CS 610: GPU Architectures and CUDA Programming Swarnendu Biswas
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GPU Architecture • Display Controller • Designing for Safety • Vision Processing
i.MX 8 GRAPHICS ARCHITECTURE FTF-DES-N1940 RAFAL MALEWSKI HEAD OF GRAPHICS TECH ENGINEERING CENTER MAY 18, 2016 PUBLIC USE AGENDA • i.MX 8 Series Scalability • GPU Architecture • Display Controller • Designing for Safety • Vision Processing 1 PUBLIC USE #NXPFTF 1 PUBLIC USE #NXPFTF i.MX is… 2 PUBLIC USE #NXPFTF SoC Scalability = Investment Re-Use Replace the Chip a Increase capability. (Pin, Software, IP compatibility among parts) 3 PUBLIC USE #NXPFTF i.MX 8 Series GPU Cores • Dual Core GPU Up to 4 displays Accelerated ARM Cores • 16 Vec4 Shaders Vision Cortex-A53 | Cortex-A72 8 • Up to 128 GFLOPS • 64 execution units 8QuadMax 8 • Tessellation/Geometry total pixels Shaders Pin Compatibility Pin • Dual Core GPU Up to 4 displays Accelerated • 8 Vec4 Shaders Vision 4 • Up to 64 GFLOPS • 32 execution units 4 total pixels 8QuadPlus • Tessellation/Geometry Compatibility Software Shaders • Dual Core GPU Up to 4 displays Accelerated • 8 Vec4 Shaders Vision 4 • Up to 64 GFLOPS 4 • 32 execution units 8Quad • Tessellation/Geometry total pixels Shaders • Single Core GPU Up to 2 displays Accelerated • 8 Vec4 Shaders 2x 1080p total Vision • Up to 64 GFLOPS pixels Compatibility Pin 8 • 32 execution units 8Dual8Solo • Tessellation/Geometry Shaders • Single Core GPU Up to 2 displays Accelerated • 4 Vec4 Shaders 2x 1080p total Vision • Up to 32 GFLOPS pixels 4 • 16 execution units 8DualLite8Solo • Tessellation/Geometry Shaders 4 PUBLIC USE #NXPFTF i.MX 8 Series – The Doubles GPU Cores • Dual Core GPU Up to 4 displays Accelerated • 16 Vec4 Shaders Vision -
Fast Calculation of the Lomb-Scargle Periodogram Using Graphics Processing Units 3
Draft version August 7, 2018 A Preprint typeset using LTEX style emulateapj v. 11/10/09 FAST CALCULATION OF THE LOMB-SCARGLE PERIODOGRAM USING GRAPHICS PROCESSING UNITS R. H. D. Townsend Department of Astronomy, University of Wisconsin-Madison, Sterling Hall, 475 N. Charter Street, Madison, WI 53706, USA; [email protected] Draft version August 7, 2018 ABSTRACT I introduce a new code for fast calculation of the Lomb-Scargle periodogram, that leverages the computing power of graphics processing units (GPUs). After establishing a background to the newly emergent field of GPU computing, I discuss the code design and narrate key parts of its source. Benchmarking calculations indicate no significant differences in accuracy compared to an equivalent CPU-based code. However, the differences in performance are pronounced; running on a low-end GPU, the code can match 8 CPU cores, and on a high-end GPU it is faster by a factor approaching thirty. Applications of the code include analysis of long photometric time series obtained by ongoing satellite missions and upcoming ground-based monitoring facilities; and Monte-Carlo simulation of periodogram statistical properties. Subject headings: methods: data analysis — methods: numerical — techniques: photometric — stars: oscillations 1. INTRODUCTION of the newly emergent field of GPU computing; then, Astronomical time-series observations are often charac- Section 3 reviews the formalism defining the L-S peri- terized by uneven temporal sampling (e.g., due to trans- odogram, and Section 4 presents a GPU-based code im- formation to the heliocentric frame) and/or non-uniform plementing this formalism. Benchmarking calculations coverage (e.g., from day/night cycles, or radiation belt to evaluate the accuracy and performance of the code passages). -
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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. -
Directx and GPU (Nvidia-Centric) History Why
10/12/09 DirectX and GPU (Nvidia-centric) History DirectX 6 DirectX 7! ! DirectX 8! DirectX 9! DirectX 9.0c! Multitexturing! T&L ! SM 1.x! SM 2.0! SM 3.0! DirectX 5! Riva TNT GeForce 256 ! ! GeForce3! GeForceFX! GeForce 6! Riva 128! (NV4) (NV10) (NV20) Cg! (NV30) (NV40) XNA and Programmable Shaders DirectX 2! 1996! 1998! 1999! 2000! 2001! 2002! 2003! 2004! DirectX 10! Prof. Hsien-Hsin Sean Lee SM 4.0! GTX200 NVidia’s Unified Shader Model! Dualx1.4 billion GeForce 8 School of Electrical and Computer 3dfx’s response 3dfx demise ! Transistors first to Voodoo2 (G80) ~1.2GHz Engineering Voodoo chip GeForce 9! Georgia Institute of Technology 2006! 2008! GT 200 2009! ! GT 300! Adapted from David Kirk’s slide Why Programmable Shaders Evolution of Graphics Processing Units • Hardwired pipeline • Pre-GPU – Video controller – Produces limited effects – Dumb frame buffer – Effects look the same • First generation GPU – PCI bus – Gamers want unique look-n-feel – Rasterization done on GPU – Multi-texturing somewhat alleviates this, but not enough – ATI Rage, Nvidia TNT2, 3dfx Voodoo3 (‘96) • Second generation GPU – Less interoperable, less portable – AGP – Include T&L into GPU (D3D 7.0) • Programmable Shaders – Nvidia GeForce 256 (NV10), ATI Radeon 7500, S3 Savage3D (’98) – Vertex Shader • Third generation GPU – Programmable vertex and fragment shaders (D3D 8.0, SM1.0) – Pixel or Fragment Shader – Nvidia GeForce3, ATI Radeon 8500, Microsoft Xbox (’01) – Starting from DX 8.0 (assembly) • Fourth generation GPU – Programmable vertex and fragment shaders -
MSI Afterburner V4.6.4
MSI Afterburner v4.6.4 MSI Afterburner is ultimate graphics card utility, co-developed by MSI and RivaTuner teams. Please visit https://msi.com/page/afterburner to get more information about the product and download new versions SYSTEM REQUIREMENTS: ...................................................................................................................................... 3 FEATURES: ............................................................................................................................................................. 3 KNOWN LIMITATIONS:........................................................................................................................................... 4 REVISION HISTORY: ................................................................................................................................................ 5 VERSION 4.6.4 .............................................................................................................................................................. 5 VERSION 4.6.3 (PUBLISHED ON 03.03.2021) .................................................................................................................... 5 VERSION 4.6.2 (PUBLISHED ON 29.10.2019) .................................................................................................................... 6 VERSION 4.6.1 (PUBLISHED ON 21.04.2019) .................................................................................................................... 7 VERSION 4.6.0 (PUBLISHED ON -
Graphics Shaders Mike Hergaarden January 2011, VU Amsterdam
Graphics shaders Mike Hergaarden January 2011, VU Amsterdam [Source: http://unity3d.com/support/documentation/Manual/Materials.html] Abstract Shaders are the key to finalizing any image rendering, be it computer games, images or movies. Shaders have greatly improved the output of computer generated media; from photo-realistic computer generated humans to more vivid cartoon movies. Furthermore shaders paved the way to general-purpose computation on GPU (GPGPU). This paper introduces shaders by discussing the theory and practice. Introduction A shader is a piece of code that is executed on the Graphics Processing Unit (GPU), usually found on a graphics card, to manipulate an image before it is drawn to the screen. Shaders allow for various kinds of rendering effect, ranging from adding an X-Ray view to adding cartoony outlines to rendering output. The history of shaders starts at LucasFilm in the early 1980’s. LucasFilm hired graphics programmers to computerize the special effects industry [1]. This proved a success for the film/ rendering industry, especially at Pixars Toy Story movie launch in 1995. RenderMan introduced the notion of Shaders; “The Renderman Shading Language allows material definitions of surfaces to be described in not only a simple manner, but also highly complex and custom manner using a C like language. Using this method as opposed to a pre-defined set of materials allows for complex procedural textures, new shading models and programmable lighting. Another thing that sets the renderers based on the RISpec apart from many other renderers, is the ability to output arbitrary variables as an image—surface normals, separate lighting passes and pretty much anything else can be output from the renderer in one pass.” [1] The term shader was first only used to refer to “pixel shaders”, but soon enough new uses of shaders such as vertex and geometry shaders were introduced, making the term shaders more general. -
Geforce 500 Series Graphics Cards, Including Without Limitation the Geforce GTX
c) GeForce 500 series graphics cards, including without limitation the GeForce GTX 580, GeForce GTX 570, GeForce GTX 560 Ti, GeForce GTX 560, GeForce GTX 550 Ti, and GeForce GT 520; d) GeForce 400 series graphics cards, including without limitation the GcForcc GTX 480, GcForcc GTX 470, GeForce GTX 460, GeForce GTS 450, GeForce GTS 440, and GcForcc GT 430; and c) GcForcc 200 series graphics cards, including without limitation the GeForce GT 240, GcForcc GT 220, and GeForce 210. 134. On information and belief, the Accused ’734 Biostar Products contain at least one of the following Accused NVIDIA ’734 Products that infringe at least claims 1-3, 7-9, 12-15, 17, and 19 of the ’734 patent, literally or under the doctrine of equivalents: the GFIOO, GFl04, GF108, GF110, GF114, GF116, GF119, GK104, GKIO6, GK107, GK208, GM107, GT2l5, GT2l6, and GT2l8, which are infringing NVIDIA GPUs. (See Section VI.D.1 and claim charts attached as Exhibit 28.) 3. ECS 135. On information and belief, ECS imports, sells for importation, and/or sells after importation into the United States, Accused Products that incorporate Accused NVIDIA ’734 Products (the “Accused PCS ’734 Products”) and therefore infringe the ’734 patent, literally or under the doctrine of equivalents. 136. On information and belief, the Accused ECS "/34 Products include at least the following products that directly infringe at least claims 1-3, 7-9, 12-15, 17, and 19 of the ’734 patent, literally or under the doctrine of equivalents: a) GeForce 600 series graphics cards, including without limitation -
CPU-GPU Benchmark Description
UC San Diego UC San Diego Electronic Theses and Dissertations Title Heterogeneity and Density Aware Design of Computing Systems Permalink https://escholarship.org/uc/item/9qd6w8cw Author Arora, Manish Publication Date 2018 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Heterogeneity and Density Aware Design of Computing Systems A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science (Computer Engineering) by Manish Arora Committee in charge: Professor Dean M. Tullsen, Chair Professor Renkun Chen Professor George Porter Professor Tajana Simunic Rosing Professor Steve Swanson 2018 Copyright Manish Arora, 2018 All rights reserved. The dissertation of Manish Arora is approved, and it is ac- ceptable in quality and form for publication on microfilm and electronically: Chair University of California, San Diego 2018 iii DEDICATION To my family and friends. iv EPIGRAPH Do not be embarrassed by your failures, learn from them and start again. —Richard Branson If something’s important enough, you should try. Even if the probable outcome is failure. —Elon Musk v TABLE OF CONTENTS Signature Page . iii Dedication . iv Epigraph . v Table of Contents . vi List of Figures . viii List of Tables . x Acknowledgements . xi Vita . xiii Abstract of the Dissertation . xvi Chapter 1 Introduction . 1 1.1 Design for Heterogeneity . 2 1.1.1 Heterogeneity Aware Design . 3 1.2 Design for Density . 6 1.2.1 Density Aware Design . 7 1.3 Overview of Dissertation . 8 Chapter 2 Background . 10 2.1 GPGPU Computing . 10 2.2 CPU-GPU Systems . -
High-Performance and Energy-Efficient Irregular Graph Processing on GPU Architectures
High-Performance and Energy-Efficient Irregular Graph Processing on GPU architectures Albert Segura Salvador Doctor of Philosophy Department of Computer Architecture Universitat Politècnica de Catalunya Advisors: Jose-Maria Arnau Antonio González July, 2020 2 Abstract Graph processing is an established and prominent domain that is the foundation of new emerging applications in areas such as Data Analytics, Big Data and Machine Learning. Appli- cations such as road navigational systems, recommendation systems, social networks, Automatic Speech Recognition (ASR) and many others are illustrative cases of graph-based datasets and workloads. Demand for higher processing of large graph-based workloads is expected to rise due to nowadays trends towards increased data generation and gathering, higher inter-connectivity and inter-linkage, and in general a further knowledge-based society. An increased demand that poses challenges to current and future graph processing architectures. To effectively perform graph processing, the large amount of data employed in these domains requires high throughput architectures such as GPGPU. Although the processing of large graph-based workloads exhibits a high degree of parallelism, the memory access patterns tend to be highly irregular, leading to poor GPGPU efficiency due to memory divergence. Graph datasets are sparse, highly unpredictable and unstructured which causes the irregular access patterns and low computation per data ratio, further lowering GPU utilization. The purpose of this thesis is to characterize the bottlenecks and limitations of irregular graph processing on GPGPU architectures in order to propose architectural improvements and extensions that deliver improved performance, energy efficiency and overall increased GPGPU efficiency and utilization. In order to ameliorate these issues, GPGPU graph applications perform stream compaction operations which process the subset of active nodes/edges so subsequent steps work on compacted dataset. -
Model System of Zirconium Oxide An
First-principles based treatment of charged species equilibria at electrochemical interfaces: model system of zirconium oxide and titanium oxide by Jing Yang B.S., Physics, Peking University, China Submitted to the Department of Materials Science and Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the MASSACHUSETTS INSTITUTE OF TECHONOLOGY February 2020 © Massachusetts Institute of Technology 2020. All rights reserved. Signature of Author: Jing Yang Department of Materials Science and Engineering January 10th, 2020 Certified by: Bilge Yildiz Professor of Materials Science and Engineering And Professor of Nuclear Science and Engineering Thesis Supervisor Accepted by: Donald R. Sadoway John F. Elliott Professor of Materials Chemistry Chair, Department Committee on Graduate Studies 2 First-principles based treatment of charged species equilibria at electrochemical interfaces: model system of zirconium oxide and titanium oxide by Jing Yang Submitted to the Department of Materials Science and Engineering on Jan. 10th, 2020 in partial fulfillment of the requirements for the degree of Doctor of Philosophy Abstract Ionic defects are known to influence the magnetic, electronic and transport properties of oxide materials. Understanding defect chemistry provides guidelines for defect engineering in various applications including energy storage and conversion, corrosion, and neuromorphic computing devices. While DFT calculations have been proven as a powerful tool for modeling point defects in bulk oxide materials, challenges remain for linking atomistic results with experimentally-measurable materials properties, where impurities and complicated microstructures exist and the materials deviate from ideal bulk behavior. This thesis aims to bridge this gap on two aspects. First, we study the coupled electro-chemo-mechanical effects of ionic impurities in bulk oxide materials. -
Nvida Geforce Driver Download Geforce Game Ready Driver
nvida geforce driver download GeForce Game Ready Driver. Game Ready Drivers provide the best possible gaming experience for all major new releases. Prior to a new title launching, our driver team is working up until the last minute to ensure every performance tweak and bug fix is included for the best gameplay on day-1. Game Ready for Naraka: Bladepoint This new Game Ready Driver provides support for Naraka: Bladepoint, which utilizes NVIDIA DLSS and NVIDIA Reflex to boost performance by up to 60% at 4K and make you more competitive through the reduction of system latency. Additionally, this release also provides optimal support for the Back 4 Blood Open Beta and Psychonauts 2 and includes support for 7 new G-SYNC Compatible displays. Effective October 2021, Game Ready Driver upgrades, including performance enhancements, new features, and bug fixes, will be available for systems utilizing Maxwell, Pascal, Turing, and Ampere-series GPUs. Critical security updates will be available on systems utilizing desktop Kepler- series GPUs through September 2024. A complete list of desktop Kepler-series GeForce GPUs can be found here. NVIDIA TITAN Xp, NVIDIA TITAN X (Pascal), GeForce GTX TITAN X, GeForce GTX TITAN, GeForce GTX TITAN Black, GeForce GTX TITAN Z. GeForce 10 Series: GeForce GTX 1080 Ti, GeForce GTX 1080, GeForce GTX 1070 Ti, GeForce GTX 1070, GeForce GTX 1060, GeForce GTX 1050 Ti, GeForce GTX 1050, GeForce GT 1030, GeForce GT 1010. GeForce 900 Series: GeForce GTX 980 Ti, GeForce GTX 980, GeForce GTX 970, GeForce GTX 960, GeForce GTX 950. 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. -
GPU Accelerated Approach to Numerical Linear Algebra and Matrix Analysis with CFD Applications
University of Central Florida STARS HIM 1990-2015 2014 GPU Accelerated Approach to Numerical Linear Algebra and Matrix Analysis with CFD Applications Adam Phillips University of Central Florida Part of the Mathematics Commons Find similar works at: https://stars.library.ucf.edu/honorstheses1990-2015 University of Central Florida Libraries http://library.ucf.edu This Open Access is brought to you for free and open access by STARS. It has been accepted for inclusion in HIM 1990-2015 by an authorized administrator of STARS. For more information, please contact [email protected]. Recommended Citation Phillips, Adam, "GPU Accelerated Approach to Numerical Linear Algebra and Matrix Analysis with CFD Applications" (2014). HIM 1990-2015. 1613. https://stars.library.ucf.edu/honorstheses1990-2015/1613 GPU ACCELERATED APPROACH TO NUMERICAL LINEAR ALGEBRA AND MATRIX ANALYSIS WITH CFD APPLICATIONS by ADAM D. PHILLIPS A thesis submitted in partial fulfilment of the requirements for the Honors in the Major Program in Mathematics in the College of Sciences and in The Burnett Honors College at the University of Central Florida Orlando, Florida Spring Term 2014 Thesis Chair: Dr. Bhimsen Shivamoggi c 2014 Adam D. Phillips All Rights Reserved ii ABSTRACT A GPU accelerated approach to numerical linear algebra and matrix analysis with CFD applica- tions is presented. The works objectives are to (1) develop stable and efficient algorithms utilizing multiple NVIDIA GPUs with CUDA to accelerate common matrix computations, (2) optimize these algorithms through CPU/GPU memory allocation, GPU kernel development, CPU/GPU communication, data transfer and bandwidth control to (3) develop parallel CFD applications for Navier Stokes and Lattice Boltzmann analysis methods.