Manycore GPU Architectures and Programming, Part 1
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Release Notes for X11R6.8.2 the X.Orgfoundation the Xfree86 Project, Inc
Release Notes for X11R6.8.2 The X.OrgFoundation The XFree86 Project, Inc. 9February 2005 Abstract These release notes contains information about features and their status in the X.Org Foundation X11R6.8.2 release. It is based on the XFree86 4.4RC2 RELNOTES docu- ment published by The XFree86™ Project, Inc. Thereare significant updates and dif- ferences in the X.Orgrelease as noted below. 1. Introduction to the X11R6.8.2 Release The release numbering is based on the original MIT X numbering system. X11refers to the ver- sion of the network protocol that the X Window system is based on: Version 11was first released in 1988 and has been stable for 15 years, with only upwardcompatible additions to the coreX protocol, a recordofstability envied in computing. Formal releases of X started with X version 9 from MIT;the first commercial X products werebased on X version 10. The MIT X Consortium and its successors, the X Consortium, the Open Group X Project Team, and the X.OrgGroup released versions X11R3 through X11R6.6, beforethe founding of the X.OrgFoundation. Therewill be futuremaintenance releases in the X11R6.8.x series. However,efforts arewell underway to split the X distribution into its modular components to allow for easier maintenance and independent updates. We expect a transitional period while both X11R6.8 releases arebeing fielded and the modular release completed and deployed while both will be available as different consumers of X technology have different constraints on deployment. Wehave not yet decided how the modular X releases will be numbered. We encourage you to submit bug fixes and enhancements to bugzilla.freedesktop.orgusing the xorgproduct, and discussions on this server take place on <[email protected]>. -
Nvidia Geforce 6 Series Specifications
NVIDIA GEFORCE 6 SERIES PRODUCT OVERVIEW DECEMBER 2004v06 NVIDIA GEFORCE 6 SERIES SPECIFICATIONS CINEFX 3.0 SHADING ARCHITECTURE ULTRASHADOW II TECHNOLOGY ADVANCED ENGINEERING • Vertex Shaders • Designed to enhance the performance of • Designed for PCI Express x16 ° Support for Microsoft DirectX 9.0 shadow-intensive games, like id Software’s • Support for AGP 8X including Fast Writes and Vertex Shader 3.0 Doom 3 sideband addressing Displacement mapping 3 • Designed for high-speed GDDR3 memory ° TURBOCACHE TECHNOLOGY Geometry instancing • Advanced thermal management and thermal ° • Shares the capacity and bandwidth of Infinite length vertex programs monitoring ° dedicated video memory and dynamically • Pixel Shaders available system memory for optimal system NVIDIA® DIGITAL VIBRANCE CONTROL™ Support for DirectX 9.0 Pixel Shader 3.0 ° performance (DVC) 3.0 Full pixel branching support ° • DVC color controls PC graphics such as photos, videos, and games require a Support for Multiple Render Targets (MRTs) PUREVIDEO TECHNOLOGY4 ° • DVC image sharpening controls ° Infinite length pixel programs • Adaptable programmable video processor lot of processing power. Without any help, the CPU • Next-Generation Texture Engine • High-definition MPEG-2 hardware acceleration OPERATING SYSTEMS ° Up to 16 textures per rendering pass • High-quality video scaling and filtering • Windows XP must handle all of the system and graphics ° Support for 16-bit floating point format • DVD and HDTV-ready MPEG-2 decoding up to • Windows ME and 32-bit floating point format 1920x1080i resolution • Windows 2000 processing which can result in decreased system ° Support for non-power of two textures • Display gamma correction • Windows 9X ° Support for sRGB texture format for • Microsoft® Video Mixing Renderer (VMR) • Linux performance. -
Stephen Clarke-Willson
Contact Stephen Clarke-Willson www.linkedin.com/in/drstephencw Programmer, Producer, Executive (LinkedIn) Sammamish www.arena.net (Company) www.above-the-garage.com (Personal) Summary above-the-garage.com/blog (Blog) Software technology development leadership and management. Top Skills Specialties: Technical / Product team building and management; Systems Programming System Architecture experience as first, second and third level manager in fast growing Game Development companies; systems programming, systems architecture, technology development. Publications Guild Wars Microservices and 24/7 Uptime Guild Wars 2 - Scaling from one to Experience millions Applying Game Design To Virtual NCSOFT Environments VP of Technology Nano-Plasm March 2019 - Present (1 year 7 months) Bellevue, WA ArenaNet LLC 13 years 6 months Programmer in the role of Studio Technical Director May 2013 - March 2019 (5 years 11 months) Bellevue, WA Lead engineering staff (about 100 members) for "gaming as a service" with continuous high volume content creation and delivery at MMO scale. Translate business objectives into innovative yet achievable technical challenges. Created technical unit with flat reporting structure and peer input reviews. Programmer in the roles of Server Programmer / Server Team Lead October 2005 - April 2013 (7 years 7 months) Developing multi-threaded, restartable, dynamically updatable, high performance, internet-resilient, bug free server code for the MMO Guild Wars (1 and 2). Above the Garage Productions Programmer / Owner Page 1 of 4 May 2004 - October 2005 (1 year 6 months) Game Technology Developer, Above the Garage Productions Developed downloadable music system "DirectSong.com" (from payment system [PayPal] to delivery system to embedded music player using Microsoft WMA technology). -
Reviving the Development of Openchrome
Reviving the Development of OpenChrome Kevin Brace OpenChrome Project Maintainer / Developer XDC2017 September 21st, 2017 Outline ● About Me ● My Personal Story Behind OpenChrome ● Background on VIA Chrome Hardware ● The History of OpenChrome Project ● Past Releases ● Observations about Standby Resume ● Developmental Philosophy ● Developmental Challenges ● Strategies for Further Development ● Future Plans 09/21/2017 XDC2017 2 About Me ● EE (Electrical Engineering) background (B.S.E.E.) who specialized in digital design / computer architecture in college (pretty much the only undergraduate student “still” doing this stuff where I attended college) ● Graduated recently ● First time conference presenter ● Very experienced with Xilinx FPGA (Spartan-II through 7 Series FPGA) ● Fluent in Verilog / VHDL design and verification ● Interest / design experience with external communication interfaces (PCI / PCIe) and external memory interfaces (SDRAM / DDR3 SDRAM) ● Developed a simple DMA engine for PCI I/F validation w/Windows WDM (Windows Driver Model) kernel device driver ● Almost all the knowledge I have is self taught (university engineering classes were not very useful) 09/21/2017 XDC2017 3 Motivations Behind My Work ● General difficulty in obtaining meaningful employment in the digital hardware design field (too many students in the field, difficulty obtaining internship, etc.) ● Collects and repairs abandoned computer hardware (It’s like rescuing puppies!) ● Owns 100+ desktop computers and 20+ laptop computers (mostly abandoned old stuff I -
NVIDIA Opengl in 2012 Mark Kilgard
NVIDIA OpenGL in 2012 Mark Kilgard • Principal System Software Engineer – OpenGL driver and API evolution – Cg (“C for graphics”) shading language – GPU-accelerated path rendering • OpenGL Utility Toolkit (GLUT) implementer • Author of OpenGL for the X Window System • Co-author of Cg Tutorial Outline • OpenGL’s importance to NVIDIA • OpenGL API improvements & new features – OpenGL 4.2 – Direct3D interoperability – GPU-accelerated path rendering – Kepler Improvements • Bindless Textures • Linux improvements & new features • Cg 3.1 update NVIDIA’s OpenGL Leverage Cg GeForce Parallel Nsight Tegra Quadro OptiX Example of Hybrid Rendering with OptiX OpenGL (Rasterization) OptiX (Ray tracing) Parallel Nsight Provides OpenGL Profiling Configure Application Trace Settings Parallel Nsight Provides OpenGL Profiling Magnified trace options shows specific OpenGL (and Cg) tracing options Parallel Nsight Provides OpenGL Profiling Parallel Nsight Provides OpenGL Profiling Trace of mix of OpenGL and CUDA shows glFinish & OpenGL draw calls Only Cross Platform 3D API OpenGL 3D Graphics API • cross-platform • most functional • peak performance • open standard • inter-operable • well specified & documented • 20 years of compatibility OpenGL Spawns Closely Related Standards Congratulations: WebGL officially approved, February 2012 “The web is now 3D enabled” Buffer and OpenGL 4 – DirectX 11 Superset Event Interop • Interop with a complete compute solution – OpenGL is for graphics – CUDA / OpenCL is for compute • Shaders can be saved to and loaded from binary -
Gs-35F-4677G
March 2013 NCS Technologies, Inc. Information Technology (IT) Schedule Contract Number: GS-35F-4677G FEDERAL ACQUISTIION SERVICE INFORMATION TECHNOLOGY SCHEDULE PRICELIST GENERAL PURPOSE COMMERCIAL INFORMATION TECHNOLOGY EQUIPMENT Special Item No. 132-8 Purchase of Hardware 132-8 PURCHASE OF EQUIPMENT FSC CLASS 7010 – SYSTEM CONFIGURATION 1. End User Computer / Desktop 2. Professional Workstation 3. Server 4. Laptop / Portable / Notebook FSC CLASS 7-25 – INPUT/OUTPUT AND STORAGE DEVICES 1. Display 2. Network Equipment 3. Storage Devices including Magnetic Storage, Magnetic Tape and Optical Disk NCS TECHNOLOGIES, INC. 7669 Limestone Drive Gainesville, VA 20155-4038 Tel: (703) 621-1700 Fax: (703) 621-1701 Website: www.ncst.com Contract Number: GS-35F-4677G – Option Year 3 Period Covered by Contract: May 15, 1997 through May 14, 2017 GENERAL SERVICE ADMINISTRATION FEDERAL ACQUISTIION SERVICE Products and ordering information in this Authorized FAS IT Schedule Price List is also available on the GSA Advantage! System. Agencies can browse GSA Advantage! By accessing GSA’s Home Page via Internet at www.gsa.gov. TABLE OF CONTENTS INFORMATION FOR ORDERING OFFICES ............................................................................................................................................................................................................................... TC-1 SPECIAL NOTICE TO AGENCIES – SMALL BUSINESS PARTICIPATION 1. Geographical Scope of Contract ............................................................................................................................................................................................................................. -
Energy-Efficient VLSI Architectures for Next
UNIVERSITY OF CALIFORNIA Los Angeles Energy-Efficient VLSI Architectures for Next- Generation Software-Defined and Cognitive Radios A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Electrical Engineering by Fang-Li Yuan 2014 c Copyright by Fang-Li Yuan 2014 ABSTRACT OF THE DISSERTATION Energy-Efficient VLSI Architectures for Next- Generation Software-Defined and Cognitive Radios by Fang-Li Yuan Doctor of Philosophy in Electrical Engineering University of California, Los Angeles, 2014 Professor Dejan Markovic,´ Chair Dedicated radio hardware is no longer promising as it was in the past. Today, the support of diverse standards dictates more flexible solutions. Software-defined radio (SDR) provides the flexibility by replacing dedicated blocks (i.e. ASICs) with more general processors to adapt to various functions, standards and even allow mutable de- sign changes. However, such replacement generally incurs significant efficiency loss in circuits, hindering its feasibility for energy-constrained devices. The capability of dy- namic and blind spectrum analysis, as featured in the cognitive radio (CR) technology, makes chip implementation even more challenging. This work discusses several design techniques to achieve near-ASIC energy effi- ciency while providing the flexibility required by software-defined and cognitive radios. The algorithm-architecture co-design is used to determine domain-specific dataflow ii structures to achieve the right balance between energy efficiency and flexibility. The flexible instruction-set-architecture (ISA), the multi-scale interconnects, and the multi- core dynamic scheduling are also proposed to reduce the energy overhead. We demon- strate these concepts on two real-time blind classification chips for CR spectrum anal- ysis, as well as a 16-core processor for baseband SDR signal processing. -
Developer Tools Showcase
Developer Tools Showcase Randy Fernando Developer Tools Product Manager NVISION 2008 Software Content Creation Performance Education Development FX Composer Shader PerfKit Conference Presentations Debugger mental mill PerfHUD Whitepapers Artist Edition Direct3D SDK PerfSDK GPU Programming Guide NVIDIA OpenGL SDK Shader Library GLExpert Videos CUDA SDK NV PIX Plug‐in Photoshop Plug‐ins Books Cg Toolkit gDEBugger GPU Gems 3 Texture Tools NVSG GPU Gems 2 Melody PhysX SDK ShaderPerf GPU Gems PhysX Plug‐Ins PhysX VRD PhysX Tools The Cg Tutorial NVIDIA FX Composer 2.5 The World’s Most Advanced Shader Authoring Environment DirectX 10 Support NVIDIA Shader Debugger Support ShaderPerf 2.0 Integration Visual Models & Styles Particle Systems Improved User Interface Particle Systems All-New Start Page 350Z Sample Project Visual Models & Styles Other Major Features Shader Creation Wizard Code Editor Quickly create common shaders Full editor with assisted Shader Library code generation Hundreds of samples Properties Panel Texture Viewer HDR Color Picker Materials Panel View, organize, and apply textures Even More Features Automatic Light Binding Complete Scripting Support Support for DirectX 10 (Geometry Shaders, Stream Out, Texture Arrays) Support for COLLADA, .FBX, .OBJ, .3DS, .X Extensible Plug‐in Architecture with SDK Customizable Layouts Semantic and Annotation Remapping Vertex Attribute Packing Remote Control Capability New Sample Projects 350Z Visual Styles Atmospheric Scattering DirectX 10 PCSS Soft Shadows Materials Post‐Processing Simple Shadows -
GPU-Based Deep Learning Inference
Whitepaper GPU-Based Deep Learning Inference: A Performance and Power Analysis November 2015 1 Contents Abstract ......................................................................................................................................................... 3 Introduction .................................................................................................................................................. 3 Inference versus Training .............................................................................................................................. 4 GPUs Excel at Neural Network Inference ..................................................................................................... 5 Inference Optimizations in Caffe and cuDNN 4 ........................................................................................ 5 Experimental Setup and Testing Methodology ........................................................................................ 7 Inference on Small and Large GPUs .......................................................................................................... 8 Conclusion ................................................................................................................................................... 10 References .................................................................................................................................................. 10 2 Abstract Deep learning methods are revolutionizing various areas of machine perception. On a -
Download Gtx 970 Driver Download Gtx 970 Driver
download gtx 970 driver Download gtx 970 driver. Completing the CAPTCHA proves you are a human and gives you temporary access to the web property. What can I do to prevent this in the future? If you are on a personal connection, like at home, you can run an anti-virus scan on your device to make sure it is not infected with malware. If you are at an office or shared network, you can ask the network administrator to run a scan across the network looking for misconfigured or infected devices. Another way to prevent getting this page in the future is to use Privacy Pass. You may need to download version 2.0 now from the Chrome Web Store. Cloudflare Ray ID: 67a229f54fd4c3c5 • Your IP : 188.246.226.140 • Performance & security by Cloudflare. GeForce Windows 10 Driver. NVIDIA has been working closely with Microsoft on the development of Windows 10 and DirectX 12. Coinciding with the arrival of Windows 10, this Game Ready driver includes the latest tweaks, bug fixes, and optimizations to ensure you have the best possible gaming experience. Game Ready Best gaming experience for Windows 10. GeForce GTX TITAN X, GeForce GTX TITAN, GeForce GTX TITAN Black, GeForce GTX TITAN Z. GeForce 900 Series: GeForce GTX 980 Ti, GeForce GTX 980, GeForce GTX 970, GeForce GTX 960. GeForce 700 Series: GeForce GTX 780 Ti, GeForce GTX 780, GeForce GTX 770, GeForce GTX 760, GeForce GTX 760 Ti (OEM), GeForce GTX 750 Ti, GeForce GTX 750, GeForce GTX 745, GeForce GT 740, GeForce GT 730, GeForce GT 720, GeForce GT 710, GeForce GT 705. -
Arxiv:1809.03668V2 [Cs.LG] 20 Jan 2019 17, 20, 21]
Comparing Computing Platforms for Deep Learning on a Humanoid Robot Alexander Biddulph∗, Trent Houliston, Alexandre Mendes, and Stephan K. Chalup School of Electrical Engineering and Computing The University of Newcastle, Callaghan, NSW, 2308, Australia. [email protected] Abstract. The goal of this study is to test two different computing plat- forms with respect to their suitability for running deep networks as part of a humanoid robot software system. One of the platforms is the CPU- centered Intel R NUC7i7BNH and the other is a NVIDIA R Jetson TX2 system that puts more emphasis on GPU processing. The experiments addressed a number of benchmarking tasks including pedestrian detec- tion using deep neural networks. Some of the results were unexpected but demonstrate that platforms exhibit both advantages and disadvantages when taking computational performance and electrical power require- ments of such a system into account. Keywords: deep learning, robot vision, gpu computing, low powered devices 1 Introduction Deep learning comes with challenges with respect to computational resources and training data requirements [6, 13]. Some of the breakthroughs in deep neu- ral networks (DNNs) only became possible through the availability of massive computing systems or through careful co-design of software and hardware. For example, the AlexNet system presented in [15] was implemented efficiently util- ising two NVIDIA R GTX580 GPUs for training. Machine learning on robots has been a growing area over the past years [4, arXiv:1809.03668v2 [cs.LG] 20 Jan 2019 17, 20, 21]. It has become increasingly desirable to employ DNNs in low powered devices, among them humanoid robot systems, specifically for complex tasks such as object detection, walk learning, and behaviour learning. -
Release 65 Notes
ForceWare Graphics Drivers Release 65 Notes Version 66.81 Windows XP / 2000 Windows 98 / ME NVIDIA Corporation October 4, 2004 Published by NVIDIA Corporation 2701 San Tomas Expressway Santa Clara, CA 95050 Notice ALL NVIDIA DESIGN SPECIFICATIONS, REFERENCE BOARDS, FILES, DRAWINGS, DIAGNOSTICS, LISTS, AND OTHER DOCUMENTS (TOGETHER AND SEPARATELY, “MATERIALS”) ARE BEING PROVIDED “AS IS.” NVIDIA MAKES NO WARRANTIES, EXPRESSED, IMPLIED, STATUTORY, OR OTHERWISE WITH RESPECT TO THE MATERIALS, AND EXPRESSLY DISCLAIMS ALL IMPLIED WARRANTIES OF NONINFRINGEMENT, MERCHANTABILITY, AND FITNESS FOR A PARTICULAR PURPOSE. Information furnished is believed to be accurate and reliable. However, NVIDIA Corporation assumes no responsibility for the consequences of use of such information or for any infringement of patents or other rights of third parties that may result from its use. No license is granted by implication or otherwise under any patent or patent rights of NVIDIA Corporation. Specifications mentioned in this publication are subject to change without notice. This publication supersedes and replaces all information previously supplied. NVIDIA Corporation products are not authorized for use as critical components in life support devices or systems without express written approval of NVIDIA Corporation. Trademarks NVIDIA, the NVIDIA logo, 3DFX, 3DFX INTERACTIVE, the 3dfx Logo, STB, STB Systems and Design, the STB Logo, the StarBox Logo, NVIDIA nForce, GeForce, NVIDIA Quadro, NVDVD, NVIDIA Personal Cinema, NVIDIA Soundstorm, Vanta, TNT2, TNT, RIVA,