

tool (IPMI 2.0, KVM/media over LAN) with dedicated LAN port

• 4 Hot-swap PWM cooling fans and 2 Hot-swap rear

fans

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high performance gpu servers

the foundation of a flexiBle and efficient hpc &

data center deployment

Brains, Brains and more Brains!!!

X9 SuperServers which provide a wide range

of configurations targeting high performance computing (HPC) applications. Systems include the 1027Gr-TQF offering up to 4 double-width GPUs in 1U for maximum compute density in a compact 32” short depth, standard rack mount format. The 2U 2027Gr-TrF supports up to 6 GPUs and is ideal for scalable, high performance computing clusters

in scientific research fields with a 2027Gr-TrFT model available supporting dual-port 10GBase-T for increased bandwidth and reduced latency. The GPU SuperBlade SBI-7127rG packs the industry’s highest compute density of 30 GPUs in 7U delivering ultimate processing performance for applications such as oil and gas exploration.

Professor Wu Feng of Virginia Tech‘s Synergy Laboratory is the main Brain behind VT‘s latest and greatest Supercomputer, HokieSpeed. HokieSpeed is a Supermicro supercluster of SuperServer®

2026GT-TrFs with thousands of CPU/GPU cores or „brains“.

In Nov. 2011, HokieSpeed ranked 11th for energy efficiency on the Green500 List and 96th on the world‘s fastest supercomputing Top500 List. Dr. Feng‘s Supermicro powered HokieSpeed boasts single-precision peak of 455 teraflops, or 455 trillion operations per second, and a double-precision peak of 240 teraflops, or 240 trillion operations per second.

2027gr-trft / 2027gr-trf (-fm475/-fm409)

• GPU Server, Mission-critical app., enterprise server,

large database, e-business, on-line transaction processing, oil & gas, medical app.

(LGA 2011)

• 10 Hot-swap 2.5“ SATA HDD Bays (4 SATA2, 6 SATA3) • 8 DIMMs support up to 256GB DDR3 1600MHz reg. ECC

memory

• 4 (x16) PCI-E 3.0 (support 4 double width GPU cards), 1 (x8) PCI-E 3.0 (in x16), and 1 (x4) PCI-E 2.0 (in x16) slots • I/O ports: 2 GbE/10GBase-T (TRFT), 1 Video, 1 COM/

Serial, 2 USB 2.0

• 5 heavy duty fans w/ optimal fan speed control • 1800W Redundant Platinum Level Power Supplies • „-FM475/409“: 4x NVIDIA M2075/M2090 GPU cards

integrated

* use your phone, smartphone or tablet pc with Qr reader software to read the Qr code.

Watch video*:

superservers in action:

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superservers

1017gr-tf (-fm275/-fm209)

oil & gas, financial, 3D rendering, chemistry, HPC

• Single Intel®_Xeon®_{processor E5-2600 family; Socket r}

(LGA 2011)

• 6 Hot-swap 2.5“ SATA HDD Bays

• 8 DIMMs support up to 256GB DDR3 1600MHz reg. ECC

memory

• 2 (x16) PCI-E 3.0 (for 2 GPU cards) and 1 (x8) PCI-E 3.0 slot • I/O ports: 2 GbE, 1 Video, 2 USB 2.0

• 8 counter rotating fans w/ optimal fan speed control • 1400W Platinum Level Power Supply w/ Digital Switching • „-FM175/109“: 1x NVIDIA M2075/M2090 GPU card

integrated

• „-FM275/209“: 2x NVIDIA M2075/M2090 GPU cards

integrated

5017gr-tf (-fm275/-fm209)

• Single Intel®_Xeon®_{processor E5-2600 family; Socket r}

(LGA 2011)

• 3 Hot-swap 3.5“ SATA HDD Bays

memory

• 2 (x16) PCI-E 3.0 (for 2 GPU cards) and 1 (x8) PCI-E 3.0

(for IB card)

• I/O ports: 2 GbE, 1 Video, 2 USB 2.0

• 8 counter rotating fans w/ optimal fan speed control • 1400W Platinum Level Power Supply w/ Digital Switching • „-FM175/109“: 1x NVIDIA M2075/M2090 GPU card

integrated

1027gr-trft/1027gr-trf (-fm375/-fm309) /

1027gr-tsf

(LGA 2011)

• 4 Hot-swap 2.5“ SATA2/3 HDD Bays

memory

• 3 (x16) PCI-E 3.0 and 1 (x8) PCI-E 3.0 (in x16) slots • I/O ports: 2 GbE/10GBase-T (TRFT), 1 Video, 1 COM/

Serial, 2 USB 2.0

• 10 heavy duty fans w/ optimal fan speed control • 1800W Redundant Platinum Level Power Supplies (TRF) • 1800W Platinum Level Power Supply (TSF)

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SUPE

rbl

Ad

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Sol

U

tion

S

gpu superBlade

®

_solutions

sBi-7126tg

• Up to 20 GPU + 20 CPU per 7U!

• Up to 2 Tesla M2090/M2070Q/M2070/2050 GPU • Up to 2 Intel®_Xeon®_{5600/5500 series processors}

• Up to 96GB DDR3 1333/1066 ECC DIMM • 1 internal SATA Disk-On-Module • 1 USB flash drive

• 2 PCI-E 2.0 x16 or 2 PCI-2.0 x8 or 2 PCI-2.0 x8

(Full-height/ maximum length 9.75“)

• Onboard BMC for IPMI 2.0 support - KVM over IP, remote

Virtual Media

• Dual IOH per blade

• Dual 40Gb InfiniBand or 10Gb Ethernet supported via optional mezzanine card

• Dual-port Gigabit Ethernet NIC • Redundant GBX connectors

sBi-7127rg

• Up to 120 GPU + 120 CPU per 42U Rack!

• Up to 2 Tesla M2090/M2075/M2070Q/M2070/2050 GPU • Up to 2 Intel®_Xeon®_{E5-2600 series processors}

• Up to 256GB DDR3 1600/1333/1066 ECC DIMM • 1 internal SATA Disk-On-Module

• 1 USB flash drive

• 2 PCI-E 2.0 x16 Full-heigh Full-length Expansion Slots • Onboard BMC for IPMI 2.0 support - KVM over IP, remote

Virtual Media

• 4x QDR (40Gb) InfiniBand or 10Gb Ethernet supported via optional mezzanine card

• Dual-port Gigabit Ethernet NIC

space optimization

When housed within a 19” EIA-310D industry-standard 42U rack, SuperBlade®_{servers reduce server footprint in}

the datacenter. Power, cooling and networking devices are removed from each individual server and positioned to the rear of the chassis thereby reducing the required amount of space while increasing flexibility to meet changing business demands. Up to twenty DP blade nodes can be installed in a 7U chassis. Compared to the rack space required by twenty individual 1U servers, the SuperBlade®_{provides over 65% space savings.}

Supermicro®_{offers GPU blade solutions optimized}

for HPC applications, low-noise blade solutions for offices and SMB as well as personal supercomputing

applications. With acoustically optimized thermal and

cooling technologies it achieves < 50dB with 10 DP server blades and features 100-240VAC, Platinum

Level high-efficiency (94%+), N+1 redundant power

supplies.

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access the poWer of gpu computing With off-the-shelf,

ready to deploy tesla gpu cluster

turnkey preconfigured

gpu clusters

ready-to-use solutions

for science and research

These preconfigured solutions from Supermicro and NVIDIA provide a powerful tool for researchers and scientists to advance their science through faster simulations. GPU Test Drive is the easiest way to start using GPUs that offer supercomputing scale HPC performance at substantially lower costs and power.

Experience a significant performance increase in a wide range of applications from various scientific domains. Supercharge your research with preconfigured Tesla

GPU cluster today!

42 tflops

10 tflops

20 tflops

gpu nodes: 4

cpu: 2x Westmere X5650 2.66GHz

memory: 24 GB per node

default gpu/node: 2x M2090

network cards/node: 1x InfiniBand

storage/node: 2x 500GB HDD (1TB/Node)

srs-14urks-gpus-11

gpu nodes: 8 + 1 Head node

memory: 48 GB per node default gpu/node: 2x M2090

storage/node: 2x 500GB HDD (1TB/Node)

srs-14urks-gpus-12

gpu nodes: 16 + 1 Head node

memory: 48 GB per node default gpu/node: 2x M2090

storage/node: 2x 1TB HDD (2TB/ Node)

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hybrid

computing

tesla k10 gpu computing accelerator ― Optimized

for single precision applications, the Tesla K10 is a throughput monster based on the ultra-efficient Tesla Kepler. The accelerator board features two Tesla Kepler and delivers up to 2x the performance for single precision applications compared to the previous generation Fermi-based Tesla M2090 in the same power envelope. With an aggregate performance of

4.58 teraflop peak single precision and 320 gigabytes

per second memory bandwidth for both GPUs put together, the Tesla

K10 is optimized for

computations in seismic, signal, image processing, and video analytics.

tesla k20 gpu computing accelerator ― Designed for double precision applications and the broader supercomputing market, the Tesla K20 delivers 3x the double precision performance compared to the previous generation Fermi-based Tesla M2090, in the same power envelope. Tesla K20 features a single Tesla Kepler that includes the Dynamic Parallelism and Hyper-Q features. With more than one teraflop peak double precision performance, the Tesla K20 is ideal for a wide range of high performance computing

workloads including climate and weather modeling, CFD, CAE, computational physics, biochemistry simulations, and computational finance.

technical specifications

TESLA K102 _{TESLA K20}

Peak double precision floating point

performance (board) 0.19 teraflops To be announced Peak single precision floating point

performance (board) 4.58 teraflops To be announced

Number of GPUs 2 x GK104s 1 x GK110

CUDA cores 2 x 1536 To be announced

Memory size per board (GDDR5) 8 GB To be announced

Memory bandwidth for board (ECC off)3 _{320 GBytes/sec} _{To be announced}

GPU Computing Applications Seismic, Image, Signal Processing,

Video analytics

CFD, CAE, Financial computing, Computational chemistry and Physics, Data analytics, Satellite imaging, Weather modeling

Architecture Features SMX SMX, Dynamic Parallelism, Hyper-Q

System Servers only Servers and Workstations.

Available May 2012 Q4 2012

1 products and availability is subject to confirmation

2 Tesla K10 specifications are shown as aggregate of two GPUs.

3_{With ECC on, 12.5% of the GPU memory is used for ECC bits. So, for example, 6 GB total memory yields 5.25 GB of user}

supermicro is committed

to support

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Tesla®_Kepler_―_{World’s fastest and most power}

efficient x86 accelerator

With the launch of Fermi GPU in 2009, NVIDIA ushered in a new era in the high performance computing (HPC) industry based on a hybrid computing model where CPUs and GPUs work together to solve computationally-intensive workloads. And in just a couple of years, NVIDIA Fermi GPUs powers some of the fastest supercomputers in the world as well as tens of thousands of research clusters globally. Now, with the new Tesla Kepler, NVIDIA raises the bar for the HPC industry, yet again.

Comprised of 7.1 billion transistors, the Tesla Kepler is an engineering marvel created to address the most daunting challenges in HPC. Kepler is designed from the ground

up to maximize computational performance with superior

power efficiency. The architecture has innovations that make hybrid computing dramatically easier, applicable to a broader set of applications, and more accessible. Tesla Kepler is a computational workhorse with teraflops of integer, single precision, and double precision performance and the highest memory bandwidth. The first GK110 based product will be the Tesla K20 GPU computing accelerator.

Let us quickly summarize three of the most important

features in the Tesla Kepler: SMX, Dynamic Parallelism, and Hyper-Q. For further details on additional

fastest, most efficient hpc architecture

architectural features, please refer to the Kepler GK110 whitepaper.

smx — next generation

streaming multiprocessor

At the heart of the Tesla Kepler is the new SMX unit, which comprises of several architectural innovations that make it not only the most powerful Streaming Multiprocessor (SM) we’ve ever built but also the most programmable and power-efficient.

dynamic parallelism —

creating Work on-the-fly

One of the overarching goals in designing the Kepler GK110 architecture was to make it easier for developers to more easily take advantage of the immense parallel processing capability of the GPU.

To this end, the new Dynamic Parallelism feature enables the Tesla Kepler to dynamically spawn new threads by adapting to the data without going back to the host CPU. This effectively allows more of a program to be run directly on the GPU, as kernels now have the ability to independently launch additional workloads as needed. Any kernel can launch another kernel and can create the necessary streams, events, and dependencies needed to process additional work without the need for host CPU interaction. This simplified programming model is

easier to create, optimize, and maintain. It also creates

a programmer friendly environment by maintaining the same syntax for GPU launched workloads as traditional CPU kernel launches.

Dynamic Parallelism broadens what applications can now accomplish with GPUs in various disciplines.

Applications can launch small and medium sized

parallel workloads dynamically where it was too expensive to do so previously.

Figure 1: SMX: 192 CUDA cores, 32 Special Function Units (SFU), and 32 Load/Store units (LD/ST)

CONTROL LOGIC CONTROL LOGIC

SM

FERMI

32 CORES 192 CORES

SMX

KEPLER

3X

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hyper-Q — maximizing the gpu resources

Hyper-Q enables multiple CPU cores to launch work on a single GPU simultaneously, thereby dramatically

increasing GPU utilization and slashing CPU idle times.

This feature increases the total number of connections between the host and the the Tesla Kepler by allowing 32 simultaneous, hardware managed connections, compared to the single connection available with Fermi. Hyper-Q is a flexible solution that allows connections for both CUDA streams and Message Passing Interface (MPI) processes, or even threads from within a process. Existing applications that were previously limited by false dependencies can see up to a 32x performance increase without changing any existing code.

Hyper-Q offers significant benefits for use in MPI-based parallel computer systems. Legacy MPI-MPI-based algorithms were often created to run on multi-core CPU-based systems. Because the workload that could be efficiently handled by CPU-based systems is generally smaller than that available using GPUs, the amount of work passed in each MPI process is generally insufficient to fully occupy the GPU processor.

While it has always been possible to issue multiple MPI processes to concurrently run on the GPU, these processes could become bottlenecked by false dependencies, forcing the GPU to operate below peak efficiency. Hyper-Q removes false dependency bottlenecks and dramatically increases speed at which MPI processes can be moved from the system CPU(s) to the GPU for processing.

Hyper-Q promises to be a performance boost for MPI applications.

conclusion

Tesla Kepler is engineered to deliver ground-breaking performance with superior power efficiency while making GPUs easier than ever to use. SMX, Dynamic Parallelism, and Hyper-Q are three important innovations in the Tesla Kepler to bring these benefits to reality for our customers. For further details on additional architectural features, please refer to the Kepler GK110 whitepaper at

www.nvidia.com/kepler

CPU GPU CPU GPU

DYNAMIC PARALLELISM

Figure 3: Hyper-Q allows all streams to run concurrently using a separate work queue. In the Fermi model, concurrency was limited due to intra-stream dependencies caused by the single hardware work queue.

Figure 2: Without Dynamic Parallelism, the CPU launches every kernel onto the GPU. With the new feature, Tesla Kepler can now launch nested kernels, eliminating the need to communicate with the CPU.

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CUDA architecture has the industry’s most robust language and API support for GPU computing

developers, including C, C++, OpenCL, DirectCompute,

and Fortran. NVIDIA Parallel Nsight, a fully integrated development environment for Microsoft Visual Studio is also available. Used by more than six million developers worldwide, Visual Studio is one of the world’s most popular development environments for Windows-based applications and services. Adding functionality specifically for GPU computing developers, Parallel Nsight makes the power of the GPU more accessible than ever before. The latest version - CUDA 4.0 has seen a host of new exciting features to make parallel computing easier. Among them the ability to relieve bus traffic by enabling GPU to GPU direct communications.

cuda

integrated development environment

research &

education liBraries

tools & partners all major

platforms

mathematical packages languages

& apis consultants, training, &

certification

programming environment

for gpu computing

nvidia’s cuda

Order personalized CUDA education course at:

www.parallel-computing.pro

Watch video*:

pgi accelerator, technical presentation at sc11

accelerate your code easily

With openacc directives

get 2x speed-up in 4 Weeks or less

Accelerate your code with directives and tap into the hundreds of computing cores in GPUs. With directives, you simply insert compiler hints into your code and the compiler will automatically map compute-intensive portions of your code to the GPU.

By starting with a free, 30-day trial of PGI directives today, you are working on the technology that is the foundation of the OpenACC directives standard. OpenACC is:

• easy: simply insert hints in your codebase

• open: run the single codebase on either the CPU or GPU

• powerful: tap into the power of GPUs within hours

openacc directives

The OpenACC Application Program Interface describes a collection of compiler directives to specify loops and

regions of code in standard C, C++ and Fortran to be

offloaded from a host CPU to an attached accelerator, providing portability across operating systems, host CPUs and accelerators.

The directives and programming model defined in this document allow programmers to create

high-level host+accelerator programs without the need to explicitly initialize the accelerator, manage data or

program transfers between the host and accelerator, or initiate accelerator startup and shutdown.

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hybrid

computing

What is gpu computing

GPU computing is the use of a GPU (graphics processing unit) to do general purpose scientific and engineering comp

history of gpu computing

Graphics chips started as fixed function graphics pipelines. Over the years, these graphics chips became increasingly programmab

relativ

e

perf

ormanc

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sc

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e

(normalized ns/da

y)

1,5

1,0

0,5

192 Quad-core cpus 2 Quad-core cpus + 4 gpus 50% Faster

with GPUs

JAC NVE Benchmark

(left) 192 Quad-Core CPUs simulation run on Kraken Supercomputer (right) Simulation 2 Intel Xeon Quad-Core CPUs and 4 Tesla M2090 GPUs

gpu acceleration in life sciences

tesla

®

_{Bio WorkBench}

The NVIDIA Tesla Bio Workbench enables biophysicists and computational chemists to push the boundaries of life sciences research. It turns a standard PC into a “computational laboratory” capable of running complex bioscience codes, in fields such as drug discovery and DNA sequencing, more than 10-20 times faster through the use of NVIDIA Tesla GPUs.

It consists of bioscience applications; a community site for downloading, discussing, and viewing the results of these applications; and GPU-based platforms.

Complex molecular simulations that had been only possible using supercomputing resources can now

be run on an individual workstation, optimizing the

scientific workflow and accelerating the pace of research. These simulations can also be scaled up to GPU-based clusters of servers to simulate large molecules and systems that would have otherwise required a supercomputer.

Applications that are accelerated on GPUs include:

• Molecular Dynamics &

Quantum chemistry

AMBEr, GrOMACS, HOOMD, LAMMPS, NAMD, TeraChem (Quantum Chemistry), VMD

• Bio informatics

BLASTP, EC,

MEME, CUDASW++

Waterman), GPU-HMMEr, MUMmerGPU

For more information, visit:

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192 Quad-core cpus

46 ns/day

4 tesla m2090 gpus + 2 cpus

69 ns/day

amBer: node processing comparison

gromacs

GrOMACS is a molecular dynamics package designed primarily for simulation of biochemical molecules like proteins, lipids, and nucleic acids that have a lot complicated bonded interactions. The CUDA port of GrOMACS enabling GPU acceleration supports Particle-Mesh-Ewald (PME), arbitrary forms of

non-bonded interactions, and implicit solvent Generalized

Born methods.

Workstation • 4xTesla C2070

• Dual-socket Quad-core CPU • 24 GB System Memory Server • Up to 8x Tesla M2090s in cluster • Dual-socket Quad-core CPU per node • 128 GB System Memory

recommended hardWare configuration

server

• 8x Tesla M2090

• Dual-socket Quad-core CPU • 128 GB System Memory

amBer

researchers today are solving the world’s most challenging and important problems. From cancer research to drugs for AIDS, computational research is bottlenecked by simulation cycles per day. More simulations mean faster time to discovery. To tackle these difficult challenges, researchers frequently rely on national supercomputers for computer simulations of their models. GPUs offer every researcher supercomputer-like performance in their own office. Benchmarks have shown four Tesla M2090 GPUs significantly outperforming the existing world record on CPU-only supercomputers.

GPU

A

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Ci

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CES

Figure 4: Absolute performance of GrOMACS running CUDA- and SSE-accelerated non-bonded kernels with PME on 3-12 CPU cores and 1-4 GPUs. Simulations with cubic and truncated dodecahedron cells, pressure coupling, as well as virtual interaction sites enabling 5 fs are shown.

29 .3 8.9 45 .6 16 .0 72. 4 28. 4 28 .5 8.7 44 .8 15 .6 70. 4 27 .7 12 .1 36 .7 49 .7 21. 9 85 .7 34 .4 83 .9 26 .9 11 4. 9 47 .5 16 5. 8 74 .4 cubic 0 20 40 60 80 100 120 140 160 180 3t+c2075 3t 6t+2xc2075 6t 12t+4xc2075 12t ns /d ay cubic

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GPU

tES

t

d

ri

VE

learn more and order today at:

www.nvidia.eu/cluster

amBer and namd 5x faster

take a free and easy test drive today

run your molecular dynamics simulation 5x faster. Take a free test drive on a remotely-hosted cluster loaded with the latest GPU-accelerated applications such as AMBEr and NAMD

and accelerate your results. Simply log on and run your application as usual, no GPU programming expertise required. Try it now and see how you can reduce simulation time from days to hours.

amBer cpu vs. gpu performance

ns/

d

ay (

h

igher is Bett

er)

5 4 3 2 1 0

2 nodes 4 nodes

cellulose npt – up to 3.5x faster

Benchmarks for AMBEr were generated with the following config -1 Node includes: Dual Tesla M2090 GPU (6GB), Dual Intel 6-core X5670 (2.93 GHz), AMBER 11 + Bugfix17, CUDA 4.0, ECC off.

3.00

0.66

1.20 3.96

2.04 4.56

1 node Сpu only cpu + gpu

namd cpu vs. gpu performance

ns/

d

ay (

h

igher is Bett

er)

1.0

0.8 0.6

0.4 0.2

0

2 nodes 4 nodes

stmv – up to 6.5x faster

Benchmarks for NAMD were generated with the following config -1 Node includes: Dual Tesla M2090 GPU (6GB), Dual Intel 4-core Xeon

(2.4 GHz), NAMD 2.8, CUDA 4.0, ECC On.

0.30

0.04 0.08

0.54

0.16 1.04

1 node Сpu only cpu + gpu

try the tesla gpu test drive today!

step

1 register

step

3 run your application and get faster results

upload your data

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With ANSYS®_{Mechanical™ 14.0 and NVIDIA}®

Professional GPUs, you can:

• Improve product quality with 2x more design

simulations

• Accelerate time-to-market by reducing engineering

cycles

• Develop high fidelity models with practical solution

times

How much more could you accomplish if simulation times could be reduced from one day to just a few hours? As an engineer, you depend on ANSYS Mechanical to design high quality products efficiently. To get the most out of ANSYS Mechanical 14.0, simply upgrade your Quadro GPU or add a Tesla GPU to your workstation, or configure a server with Tesla GPUs, and instantly unlock the highest levels of ANSYS simulation performance.

future directions

As GPU computing trends evolve, ANSYS will continue to enhance its offerings as necessary for a variety of simulation products. Certainly, performance improvements will continue as GPUs become computationally more powerful and extend their functionality to other areas of ANSYS software.

gpu accelerated engineering

ansys: supercomputing from your Workstation

With nvidia tesla gpu

What can product engineers achieve if a single

simulation run-time reduced from 48 hours to 3

hours? CST Microwave Studio is one of the most widely used electromagnetic simulation software and some of the largest customers in the world today are leveraging GPUs to introduce their products to market faster and with more confidence in the fidelity of the product design.

20x faster simulations With gpus

design superior products

With cst microWave studio

recommended tesla configurations

Workstation • 4x Tesla C2070

server

• 4x Tesla M2090

relativ

e

perf

ormanc

e v

s

cpu

25

20

15

10

5

0

2x cpu 2x cpu + 1x c2070

2x cpu + 4x c2070 9x faster with

tesla gpu

23x faster with tesla gpus

Benchmark: BGA models, 2M to 128M mesh models. CST MWS, transient solver.

CPU: 2x Intel Xeon X5620.

Single GPU run only on 50M mesh model.

A new feature in ANSYS Mechanical

leverages graphics processing units to

significantly lower solution times for large

analysis problem sizes.”

By Jeff Beisheim, Senior Software Developer, ANSYS, Inc.

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• Nastran direct equation solver is GPU accelerated

– Real, symmetric sparse direct factorization

– Handles very large fronts with minimal use of pinned host memory

– Impacts SOL101, SOL400 that are dominated by

MSCLDL factorization times

– More of Nastran (SOL108, SOL111) will be moved

to GPU in stages

• Support of multi-GPU and for both Linux and Windows

– With DMP> 1, multiple fronts are factorized

concurrently on multiple GPUs; 1 GPU per matrix domain

– NVIDIA GPUs include Tesla 20-series and Quadro 6000

– CUDA 4.0 and above

msc nastran, marc

5x performance Boost With single gpu over single core,

>1.5x With 2 gpus over 8 core

gpu acceleration in computer aided engineering

simulia aBaQus / standard

reduce engineering simulation times in half

As products get more complex, the task of innovating with more confidence has been ever increasingly difficult for product engineers. Engineers rely on Abaqus to understand behavior of complex assembly or of new materials.

With GPUs, engineers can run Abaqus simulations twice as fast. A leading car manufacturer, NVIDIA customer, reduced the simulation time of an engine model from 90 minutes to 44 minutes with GPUs. Faster simulations enable designers to simulate more scenarios to achieve, for example, a more fuel efficient engine.

speed up v

s.

cpu

onl

y

number of equations (millions)

1,5 1,5 3,0 3,4 3,8

1,9

1,8

1,7 1,6 1,5 1,4 1,3 1,2 1,1 1

abaqus 6.12 multi gpu execution 24 core 2 host, 48 gB memory per host

1 GPU/Host 2 GPUs/Host

speed up

* fs0= NVIDIA PSG cluster node

2.2 TB SATA 5-way striped rAID Linux, 96GB memory,Tesla C2050, Nehalem 2.27ghz 7

6 5 4 3 2 1

0 _{3.4m dof; fs0; total} _{3.4m dof; fs0; solver}

sol101, 3.4m dof

1 Core 1 GPU + 1 Core _{2 GPU + 2 Core}

(DMP=2) 4 Core (SMP) 8 Core (DMP=2)

4.6x 5.6x

1.6x

1.8x

GPU

A

CCE

lE

r

At

Ed

En

G

in

EE

rin

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visualize and simulate

at the same time on a single system

nvidia

®

_{maximus™ technology}

Engineers, designers, and content creation professionals are constantly being challenged to find new ways to explore and validate more ideas — faster. This often involves creating content with both visual design and physical simulation demands. For example, designing a car or creating a digital film character and understanding how air flows over the car or the character‘s clothing moves in an action scene.

Unfortunately, the design and simulation processes have often been disjointed, occurring on different systems or at different times.

introducing nvidia maximus

NVIDIA Maximus-powered workstations solve

this challenge by combining the visualization and

interactive design capability of NVIDIA Quadro GPUs and the high-performance computing power of NVIDIA Tesla GPUs into a single workstation. Tesla companion processors automatically perform the heavy lifting of photorealistic rendering or engineering simulation computation. This frees up CPU resources for the work they‘re best suited for – I/O, running the operating system and multi-tasking – and also allows the Quadro GPU to be dedicated to powering rich, full-performance, interactive design.

reinventing the WorkfloW

With Maximus, engineers, designers and content creation professionals can continue to remain productive and work with maximum complexity in real-time.

traditional workstation

nvidia®_{maximus™ workstation}

design simulate (cpu)

design design 2 design 3 design 4

+

faster iterations = faster time to market

+

simulate (gpu) simulate (gpu) simulate (gpu) simulate (gpu)

Watch video*:

nvidia maximus technology helps drive

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nV

idi

A

®

mAX

im

US

™

tECH

nol

o

Gy

simulation analysis

and cad

photorealistic rendering

and cad

ray tracing With catia

live rendering

fast, fluid editing

With premiere pro

With Maximus technology, you can perform simultaneous structural or fluid dynamics analysis with applications such as ANSYS while running your design application, including SolidWorks and PTC Creo. For more information, visit

www.nvidia.co.uk/object/tesla-ansys-accelerations-uk

For more information, visit

www.nvidia.co.uk/object/ quadro-3ds-max-uk

www.nvidia.co.uk/object/ quadro-catia-uk

www.nvidia.co.uk/object/adobe_ PremiereproCS5_uk

With Maximus technology, you can perform rapid photorealistic rendering of your designs in applications such as 3ds Max or Bunkspeed while still using your system for other work.

With Maximus technology, photorealistic rendering is interactive. And it allows you to simultaneously run other applications without bogging down your system.

With Maximus technology, you can relieve the pressure of getting more done in less time.

faster simulations, more joB instances

relative Performance Scale vs 2 CPU Cores

8 cpu cores + tesla c2075

8 CPU Cores

2 CPU Cores

relative Performance 0 1 2 3 4 5

maximus performance for 3ds max 2012 With iray Relative Performance Scale vs 8 CPU Cores

tesla c2075 + Quadro 6000 tesla c2075 + Quadro 5000 tesla c2075 + Quadro 4000 tesla c2075 + Quadro 2000

Quadro 2000 8 CPU Cores

relative Performance 0 1 2 3 4 5 6 7 8 9 10

adoBe premiere pro price/performance*

Adobe Mercury Playback Engine (MPE)

tesla c2075 + Quadro 2000 Quadro 6000 Quadro 5000 Quadro 4000

Quadro 2000 8 CPU Cores % Value Increase

* Adobe Premier Pro results obtained from 5 layers 6 effects per layer output to H.264 on a Dell T7500, 48 GB, Windows 7 at 1440 x 1080 resolution. Price performance calculated using cost per system and number of clips possible per hour.

0 100 200 300 400 500 600

maximus performance for catia live rendering Relative Performance Scale vs 8 CPU Cores

tesla c2075 + Quadro 6000 tesla c2075 + Quadro 4000

Quadro 4000 8 CPU Cores

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© 2012 nVidiA Corporation. All rights reserved. nVidiA, the nVidiA logo, nVidiA tesla, CUdA, Gigathread, Parallel dataCache and Parallel nSight are trademarks and/or registered trademarks of nVidiA Corporation. All company and product names are trademarks or