DOCSLIB.ORG

Nvidia Corporation from Super Phones to Super Cars

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Nvidia Corporation from Super Phones to Super Cars NVIDIA CORPORATION FROM SUPER PHONES TO SUPER CARS NVIDIA awakened the world to computer With the invention of the virtual GPU, NVIDIA IN BRIEF graphics when it invented the GPU in 1999. we’re accelerating cloud computing for Founded in 1993 From our roots in visual computing, we’ve consumers and enterprises. Jen-Hsun Huang is co-founder, expanded into super, mobile and cloud president and CEO computing. NVIDIA’s mobile processors GPUs: THE ENGINES OF are used in smartphones, tablets and auto MODERN COMPUTING Listed with NASDAQ under the symbol NVDA in 1999 infotainment systems. PC gamers rely on One of the most complex processors ever GPUs to enjoy spectacularly immersive created, the GPU is the engine behind Invented the GPU in 1999 and has shipped more than 1 billion to date worlds. Professionals use them to create state-of-the-art computer graphics and visual effects in movies and design every- energy-efficient computing. NVIDIA’s latest 7,500 employees worldwide thing from golf clubs to jumbo jets. And GPU architecture, Kepler, boasts 7 billion $4 billion in revenue in FY12 researchers utilize GPUs to advance the transistors. Based on Kepler, the GTX690 5,000 patents issued, allowed frontiers of science with high-performance is the fastest, most energy efficient GPU or filed computers. ever built. And key features in Kepler Ranked #10 “greenest” company in will make supercomputing more efficient America by Newsweek in 2011 A CULTURE OF REINVENTION and accessible. Founded in 1993, NVIDIA has continuously reinvented itself to delight users and shape A PASSIONATE FOLLOWING the industry. From our beginnings in PC The passionate drive that fuels our company graphics, we expanded into professional is most powerfully reflected back from our graphics to become the standard bearer in users. The devotion to our brand is truly visual computing. We later harnessed the rare and is expressed in deeply personal parallel computing capabilities of the GPU to ways—including artwork, tattoos and even advance high-performance computing. Our in fans naming their children “NVIDIA.” move into mobile put us at the center of one of the industry’s fastest-growing segments. NVIDIA’s latest class of GPUs have up to 7 billion transistors. NVIDIA | FACTSHEET | 0812 “What NVIDIA is helping GEFORCE: AMAZING VISUAL EXPERIENCES TESLA: ACCELERATING SCIENCE to create is a world only Our heritage is in PC graphics, and our NVIDIA’s expertise in programmable limited by our imaginations, GeForce® processors deliver amazing GPUs has led to breakthroughs in parallel visual experiences to a booming gaming processing. Scientists and researchers where dreams can blend market—opening week game sales around the world are using Tesla® GPUs to with reality, where our regularly outstrip sales of blockbuster tackle the most complex challenges, from Hollywood movies. The PC gaming market climate modeling to quantum physics to hopes can be realized.” ® ® is expected to reach $25B in 2016. And finding a cure for cancer. NVIDIA CUDA — Rob Enderle, Enderle Group gaming is one of the most popular activities architecture enables GPUs to work not in China’s 160,000+ icafes. Beyond gaming, just with the pixels of an image, but with GeForce processors power the sleekest numerical data. NVIDIA Tesla processors ultrabooks so users can do things like harness CUDA to make supercomputing edit movies, retouch photos and play more efficient and more accessible. Today, games without compromise. GeForce CUDA is taught in more than 560 universities. notebook GPUs also efficiently power the On the June 2012 list of Top500 supercom- MacBook Pro and its dazzling 2880×1800 puters, more than 50 systems were powered Retina display. by NVIDIA GPUs, rising from 10 in just 18 months. QUADRO: THE PROFESSIONALS’ CHOICE In the early 2000s, our invention of a programmable processor expanded TEGRA: THE MOBILE SUPER CHIP NVIDIA’s reach into professional graphics. Tegra®, a mobile super chip, powers the Today, the majority of the world’s cars and next generation of mobile devices, as well planes, as well as a host of consumer as in-car safety and infotainment systems. products like tennis shoes and shampoo Tegra 3’s 4-PLUS-1 architecture—four bottles, are designed using Quadro® powerful CPU cores handle demanding tasks GPU-ACCELERATED CLOUD COMPUTING solutions. In film, Quadro GPUs were while a fifth low-power, battery-saver core Cloud computing will deliver the content behind all of the “Best Visual Effects” manages less strenuous tasks—provides people care about to whatever display Oscar nominees for the past three years outstanding performance and exceptional they’re looking at. With the invention of the running. With NVIDIA Maximus technology, battery life. The Asus Transformer Prime virtual GPU, NVIDIA is accelerating cloud designers and engineers can do graphics- tablet and super phones from HTC, Fujitsu computing, from gaming to the enterprise. intensive work and compute-intensive work and ZTE are just a few of the devices that With GeForce® GRID, gamers have the at the same time, on the same machine. feature the super chip. NVIDIA continues freedom to play the most graphics-intensive to build on its early tech leadership in the games from the cloud on any display. And mobile computing revolution. In 2012, the NVIDIA VGX™ enables a true PC experience number of Tegra phone design wins has for the hundreds of millions of power users doubled, from 15 to 30; Tegra was selected who increasingly want to bring their own by Asus to power the world’s first WinRT devices to work. tablet; and Google chose Tegra for its own Android tablet, the Nexus 7. To learn more about NVIDIA, go to www.nvidia.com © 2012 NVIDIA Corporation. All rights reserved. NVIDIA and the NVIDIA logo, CUDA, GeForce, NVIDIA 3D Vision, PhysX, Quadro, Tegra, TegraZone, and Tesla are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability, and specifications are subject to change without notice. The Avengers image courtesy of Marvel Studios © 2012..
Load more

Recommended publications
  • Nvidia Tesla P40 Gpu Accelerator
    NVIDIA TESLA P40 GPU ACCELERATOR HIGH-PERFORMANCE VIRTUAL GRAPHICS AND COMPUTE NVIDIA redefined visual computing by giving designers, engineers, scientists, and graphic artists the power to take on the biggest visualization challenges with immersive, interactive, photorealistic environments. NVIDIA® Quadro® Virtual Data GPU 1 NVIDIA Pascal GPU Center Workstation (Quadro vDWS) takes advantage of NVIDIA® CUDA Cores 3,840 Tesla® GPUs to deliver virtual workstations from the data center. Memory Size 24 GB GDDR5 H.264 1080p30 streams 24 Architects, engineers, and designers are now liberated from Max vGPU instances 24 (1 GB Profile) their desks and can access applications and data anywhere. vGPU Profiles 1 GB, 2 GB, 3 GB, 4 GB, 6 GB, 8 GB, 12 GB, 24 GB ® ® The NVIDIA Tesla P40 GPU accelerator works with NVIDIA Form Factor PCIe 3.0 Dual Slot Quadro vDWS software and is the first system to combine an (rack servers) Power 250 W enterprise-grade visual computing platform for simulation, Thermal Passive HPC rendering, and design with virtual applications, desktops, and workstations. This gives organizations the freedom to virtualize both complex visualization and compute (CUDA and OpenCL) workloads. The NVIDIA® Tesla® P40 taps into the industry-leading NVIDIA Pascal™ architecture to deliver up to twice the professional graphics performance of the NVIDIA® Tesla® M60 (Refer to Performance Graph). With 24 GB of framebuffer and 24 NVENC encoder sessions, it supports 24 virtual desktops (1 GB profile) or 12 virtual workstations (2 GB profile), providing the best end-user scalability per GPU. This powerful GPU also supports eight different user profiles, so virtual GPU resources can be efficiently provisioned to meet the needs of the user.
    [Show full text]
  • NVIDIA Ampere GA102 GPU Architecture Whitepaper
    NVIDIA AMPERE GA102 GPU ARCHITECTURE Second-Generation RTX Updated with NVIDIA RTX A6000 and NVIDIA A40 Information V2.0 Table of Contents Introduction 5 GA102 Key Features 7 2x FP32 Processing 7 Second-Generation RT Core 7 Third-Generation Tensor Cores 8 GDDR6X and GDDR6 Memory 8 Third-Generation NVLink® 8 PCIe Gen 4 9 Ampere GPU Architecture In-Depth 10 GPC, TPC, and SM High-Level Architecture 10 ROP Optimizations 11 GA10x SM Architecture 11 2x FP32 Throughput 12 Larger and Faster Unified Shared Memory and L1 Data Cache 13 Performance Per Watt 16 Second-Generation Ray Tracing Engine in GA10x GPUs 17 Ampere Architecture RTX Processors in Action 19 GA10x GPU Hardware Acceleration for Ray-Traced Motion Blur 20 Third-Generation Tensor Cores in GA10x GPUs 24 Comparison of Turing vs GA10x GPU Tensor Cores 24 NVIDIA Ampere Architecture Tensor Cores Support New DL Data Types 26 Fine-Grained Structured Sparsity 26 NVIDIA DLSS 8K 28 GDDR6X Memory 30 RTX IO 32 Introducing NVIDIA RTX IO 33 How NVIDIA RTX IO Works 34 Display and Video Engine 38 DisplayPort 1.4a with DSC 1.2a 38 HDMI 2.1 with DSC 1.2a 38 Fifth Generation NVDEC - Hardware-Accelerated Video Decoding 39 AV1 Hardware Decode 40 Seventh Generation NVENC - Hardware-Accelerated Video Encoding 40 NVIDIA Ampere GA102 GPU Architecture ii Conclusion 42 Appendix A - Additional GeForce GA10x GPU Specifications 44 GeForce RTX 3090 44 GeForce RTX 3070 46 Appendix B - New Memory Error Detection and Replay (EDR) Technology 49 Appendix C - RTX A6000 GPU Perf ormance 50 List of Figures Figure 1.
    [Show full text]
  • PACKET 22 BOOKSTORE, TEXTBOOK CHAPTER Reading Graphics
    A.11 GRAPHICS CARDS, Historical Perspective (edited by J Wunderlich PhD in 2020) Graphics Pipeline Evolution 3D graphics pipeline hardware evolved from the large expensive systems of the early 1980s to small workstations and then to PC accelerators in the 1990s, to $X,000 graphics cards of the 2020’s During this period, three major transitions occurred: 1. Performance-leading graphics subsystems PRICE changed from $50,000 in 1980’s down to $200 in 1990’s, then up to $X,0000 in 2020’s. 2. PERFORMANCE increased from 50 million PIXELS PER SECOND in 1980’s to 1 billion pixels per second in 1990’’s and from 100,000 VERTICES PER SECOND to 10 million vertices per second in the 1990’s. In the 2020’s performance is measured more in FRAMES PER SECOND (FPS) 3. Hardware RENDERING evolved from WIREFRAME to FILLED POLYGONS, to FULL- SCENE TEXTURE MAPPING Fixed-Function Graphics Pipelines Throughout the early evolution, graphics hardware was configurable, but not programmable by the application developer. With each generation, incremental improvements were offered. But developers were growing more sophisticated and asking for more new features than could be reasonably offered as built-in fixed functions. The NVIDIA GeForce 3, described by Lindholm, et al. [2001], took the first step toward true general shader programmability. It exposed to the application developer what had been the private internal instruction set of the floating-point vertex engine. This coincided with the release of Microsoft’s DirectX 8 and OpenGL’s vertex shader extensions. Later GPUs, at the time of DirectX 9, extended general programmability and floating point capability to the pixel fragment stage, and made texture available at the vertex stage.
    [Show full text]
  • Advanced Computing
    National Aeronautics and Space Administration S NASA Advanced Computing e NASA Advanced Supercomputing Division has been the agency’s primary resource for high performance computing, data storage, and advanced modeling and simulation tools for over 30 years. From the 1.9 gigaflop Cray-2 system installed in 1985 to the current petascale Pleiades, Electra, and Aitken superclusters, our facility at NASA’s Ames Research Center in Silicon Valley has housed over 40 production and testbed super- computers supporting NASA missions and projects in aeronautics, human space exploration, Earth science, and astrophysics. www.nasa.gov SUPERCOMPUTING (NAS) DIVISION NASA ADVANCED e NASA Advanced Supercomputing (NAS) facility’s NVIDIA Tesla V100 GPUs, to the Pleiades supercomputer, computing environment includes the three most powerful providing dozens of teraflops of computational boost to supercomputers in the agency: the petascale Electra, Aitken, each of the enhanced nodes. and Pleiades systems. Developed with a focus on flexible scalability, the systems at NAS have the ability to expand e NAS facility also houses several smaller systems to sup- and upgrade hardware with minimal impact to users, allow- port various computational needs, including the Endeavour ing us the ability to continually provide the most advanced shared-memory system for large-memory jobs, and the computing technologies to support NASA’s many inspiring hyperwall visualization system, which provides a unique missions and projects. environment for researchers to explore their very large, high-dimensional datasets. Additionally, we support both Part of this hardware diversity includes the integration of short-term RAID and long-term tape mass storage systems, graphics processing units (GPUs), which can speed up providing more than 1,500 users running jobs on the some codes and algorithms run on NAS systems.
    [Show full text]
  • Virtual GPU Software User Guide Is Organized As Follows: ‣ This Chapter Introduces the Capabilities and Features of NVIDIA Vgpu Software
    Virtual GPU Software User Guide DU-06920-001 _v13.0 Revision 02 | August 2021 Table of Contents Chapter 1. Introduction to NVIDIA vGPU Software..............................................................1 1.1. How NVIDIA vGPU Software Is Used....................................................................................... 1 1.1.2. GPU Pass-Through.............................................................................................................1 1.1.3. Bare-Metal Deployment.....................................................................................................1 1.2. Primary Display Adapter Requirements for NVIDIA vGPU Software Deployments................2 1.3. NVIDIA vGPU Software Features............................................................................................. 3 1.3.1. GPU Instance Support on NVIDIA vGPU Software............................................................3 1.3.2. API Support on NVIDIA vGPU............................................................................................ 5 1.3.3. NVIDIA CUDA Toolkit and OpenCL Support on NVIDIA vGPU Software...........................5 1.3.4. Additional vWS Features....................................................................................................8 1.3.5. NVIDIA GPU Cloud (NGC) Containers Support on NVIDIA vGPU Software...................... 9 1.3.6. NVIDIA GPU Operator Support.......................................................................................... 9 1.4. How this Guide Is Organized..................................................................................................10
    [Show full text]
  • Nvidia Tesla V100 Gpu Accelerator
    NVIDIA TESLA V100 GPU ACCELERATOR The Most Advanced Data Center GPU Ever Built. SPECIFICATIONS NVIDIA® Tesla® V100 is the world’s most advanced data center GPU ever built to accelerate AI, HPC, and graphics. Powered by NVIDIA Volta, the latest GPU architecture, Tesla V100 offers the Tesla V100 Tesla V100 PCle SXM2 performance of up to 100 CPUs in a single GPU—enabling data GPU Architecture NVIDIA Volta scientists, researchers, and engineers to tackle challenges that NVIDIA Tensor 640 were once thought impossible. Cores NVIDIA CUDA® 5,120 Cores 47X Higher Throughput than CPU Deep Learning Training in Less Double-Precision 7 TFLOPS 7.8 TFLOPS Server on Deep Learning Inference Than a Workday Performance Single-Precision 14 TFLOPS 15.7 TFLOPS 8X V100 Performance Tesla V100 47X 51 Hours Tensor 112 TFLOPS 125 TFLOPS Tesla P100 15X Performance 1X PU 8X P100 GPU Memory 32GB /16GB HBM2 155 Hours Memory 900GB/sec 0 10X 20X 30X 40X 50X 0 4 8 12 16 Bandwidth Performance Normalzed to PU Tme to Soluton n Hours Lower s Better ECC Yes Workload ResNet-50 | PU 1X Xeon E5-2690v4 26Hz | PU add 1X NVIDIA® Server ong Dual Xeon E5-2699 v4 26­Hz | 8X Interconnect Tesla ® P100 or V100 Tesla P100 or V100 | ResNet-50 Tranng on MXNet 32GB/sec 300GB/sec for 90 Epochs wth 128M ImageNet dataset Bandwidth System Interface PCIe Gen3 NVIDIA NVLink Form Factor PCIe Full SXM2 Height/Length 1 GPU Node Replaces Up To 54 CPU Nodes Node Replacement: HPC Mixed Workload Max Power 250 W 300 W Comsumption L­fe Sc­ence 14 Thermal Solution Passive (NAMD) Compute APIs CUDA, DirectCompute,
    [Show full text]
  • NVIDIA Tesla P100 Pcie Data Sheet
    NVIDIA® TESLA® P100 GPU ACCELERATOR World’s most advanced data center accelerator for PCIe-based servers HPC data centers need to support the ever-growing demands of scientists and researchers while staying within a tight budget. The old approach of deploying lots of commodity compute nodes requires huge interconnect overhead that substantially increases costs SPECIFICATIONS without proportionally increasing performance. GPU Architecture NVIDIA Pascal NVIDIA CUDA® Cores 3584 NVIDIA Tesla P100 GPU accelerators are the most advanced ever Double-Precision 4.7 TeraFLOPS built, powered by the breakthrough NVIDIA Pascal™ architecture Performance Single-Precision 9.3 TeraFLOPS and designed to boost throughput and save money for HPC and Performance hyperscale data centers. The newest addition to this family, Tesla Half-Precision 18.7 TeraFLOPS Performance P100 for PCIe enables a single node to replace half a rack of GPU Memory 16GB CoWoS HBM2 at commodity CPU nodes by delivering lightning-fast performance in a 732 GB/s or 12GB CoWoS HBM2 at broad range of HPC applications. 549 GB/s System Interface PCIe Gen3 MASSIVE LEAP IN PERFORMANCE Max Power Consumption 250 W ECC Yes NVIDIA Tesla P100 for PCIe Performance Thermal Solution Passive Form Factor PCIe Full Height/Length 30 X 2X K80 2X P100 (PIe) 4X P100 (PIe) Compute APIs CUDA, DirectCompute, 25 X OpenCL™, OpenACC ™ 20 X TeraFLOPS measurements with NVIDIA GPU Boost technology 15 X 10 X 5 X Appl cat on Speed-up 0 X NAMD VASP MIL HOOMD- AMBER affe/ Blue AlexNet Dual PU server, Intel E5-2698 v3 23 Hz, 256 B System Memory, Pre-Product on Tesla P100 TESLA P100 PCle | DATA SHEEt | Oct16 A GIANT LEAP IN PERFORMANCE Tesla P100 for PCIe is reimagined from silicon to software, crafted with innovation at every level.
    [Show full text]
  • Nvidia Virtual Gpu How to Buy
    NVIDIA VIRTUAL GPU HOW TO BUY OVERVIEW NVIDIA virtual GPU software enables the delivery of graphics-rich virtual • NVIDIA Quadro® Virtual Data Center Workstation (Quadro vDWS) desktops and workstations accelerated by NVIDIA® Tesla® GPUs, the most • NVIDIA GRID® Virtual PC (GRID vPC) powerful data center GPUs on the market today. NVIDIA virtual GPU software divides Tesla GPU resources so the GPU can be shared across multiple virtual • NVIDIA GRID Virtual Applications (GRID vApps) machines running any application. To run these software products, you’ll need an NVIDIA Tesla GPU and a The portfolio of NVIDIA virtual GPU software products includes: software license that addresses your specific use case. FIND THE BEST VIRTUAL GPU SOFTWARE PRODUCT FOR YOUR USERS. Type of User Creative and Technical Professional Knowledge Worker Virtual GPU Software Edition Quadro Virtual Data Center Workstation GRID Virtual PC / Virtual Applications Tesla P4, M60, P40, P100, V100, or Tesla P6 for GPU Hardware Recommendation Tesla M10, or Tesla P6 for blade form factor blade form factor NVIDIA VIRTUAL GPU SOFTWARE FEATURE LIST Quadro GRID GRID Quadro GRID GRID Configuration and Deployment vDWS vPC vApps Display vDWS vPC vApps Desktop Virtualization Maximum Hardware Rendered Display Four 4k Four One6 ✓ ✓ QHD, Two 12 RDSH App Hosting ✓1 ✓ ✓ 4K Maximum Resolution 4096 x 4096 x 1280 x RDSH Desktop Hosting ✓1 ✓ ✓ 2160 2160 1024 Windows OS Support Quadro GRID GRID ✓ ✓ ✓ Support vDWS vPC vApps Linux OS Support 2 ✓ ✓ NVIDIA Direct Enterprise-Level Technical Support ✓ ✓ ✓ GPU Pass-Through Support3 ✓ ✓ Maintenance Releases, Defect Resolutions, 8 ✓ ✓ ✓ Bare Metal Support4 ✓ ✓ and Security Patches for up to 3 Years Quadro GRID GRID NVIDIA Graphics Driver 1 Data Center Management ✓ ✓ ✓ vDWS vPC vApps NVIDIA Quadro Driver Host, Guest, and Application- ✓ Level Monitoring7 ✓ ✓ ✓ Guaranteed Quality-of-Service Scheduling5 ✓ ✓ ✓ Live Migration2 ✓ ✓ ✓ Quadro GRID GRID Advanced Professional Features FIND THE BEST NVIDIA DATA CENTER GPU vDWS vPC vApps FOR YOUR ENVIRONMENT.
    [Show full text]
  • NVIDIA® TESLA™ M2070Q Visual Supercomputing at 1/10Th the Cost
    NVIDIA® TESLA™ M2070Q VISUAL SUPERCOMPUTING TH at 1/10 THE COST Based on the next-generation CUDA™ architecture codenamed “Fermi”, TECHnICAL SPECIFICATIONS ™ the Tesla M2070Q Computing and Visualization Module enables CudA PARALLEL prOceSSING COreS integration of GPU computing and visualization with host systems for high- > 448 performance computing and large data center, scale-out deployments. FOrm FActOR > 9.75” PCIe x16 Dual Slot # OF TESLA GPUs The Tesla M2070Q is the first to deliver greater From medical imaging to structural > 1 than 10X the double-precision horsepower of analysis applications, data integrity and DOUBLE PreciSION FLOAtiNG a quad-core x86 CPU and the first to deliver precision is assured, without sacrificing POINT perfOrmANce (peAK) ECC memory. The Tesla M2070Q module graphics performance. The Tesla M2070Q > 515 Gflops SiNGLE PreciSION FLOAtiNG delivers all of the standard benefits of GPU is even a great solution for enabling rich POINT perfOrmANce (peAK) computing while enabling maximum reliability media VDI desktops using Microsoft’s > 1.03 Tflops and tight integration with system monitoring RemoteFX, giving multiple VDI users TOTAL DedicAted MEMORY2 and management tools. In addition, the the power of hardware accelerated > 6GB GDDR5 MEMORY Speed “Q” means Quadro graphics features are graphics from a single graphics device. > 1.55 GHz also enabled, making the M2070Q a great MemORY INterfAce solution for server based graphics delivering > 384-bit up to an unheard of 1.3 billion triangles per MemORY BANdwidth > 148 GB/s second, shattering previous 3D performance MAX POwer CONSumptiON 1 benchmarks. This gives data center IT > 225W TDP staff the ability to deploy GPUs for both SYStem INterfAce compute and visualization in one convenient > PCIe x16 Gen2 solution.
    [Show full text]
  • TESLA™ S2050 GPU Computing SYSTEM Supercomputing at 1/10Th the Cost
    TESLA™ S2050 GPU ComputinG SYSTEm SuperComputinG at 1/10Th ThE Cost Based on the new NVIDIA cUDA™ GPU architecture codenamed TEchnical SPEcIFIcATIONS ™ “Fermi,” the Tesla S2050 1U computing Systems are designed from FORM FAcTOR > 1U the ground up for high performance computing. # of Tesla GPUS > 4 The Tesla S2050 computing System GPU Memory Speed > 1.55 GHz delivers “must have” features GPU Memory InterfacE for the technical and enterprise > 384-bit computing space including ECC memory GPU Memory Bandwidth for uncompromised accuracy and > 148 GB/sec scalability, and 7X the double precision Double Precision floating point performancE (peak) performance compared Tesla 10-series > 2 Tflops GPU computing products. compared to Oil & Gas Single Precision floating point typical quad-core cPUs, Tesla 20-series performancE (peak) > 4.13 Tflops computing systems deliver equivalent Total Dedicated Memory* th th performance at 1/10 the cost and1/20 > 12GB GDDR5 the power consumption. POwer Consumption (Typical) > 900w TDP Designed with four Fermi-based System InterfacE > PcIe x16 Gen2 Tesla computing processors in a Software Development Tools standard 1U chassis, the Tesla S2050 > cUDA c/c++/Fortran, OpencL, ScIENcE Directcompute Toolkits. computing system scales to solve the NVIDIA Parallel Nsight™ for Visual Studio world’s most important computing *Note: With ECC on, a portion of the dedicated challenges – more quickly memory is used for ECC bits, so the available user memory is reduced by 12.5%. (e.g. 3 GB total memory and accurately. yields 2.625 GB of user available memory.) FinancE NVIDIA TESLA | DATASHEET | JUN10 FEATURES AND BENEFITS GPUs powered By the Fermi- Delivers cluster performance at 1/10th the cost and 1/20th the power of generation of the cUDA architecture cPU-only systems based on the latest quad core cPUs.
    [Show full text]
  • Nvidia Maximus System Builders' Guide
    NVIDIA MAXIMUS SYSTEM BUILDERS’ GUIDE MICROSOFT WINDOWS 7–64 DI-06471-001_v02 | September 2012 User Instructions DOCUMENT CHANGE HISTORY DI-06471-001_v02 Version Date Authors Description of Change 01 August 4, 2012 OO, TS Initial release 02 September 6, 2012 EK, TS Minor Edits NVIDIA Maximus System Builders’ Guide Microsoft Windows 7–64 DI-06471-001_v02 | ii TABLE OF CONTENTS NVIDIA Maximus System Builders’ Guide ..................................................... 5 Audience ....................................................................................................... 5 Prerequisite Skills ............................................................................................ 6 Contents ....................................................................................................... 6 Benefits of Maximus Technology ........................................................................... 6 Installation ......................................................................................... 7 Required Components to Enable Maximus Technology ................................................ 7 Quadro Professional Graphics ........................................................................... 8 Tesla C2075 ................................................................................................ 8 NVIDIA Quadro Professional Graphics Driver ......................................................... 9 Implementing the Maximus Platform .................................................................. 9 Requirements
    [Show full text]
  • Nvidia Tesla Product Overview
    NVIDIA Tesla NVIDIA Tesla GPU Computing Solutions for HPC Revolutionary NVIDIA® Tesla™ high include a Thread Execution Compatible Solutions performance computing solutions Manager to coordinate the As an industry-standard solution, put personal supercomputing into concurrent execution of thousands Tesla easily fits into existing the hands of individual scientists of computing threads and a HPC environments. Available and engineers by expanding the Parallel Data Cache enabling products include a Tesla C870 capability of any workstation or computing threads to share data GPU computing processor for server with the power of GPU easily, delivering results in less users to upgrade their existing computing. Scientific and technical time. workstation, a Tesla D870 deskside professionals now have an supercomputer to add additional incredible opportunity to expand C for the GPU performance alongside a workstation, and a Tesla S870 GPU their ability to solve problems The world’s only C-language computing server for deployment previously impossible with current development environment for within an enterprise data center. computing approaches. the GPU, the NVIDIA CUDA™ software development kit includes Used in tandem with multi-core Parallel Performance a standard C compiler, hardware CPU systems, Tesla solutions provide a flexible computing Tesla computing solutions enable debugger tools, and a performance platform that runs on both users to process large datasets profiler for simplified application Microsoft® Windows® and Linux® with a massively multi-threaded development. computing architecture. By operating system environments. developing a parallel architecture Developer Community from the ground up, NVIDIA has NVIDIA is the catalyst for the designed its new Tesla computing largest GPU computing developer products to meet the requirements community.
    [Show full text]