100x. Performance Advantage by 2021. 25% year. 52% year. 20% year. CPU. GPU ..... By starting with a free, 30-day trial of PGI directives today .... domain. â NVIDIA GPUs include Tesla 20-series and Quadro. 6000. â CUDA 4.0 and above.
revolutionising high performance computing WITH supermicro SOLUTIONS USING nvidia® tesla®
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.
100x Performance Advantage by 2021
Conventional CPU computing architecture can no longer support the growing HPC needs. Source: Hennesse]y &Patteson, CAAQA, 4th Edition.
10000
20% year
Performance vs VAX
1000
52% year 100
10
25% year
CPU GPU Growth per year
1 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
2016
Latest GPU SuperServer®, SuperBlade® and NVIDIA® Maximus™ Certified 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
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, highdensity GPU server and workstation platforms,” said Charles Liang, President and CEO of Supermicro®. “At GTC, we are showcasing our new generation X9 SuperServer®, SuperBladeTM 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.”
Accelerating Research, Scietific, Engineering, Computational Finance and Design Applications 1U SuperServer®
2U SuperServer®
7U SuperBlade®
SuperWorkstation
1027Gr-TQF
2027GR-TRF
SBI-7127RG
7047GR-TRF
Up to 4x GPUs
Up to 6x GPUs
Up to 20x GPUs
4x NVIDIA Tesla GPUs 1x NVIDIA Quadro GPU
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.
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hybrid computing
Solutions from Supermicro®
NVIDIA® TESLA / Hybrid computing solutions 2010
superworkstations
TM
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
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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 • 1620W Redundant Platinum Level Power Supplies
High Performance GPU servers
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.
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. • Dual Intel® Xeon® processor E5-2600 family; Socket R (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
Brains, Brains and More Brains!!! 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® 2026GTTRFs 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.
Watch video*: Superservers in action: Virginia Tech − HokieSpeed Supercomputer * Use your phone, smartphone or tablet PC with QR reader software to read the QR code.
5
hybrid computing
The foundation of a flexible and Efficient HPC & Data center deployment
NVIDIA® TESLA / Hybrid computing solutions 2010 TM
High Performance GPU servers
SuperServers 1017GR-TF (-FM275/-FM209) • GPU Server, Mission-critical app., enterprise server, 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) • GPU Server, Mission-critical app., enterprise server, oil & gas, financial, 3D rendering, chemistry, HPC • Single Intel® Xeon® processor E5-2600 family; Socket R (LGA 2011) • 3 Hot-swap 3.5“ 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 (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 • „-FM275/209“: 2x NVIDIA M2075/M2090 GPU cards integrated
1027GR-TRFT/1027GR-TRF (-FM375/-FM309) / 1027GR-TSF • GPU Server, Mission-critical app., enterprise server, oil & gas, financial, 3D rendering, chemistry, HPC • Dual Intel® Xeon® processor E5-2600 family; Socket R (LGA 2011) • 4 Hot-swap 2.5“ SATA2/3 HDD Bays • 8 DIMMs support up to 256GB DDR3 1600MHz reg. ECC 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) • „-FM375/309“: 3x NVIDIA M2075/M2090 GPU cards integrated
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GPU SUPERBLADE® SOLUTIONS
Superblade solutions
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. www.supermicro.com/SuperBlade
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.
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
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
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Turnkey Preconfigured GPU Clusters Ready-to-use solutions for science and research
ACCESS THE POWER OF GPU COMPUTING WITH OFF-THE-SHELF, READY TO DEPLOY TESLA GPU CLUSTER 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
SRS-14URKS-GPUS-11
SRS-14URKS-GPUS-12
SRS-42URKS-GPUS-13
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)
GPU Nodes: 8 + 1 Head node CPU: 2x Westmere X5650 2.66GHz Memory: 48 GB per node Default GPU/Node: 2x M2090 Network Cards/Node: 1x InfiniBand Storage/Node: 2x 500GB HDD (1TB/Node)
GPU Nodes: 16 + 1 Head node CPU: 2x Westmere X5650 2.66GHz Memory: 48 GB per node Default GPU/Node: 2x M2090 Network Cards/Node: 1x InfiniBand Storage/Node: 2x 1TB HDD (2TB/ Node)
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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.
hybrid computing
supermicro is committed to support ® Tesla kepler GPU accelerators1
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 available memory with ECC on.
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NVIDIA® Tesla® Kepler.. GPU Computing Accelerators..
Tesla® Kepler ― World’s fastest and most power efficient x86 accelerator
Fastest, Most Efficient HPC Architecture 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 computationallyintensive 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
SM
SMX
FERMI
CONTROL LOGIC
KEPLER
CONTROL LOGIC
3X
PERF/WATT
32 CORES
192 CORES
Figure 1: SMX: 192 CUDA cores, 32 Special Function Units (SFU), and 32 Load/Store units (LD/ST)
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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.
DYNAMIC PARALLELISM GPU
CPU
GPU
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.
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 MPIbased parallel computer systems. Legacy 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
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.
To learn more about NVIDIA Tesla, go to www.nvidia.eu/tesla 11
Nvidia® Tesla® Kepler
CPU
Programming environment for gpu computing nvidia’s cuda 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.
research & Education Integrated development environment languages & APIs
LIBRARIES
CUDA All major platforms
Mathematical packages consultants, training, & certification
Tools & Partners
Order personalized CUDA education course at: www.parallel-computing.pro
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 highlevel 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. www.nvidia.eu/openacc
Watch video*: PGI ACCELERATOR, TECHNICAL PRESENTATION AT SC11 * Use your phone, smartphone or tablet PC with QR reader software to read the QR code.
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History of gpu computing Graphics chips started as fixed function graphics pipelines. Over the years, these graphics chips became increasingly programmab
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
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.
Relative Performance Scale (normalized ns/day)
1,5
50% Faster with 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: •
1,0
0,5
192 Quad-Core CPUs
2 Quad-Core CPUs + 4 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
Molecular Dynamics & Quantum Chemistry AMBER, GROMACS, HOOMD, LAMMPS, NAMD, TeraChem (Quantum Chemistry), VMD
• Bio Informatics CUDA-BLASTP, CUDA-EC, CUDA MEME, CUDASW++ (Smith Waterman), GPU-HMMER, MUMmerGPU For more information, visit: www.nvidia.co.uk/bio_workbench
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NVIDIA® TESLA / Hybrid computing solutions 2010 TM
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.
AMBER: NODE PROCESSING COMPARISON 4 Tesla M2090 GPUs + 2 CPUs
192 Quad-Core CPUs
69 ns/day
46 ns/day
GPUs offer every researcher supercomputerlike performance in their own office. Benchmarks have shown four Tesla M2090 GPUs significantly outperforming the existing world record on CPU-only supercomputers.
RECOMMENDED HARDWARE CONFIGURATION Workstation
Server
• • • • • •
• 8x Tesla M2090 • Dual-socket Quad-core CPU • 128 GB System Memory
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
180
3T+C2075 3T
160
6T+2xC2075 140
114.9
6T 12T+4xC2075
120
0
cubic + pcoupl
dodec
47.5 26.9
21.9
34.4
36.7 12.1
27.7
28.5
44.8
49.7
70.4
74.4
85.7
cubic
8.7
28.4
29.3 16.0
20
8.9
40
45.6
60
15.6
80
83.9
12T
100 72.4
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 nonbonded interactions, and implicit solvent Generalized Born methods.
165.8
GROMACS
ns/day
GPU ACCELERATION IN Life Sciences
Amber
dodec + vsites
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.
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AMBER and NAMD 5x Faster 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
GPU Test Drive
Take a Free and Easy Test Drive Today
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.
Try the Tesla GPU Test drive today!
Step 1
Register
Step 2
Upload your data
Step 3
Run your application and get faster results
AMBER CPU vs. GPU Performance
Namd CPU vs. GPU Performance
5
1.0
СPU Only CPU + GPU
0.8
3.96 3
3.00
2
2.04
1
1.20
CPU + GPU
0.6
0.54
0.4
0.2
0.66
0.30
0.16 0.04
0 1 Node
2 Nodes
1.04
СPU Only
ns/Day (Higher is Better)
ns/Day (Higher is Better)
4
4.56
0
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.
0.08
1 Node
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.
Learn more and order today at: www.nvidia.eu/cluster
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GPU ACCELERATED ENGINEERING
ansys: supercomputing from your workstation with NVIDIA Tesla GPU
“
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.
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.
20x Faster Simulations with GPUs Design Superior Products with CST Microwave Studio
Recommended Tesla Configurations
16
Workstation
Server
• 4x Tesla C2070 • Dual-socket Quad-core CPU • 48 GB System Memory
• 4x Tesla M2090 • Dual-socket Quad-core CPU • 48 GB System Memory
23x Faster with Tesla GPUs
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Relative Performance vs CPU
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.
20
15
9X Faster with Tesla GPU
10
5
0
2x CPU
2x CPU + 1x C2070
2x CPU + 4x C2070
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.
GPU ACCELERATED ENGINEERING
GPU acceleration in Computer aided Engineering MSC Nastran, Marc 5X performance boost with single GPU over single core, >1.5X with 2 GPUs over 8 core
Sol101, 3.4M DOF
• 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
7
1 Core
1 GPU + 1 Core
4 Core (SMP)
8 Core (DMP=2)
2 GPU + 2 Core (DMP=2)
6 1.8x
5 1.6x
4
• Support of multi-GPU and for both Linux and Windows
5.6x 4.6x
3 2
– 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
1 0
3.4M DOF; fs0; Total
3.4M DOF; fs0; Solver
Speed Up * fs0= NVIDIA PSG cluster node 2.2 TB SATA 5-way striped RAID
Linux, 96GB memory, Tesla C2050, Nehalem 2.27ghz
SIMULIA Abaqus / Standard Reduce Engineering Simulation Times in Half
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.
Abaqus 6.12 Multi GPU Execution 24 core 2 host, 48 GB memory per host 1,9 1,8 Speed up vs. CPU only
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.
1,7
1 GPU/Host 2 GPUs/Host
1,6 1,5 1,4 1,3 1,2 1,1 1
1,5
1,5 3,0 3,4 Number of Equations (millions)
3,8
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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
Simulate (CPU)
Design
NVIDIA® Maximus™ workstation Design
Design 2
Design 3
Design 4
Simulate (GPU)
Simulate (GPU)
Simulate (GPU)
Simulate (GPU)
+
+
+
+
Faster Iterations = Faster Time to Market
Watch video*: NVIDIA Maximus Technology Helps Drive the Silver Arrow Mercedes-Benz Concept Car * Use your phone, smartphone or tablet PC with QR reader software to read the QR code.
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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.
8 CPU Cores + Tesla C2075 8 CPU Cores 2 CPU Cores Relative Performance
0
1
2
3
4
For more information, visit www.nvidia.co.uk/object/teslaansys-accelerations-uk
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Photorealistic rendering and CAD
Maximus performance for 3ds max 2012 with iray Relative Performance Scale vs 8 CPU Cores
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.
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
For more information, visit www.nvidia.co.uk/object/ quadro-3ds-max-uk
Ray tracing with Catia live rendering
MAXIMUS PERFORMANCE FOR CATIA LIVE RENDERING Relative Performance Scale vs 8 CPU Cores
With Maximus technology, photorealistic rendering is interactive. And it allows you to simultaneously run other applications without bogging down your system.
Tesla C2075 + Quadro 6000 Tesla C2075 + Quadro 4000 Quadro 4000 8 CPU Cores Relative Performance
Nvidia® Maximus™ Technology
Simulation analysis and cad
Faster Simulations, more job instances Relative Performance Scale vs 2 CPU Cores
0
1
2
3
4
5
6
7
8
For more information, visit www.nvidia.co.uk/object/ quadro-catia-uk
Fast, fluid editing with premiere pro
ADOBE PREMIERE PRO PRICE/PERFORMANCE* Adobe Mercury Playback Engine (MPE)
With Maximus technology, you can relieve the pressure of getting more done in less time.
Tesla C2075 + Quadro 2000 Quadro 6000 Quadro 5000
For more information, visit www.nvidia.co.uk/object/adobe_ PremiereproCS5_uk
Quadro 4000 Quadro 2000 8 CPU Cores % Value Increase
0
100
200
300
400
500
600
* 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.
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