Graphics Processing Unit (GPU)

Size: px
Start display at page:

Download "Graphics Processing Unit (GPU)"

Transcription

1 Eric Scheler & Joshua Shear Graphics Processing Unit (GPU) Architecture and Applications

2 Agenda Origin of GPUs First GPU Models and capabilities GPUs then and now (with architecture breakdown) Graphics and Compute APIs Applications

3 Origin of GPUs Tape was simple to output for a computer Once CRT monitors were attached to computers displaying to them was more complex GPUs allowed for lots of parallel computation to output to the monitor in a timely manner

4 The First GPUs Television Interface Adaptors (TIA) Video & sound 40 x 192 Atari 2600 Companies Motorola, IBM, Yamaha, TI, Intel isbx 275 (right) 256 x color Interfaced via eight-bit isbx bus Supported: panning, scrolling, drawing lines, arcs, circles, rectangles, character/symbol painting and area fill Intel s isbx 275 Video Graphics Controller Board

5 The First GPUs - ATI Wonder Series ATI Graphics Solution (1986) 64KB DRAM CGA & MDA ATI VGA Wonder XL24 (1992) 512KB/1MB DRAM MDA, CGA, EGA, VGA, SVGA High end video card (last of Wonder series)

6 Architecture (AMD)

7 Architecture (NVidia)

8 Memory Bandwidth

9 Performance Over Time

10 Graphics Pipeline Vertex Processing Lighting per vertex Primitive Assembly Lines, triangles, points Rasterization Pixel positions Generate colored fragments Update framebuffer

11 Introduction of APIs Used by game engines for easy development on a wide variety of hardware Eventually, the use of GPUs for data computation was discovered and the APIs added computation calls

12 OpenGL OpenGL was the first, targeted at all major GPUs Started strictly as a graphics API in the 1990s Added compute support in the 2000s Usable on all GPUs (3Dfx, ATI, AMD, NVidia, Intel)

13 CUDA CUDA was developed by NVidia in the 2000s for compute uses Exclusive to NVidia GPUs Can be ported to work on Intel integrated graphics Has no graphical support Used by most companies that do GPU acceleration because of its ease of use for compute

14 Vulkan Vulkan is the new successor to OpenGL providing finer control over the hardware Difficult to use but offers much better performance over OpenGL Usable on all modern GPUs (Intel, AMD, NVidia)

15 Applications - MapReduce MapReduce, developed at Google, allows for large numbers of computers to work on massively parallel tasks When GPU accelerated, can perform far faster than with CPUs alone (+87% faster)

16 Deep Neural Networks (DNNs) DNNs require lots of independent neurons firing to generate an output The firing can be partially parallelized leading to much faster run times on GPUs Some GPUs such as the Tesla GV100 and the Titan V are including Tensor cores specifically optimized for DNNs Google Brain Project learned to recognize cats and people (deep learning) 2,000 CPUs became 12 NVIDIA GPUs

17 Monte Carlo

18 CryptoCurrency Mining

19 References -Graphics Pipeline pics (2) Old GPU Architecture Diagrams from AnandTech New GPU Architecture Diagrams from GamersNexus VRAM and RAM charts from TweakTown API Images from Khronos Group and NVidia Application images from various sources

ECE 571 Advanced Microprocessor-Based Design Lecture 18

ECE 571 Advanced Microprocessor-Based Design Lecture 18 ECE 571 Advanced Microprocessor-Based Design Lecture 18 Vince Weaver http://www.eece.maine.edu/ vweaver vincent.weaver@maine.edu 11 November 2014 Homework #4 comments Project/HW Reminder 1 Stuff from Last

More information

ECE 571 Advanced Microprocessor-Based Design Lecture 20

ECE 571 Advanced Microprocessor-Based Design Lecture 20 ECE 571 Advanced Microprocessor-Based Design Lecture 20 Vince Weaver http://www.eece.maine.edu/~vweaver vincent.weaver@maine.edu 12 April 2016 Project/HW Reminder Homework #9 was posted 1 Raspberry Pi

More information

Graphics Hardware. Instructor Stephen J. Guy

Graphics Hardware. Instructor Stephen J. Guy Instructor Stephen J. Guy Overview What is a GPU Evolution of GPU GPU Design Modern Features Programmability! Programming Examples Overview What is a GPU Evolution of GPU GPU Design Modern Features Programmability!

More information

Introduction to Computer Graphics (CS602) Lecture No 03 Graphics Systems

Introduction to Computer Graphics (CS602) Lecture No 03 Graphics Systems Introduction to Computer Graphics (CS602) Lecture No 03 Graphics Systems 3.1 Raster-Scan Systems Interactive raster graphics systems typically employ several processing units. In addition to the CPU, a

More information

CMPE 665:Multiple Processor Systems CUDA-AWARE MPI VIGNESH GOVINDARAJULU KOTHANDAPANI RANJITH MURUGESAN

CMPE 665:Multiple Processor Systems CUDA-AWARE MPI VIGNESH GOVINDARAJULU KOTHANDAPANI RANJITH MURUGESAN CMPE 665:Multiple Processor Systems CUDA-AWARE MPI VIGNESH GOVINDARAJULU KOTHANDAPANI RANJITH MURUGESAN Graphics Processing Unit Accelerate the creation of images in a frame buffer intended for the output

More information

Graphics Hardware. Graphics Processing Unit (GPU) is a Subsidiary hardware. With massively multi-threaded many-core. Dedicated to 2D and 3D graphics

Graphics Hardware. Graphics Processing Unit (GPU) is a Subsidiary hardware. With massively multi-threaded many-core. Dedicated to 2D and 3D graphics Why GPU? Chapter 1 Graphics Hardware Graphics Processing Unit (GPU) is a Subsidiary hardware With massively multi-threaded many-core Dedicated to 2D and 3D graphics Special purpose low functionality, high

More information

CSE 591/392: GPU Programming. Introduction. Klaus Mueller. Computer Science Department Stony Brook University

CSE 591/392: GPU Programming. Introduction. Klaus Mueller. Computer Science Department Stony Brook University CSE 591/392: GPU Programming Introduction Klaus Mueller Computer Science Department Stony Brook University First: A Big Word of Thanks! to the millions of computer game enthusiasts worldwide Who demand

More information

CSE 591: GPU Programming. Introduction. Entertainment Graphics: Virtual Realism for the Masses. Computer games need to have: Klaus Mueller

CSE 591: GPU Programming. Introduction. Entertainment Graphics: Virtual Realism for the Masses. Computer games need to have: Klaus Mueller Entertainment Graphics: Virtual Realism for the Masses CSE 591: GPU Programming Introduction Computer games need to have: realistic appearance of characters and objects believable and creative shading,

More information

Rendering Objects. Need to transform all geometry then

Rendering Objects. Need to transform all geometry then Intro to OpenGL Rendering Objects Object has internal geometry (Model) Object relative to other objects (World) Object relative to camera (View) Object relative to screen (Projection) Need to transform

More information

GPU Architecture and Function. Michael Foster and Ian Frasch

GPU Architecture and Function. Michael Foster and Ian Frasch GPU Architecture and Function Michael Foster and Ian Frasch Overview What is a GPU? How is a GPU different from a CPU? The graphics pipeline History of the GPU GPU architecture Optimizations GPU performance

More information

EECS 487: Interactive Computer Graphics

EECS 487: Interactive Computer Graphics EECS 487: Interactive Computer Graphics Lecture 21: Overview of Low-level Graphics API Metal, Direct3D 12, Vulkan Console Games Why do games look and perform so much better on consoles than on PCs with

More information

X. GPU Programming. Jacobs University Visualization and Computer Graphics Lab : Advanced Graphics - Chapter X 1

X. GPU Programming. Jacobs University Visualization and Computer Graphics Lab : Advanced Graphics - Chapter X 1 X. GPU Programming 320491: Advanced Graphics - Chapter X 1 X.1 GPU Architecture 320491: Advanced Graphics - Chapter X 2 GPU Graphics Processing Unit Parallelized SIMD Architecture 112 processing cores

More information

Graphics Architectures and OpenCL. Michael Doggett Department of Computer Science Lund university

Graphics Architectures and OpenCL. Michael Doggett Department of Computer Science Lund university Graphics Architectures and OpenCL Michael Doggett Department of Computer Science Lund university Overview Parallelism Radeon 5870 Tiled Graphics Architectures Important when Memory and Bandwidth limited

More information

Real - Time Rendering. Graphics pipeline. Michal Červeňanský Juraj Starinský

Real - Time Rendering. Graphics pipeline. Michal Červeňanský Juraj Starinský Real - Time Rendering Graphics pipeline Michal Červeňanský Juraj Starinský Overview History of Graphics HW Rendering pipeline Shaders Debugging 2 History of Graphics HW First generation Second generation

More information

CS GPU and GPGPU Programming Lecture 8+9: GPU Architecture 7+8. Markus Hadwiger, KAUST

CS GPU and GPGPU Programming Lecture 8+9: GPU Architecture 7+8. Markus Hadwiger, KAUST CS 380 - GPU and GPGPU Programming Lecture 8+9: GPU Architecture 7+8 Markus Hadwiger, KAUST Reading Assignment #5 (until March 12) Read (required): Programming Massively Parallel Processors book, Chapter

More information

GPGPU, 1st Meeting Mordechai Butrashvily, CEO GASS

GPGPU, 1st Meeting Mordechai Butrashvily, CEO GASS GPGPU, 1st Meeting Mordechai Butrashvily, CEO GASS Agenda Forming a GPGPU WG 1 st meeting Future meetings Activities Forming a GPGPU WG To raise needs and enhance information sharing A platform for knowledge

More information

Antonio R. Miele Marco D. Santambrogio

Antonio R. Miele Marco D. Santambrogio Advanced Topics on Heterogeneous System Architectures GPU Politecnico di Milano Seminar Room A. Alario 18 November, 2015 Antonio R. Miele Marco D. Santambrogio Politecnico di Milano 2 Introduction First

More information

Motivation Hardware Overview Programming model. GPU computing. Part 1: General introduction. Ch. Hoelbling. Wuppertal University

Motivation Hardware Overview Programming model. GPU computing. Part 1: General introduction. Ch. Hoelbling. Wuppertal University Part 1: General introduction Ch. Hoelbling Wuppertal University Lattice Practices 2011 Outline 1 Motivation 2 Hardware Overview History Present Capabilities 3 Programming model Past: OpenGL Present: CUDA

More information

Current Trends in Computer Graphics Hardware

Current Trends in Computer Graphics Hardware Current Trends in Computer Graphics Hardware Dirk Reiners University of Louisiana Lafayette, LA Quick Introduction Assistant Professor in Computer Science at University of Louisiana, Lafayette (since 2006)

More information

Spring 2009 Prof. Hyesoon Kim

Spring 2009 Prof. Hyesoon Kim Spring 2009 Prof. Hyesoon Kim Application Geometry Rasterizer CPU Each stage cane be also pipelined The slowest of the pipeline stage determines the rendering speed. Frames per second (fps) Executes on

More information

Spring 2011 Prof. Hyesoon Kim

Spring 2011 Prof. Hyesoon Kim Spring 2011 Prof. Hyesoon Kim Application Geometry Rasterizer CPU Each stage cane be also pipelined The slowest of the pipeline stage determines the rendering speed. Frames per second (fps) Executes on

More information

Graphics Processing Unit Architecture (GPU Arch)

Graphics Processing Unit Architecture (GPU Arch) Graphics Processing Unit Architecture (GPU Arch) With a focus on NVIDIA GeForce 6800 GPU 1 What is a GPU From Wikipedia : A specialized processor efficient at manipulating and displaying computer graphics

More information

GPU ARCHITECTURE Chris Schultz, June 2017

GPU ARCHITECTURE Chris Schultz, June 2017 GPU ARCHITECTURE Chris Schultz, June 2017 MISC All of the opinions expressed in this presentation are my own and do not reflect any held by NVIDIA 2 OUTLINE CPU versus GPU Why are they different? CUDA

More information

PART III. GPU Cards and Architectures. Dr. Christian Napoli, M.Sc.! Dpt. Mathematics and Informatics, University of Catania!

PART III. GPU Cards and Architectures. Dr. Christian Napoli, M.Sc.! Dpt. Mathematics and Informatics, University of Catania! Postgraduate course on Electronics and Informatics Engineering (M.Sc.) Training Course on Circuits Theory (prof. G. Capizzi)! Workshop on High performance computing and GPGPU computing Postgraduate course

More information

ECE 574 Cluster Computing Lecture 16

ECE 574 Cluster Computing Lecture 16 ECE 574 Cluster Computing Lecture 16 Vince Weaver http://web.eece.maine.edu/~vweaver vincent.weaver@maine.edu 26 March 2019 Announcements HW#7 posted HW#6 and HW#5 returned Don t forget project topics

More information

Portland State University ECE 588/688. Graphics Processors

Portland State University ECE 588/688. Graphics Processors Portland State University ECE 588/688 Graphics Processors Copyright by Alaa Alameldeen 2018 Why Graphics Processors? Graphics programs have different characteristics from general purpose programs Highly

More information

Vulkan: Architecture positive How Vulkan maps to PowerVR GPUs Kevin sun Lead Developer Support Engineer, APAC PowerVR Graphics.

Vulkan: Architecture positive How Vulkan maps to PowerVR GPUs Kevin sun Lead Developer Support Engineer, APAC PowerVR Graphics. Vulkan: Architecture positive How Vulkan maps to PowerVR GPUs Kevin sun Lead Developer Support Engineer, APAC PowerVR Graphics www.imgtec.com Introduction Who am I? Kevin Sun Working at Imagination Technologies

More information

The Graphics Pipeline

The Graphics Pipeline The Graphics Pipeline Ray Tracing: Why Slow? Basic ray tracing: 1 ray/pixel Ray Tracing: Why Slow? Basic ray tracing: 1 ray/pixel But you really want shadows, reflections, global illumination, antialiasing

More information

CS 220: Introduction to Parallel Computing. Introduction to CUDA. Lecture 28

CS 220: Introduction to Parallel Computing. Introduction to CUDA. Lecture 28 CS 220: Introduction to Parallel Computing Introduction to CUDA Lecture 28 Today s Schedule Project 4 Read-Write Locks Introduction to CUDA 5/2/18 CS 220: Parallel Computing 2 Today s Schedule Project

More information

GPUs and GPGPUs. Greg Blanton John T. Lubia

GPUs and GPGPUs. Greg Blanton John T. Lubia GPUs and GPGPUs Greg Blanton John T. Lubia PROCESSOR ARCHITECTURAL ROADMAP Design CPU Optimized for sequential performance ILP increasingly difficult to extract from instruction stream Control hardware

More information

On-the-fly Vertex Reuse for Massively-Parallel Software Geometry Processing

On-the-fly Vertex Reuse for Massively-Parallel Software Geometry Processing 2018 On-the-fly for Massively-Parallel Software Geometry Processing Bernhard Kerbl Wolfgang Tatzgern Elena Ivanchenko Dieter Schmalstieg Markus Steinberger 5 4 3 4 2 5 6 7 6 3 1 2 0 1 0, 0,1,7, 7,1,2,

More information

What Next? Kevin Walsh CS 3410, Spring 2010 Computer Science Cornell University. * slides thanks to Kavita Bala & many others

What Next? Kevin Walsh CS 3410, Spring 2010 Computer Science Cornell University. * slides thanks to Kavita Bala & many others What Next? Kevin Walsh CS 3410, Spring 2010 Computer Science Cornell University * slides thanks to Kavita Bala & many others Final Project Demo Sign-Up: Will be posted outside my office after lecture today.

More information

20 Years of OpenGL. Kurt Akeley. Copyright Khronos Group, Page 1

20 Years of OpenGL. Kurt Akeley. Copyright Khronos Group, Page 1 20 Years of OpenGL Kurt Akeley Copyright Khronos Group, 2010 - Page 1 So many deprecations! Application-generated object names Color index mode SL versions 1.10 and 1.20 Begin / End primitive specification

More information

GPU Basics. Introduction to GPU. S. Sundar and M. Panchatcharam. GPU Basics. S. Sundar & M. Panchatcharam. Super Computing GPU.

GPU Basics. Introduction to GPU. S. Sundar and M. Panchatcharam. GPU Basics. S. Sundar & M. Panchatcharam. Super Computing GPU. Basics of s Basics Introduction to Why vs CPU S. Sundar and Computing architecture August 9, 2014 1 / 70 Outline Basics of s Why vs CPU Computing architecture 1 2 3 of s 4 5 Why 6 vs CPU 7 Computing 8

More information

Cornell University CS 569: Interactive Computer Graphics. Introduction. Lecture 1. [John C. Stone, UIUC] NASA. University of Calgary

Cornell University CS 569: Interactive Computer Graphics. Introduction. Lecture 1. [John C. Stone, UIUC] NASA. University of Calgary Cornell University CS 569: Interactive Computer Graphics Introduction Lecture 1 [John C. Stone, UIUC] 2008 Steve Marschner 1 2008 Steve Marschner 2 NASA University of Calgary 2008 Steve Marschner 3 2008

More information

Computer Graphics (CS 543) Lecture 1 (Part 1): Introduction to Computer Graphics

Computer Graphics (CS 543) Lecture 1 (Part 1): Introduction to Computer Graphics Computer Graphics (CS 543) Lecture 1 (Part 1): Introduction to Computer Graphics Prof Emmanuel Agu Computer Science Dept. Worcester Polytechnic Institute (WPI) What is Computer Graphics (CG)? Computer

More information

CME 213 S PRING Eric Darve

CME 213 S PRING Eric Darve CME 213 S PRING 2017 Eric Darve Summary of previous lectures Pthreads: low-level multi-threaded programming OpenMP: simplified interface based on #pragma, adapted to scientific computing OpenMP for and

More information

CS130 : Computer Graphics. Tamar Shinar Computer Science & Engineering UC Riverside

CS130 : Computer Graphics. Tamar Shinar Computer Science & Engineering UC Riverside CS130 : Computer Graphics Tamar Shinar Computer Science & Engineering UC Riverside Raster Devices and Images Raster Devices Hearn, Baker, Carithers Raster Display Transmissive vs. Emissive Display anode

More information

Vulkan and Animation 3/13/ &height=285&playerId=

Vulkan and Animation 3/13/ &height=285&playerId= https://media.oregonstate.edu/id/0_q2qgt47o?width= 400&height=285&playerId=22119142 Vulkan and Animation Natasha A. Anisimova (Particle systems in Vulkan) Intel Game Dev The Loop Vulkan Cookbook https://software.intel.com/en-us/articles/using-vulkan-graphics-api-to-render-acloud-of-animated-particles-in-stardust-application

More information

Graphics Hardware, Graphics APIs, and Computation on GPUs. Mark Segal

Graphics Hardware, Graphics APIs, and Computation on GPUs. Mark Segal Graphics Hardware, Graphics APIs, and Computation on GPUs Mark Segal Overview Graphics Pipeline Graphics Hardware Graphics APIs ATI s low-level interface for computation on GPUs 2 Graphics Hardware High

More information

Scanline Rendering 2 1/42

Scanline Rendering 2 1/42 Scanline Rendering 2 1/42 Review 1. Set up a Camera the viewing frustum has near and far clipping planes 2. Create some Geometry made out of triangles 3. Place the geometry in the scene using Transforms

More information

CSCI 402: Computer Architectures. Parallel Processors (2) Fengguang Song Department of Computer & Information Science IUPUI.

CSCI 402: Computer Architectures. Parallel Processors (2) Fengguang Song Department of Computer & Information Science IUPUI. CSCI 402: Computer Architectures Parallel Processors (2) Fengguang Song Department of Computer & Information Science IUPUI 6.6 - End Today s Contents GPU Cluster and its network topology The Roofline performance

More information

CONSOLE ARCHITECTURE

CONSOLE ARCHITECTURE CONSOLE ARCHITECTURE Introduction Part 1 What is a console? Console components Differences between consoles and PCs Benefits of console development The development environment Console game design What

More information

Lecture 2. Shaders, GLSL and GPGPU

Lecture 2. Shaders, GLSL and GPGPU Lecture 2 Shaders, GLSL and GPGPU Is it interesting to do GPU computing with graphics APIs today? Lecture overview Why care about shaders for computing? Shaders for graphics GLSL Computing with shaders

More information

Scan Conversion of Polygons. Dr. Scott Schaefer

Scan Conversion of Polygons. Dr. Scott Schaefer Scan Conversion of Polygons Dr. Scott Schaefer Drawing Rectangles Which pixels should be filled? /8 Drawing Rectangles Is this correct? /8 Drawing Rectangles What if two rectangles overlap? 4/8 Drawing

More information

Deep Learning: Transforming Engineering and Science The MathWorks, Inc.

Deep Learning: Transforming Engineering and Science The MathWorks, Inc. Deep Learning: Transforming Engineering and Science 1 2015 The MathWorks, Inc. DEEP LEARNING: TRANSFORMING ENGINEERING AND SCIENCE A THE NEW RISE ERA OF OF GPU COMPUTING 3 NVIDIA A IS NEW THE WORLD S ERA

More information

Mobile Graphics Ecosystem. Tom Olson OpenGL ES working group chair

Mobile Graphics Ecosystem. Tom Olson OpenGL ES working group chair OpenGL ES in the Mobile Graphics Ecosystem Tom Olson OpenGL ES working group chair Director, Graphics Research, ARM Ltd 1 Outline Why Mobile Graphics? OpenGL ES Overview Getting Started with OpenGL ES

More information

ECE 574 Cluster Computing Lecture 18

ECE 574 Cluster Computing Lecture 18 ECE 574 Cluster Computing Lecture 18 Vince Weaver http://web.eece.maine.edu/~vweaver vincent.weaver@maine.edu 2 April 2019 HW#8 was posted Announcements 1 Project Topic Notes I responded to everyone s

More information

GPU Architecture. Michael Doggett Department of Computer Science Lund university

GPU Architecture. Michael Doggett Department of Computer Science Lund university GPU Architecture Michael Doggett Department of Computer Science Lund university GPUs from my time at ATI R200 Xbox360 GPU R630 R610 R770 Let s start at the beginning... Graphics Hardware before GPUs 1970s

More information

CSE4030 Introduction to Computer Graphics

CSE4030 Introduction to Computer Graphics CSE4030 Introduction to Computer Graphics Dongguk University Jeong-Mo Hong Timetable 00:00~00:10 Introduction (English) 00:10~00:50 Topic 1 (English) 00:50~00:60 Q&A (English, Korean) 01:00~01:40 Topic

More information

Multi-Processors and GPU

Multi-Processors and GPU Multi-Processors and GPU Philipp Koehn 7 December 2016 Predicted CPU Clock Speed 1 Clock speed 1971: 740 khz, 2016: 28.7 GHz Source: Horowitz "The Singularity is Near" (2005) Actual CPU Clock Speed 2 Clock

More information

GPGPU. Peter Laurens 1st-year PhD Student, NSC

GPGPU. Peter Laurens 1st-year PhD Student, NSC GPGPU Peter Laurens 1st-year PhD Student, NSC Presentation Overview 1. What is it? 2. What can it do for me? 3. How can I get it to do that? 4. What s the catch? 5. What s the future? What is it? Introducing

More information

Accessing the GPU & the GPUImage Library

Accessing the GPU & the GPUImage Library Accessing the GPU & the GPUImage Library Instructor - Simon Lucey 16-423 - Designing Computer Vision Apps Today Motivation GPU OpenGL GPUImage Library Algorithm Software Architecture SOC Hardware Correlation

More information

GPU ARCHITECTURE Chris Schultz, June 2017

GPU ARCHITECTURE Chris Schultz, June 2017 Chris Schultz, June 2017 MISC All of the opinions expressed in this presentation are my own and do not reflect any held by NVIDIA 2 OUTLINE Problems Solved Over Time versus Why are they different? Complex

More information

Introduction to Multicore architecture. Tao Zhang Oct. 21, 2010

Introduction to Multicore architecture. Tao Zhang Oct. 21, 2010 Introduction to Multicore architecture Tao Zhang Oct. 21, 2010 Overview Part1: General multicore architecture Part2: GPU architecture Part1: General Multicore architecture Uniprocessor Performance (ECint)

More information

CS450/550. Pipeline Architecture. Adapted From: Angel and Shreiner: Interactive Computer Graphics6E Addison-Wesley 2012

CS450/550. Pipeline Architecture. Adapted From: Angel and Shreiner: Interactive Computer Graphics6E Addison-Wesley 2012 CS450/550 Pipeline Architecture Adapted From: Angel and Shreiner: Interactive Computer Graphics6E Addison-Wesley 2012 0 Objectives Learn the basic components of a graphics system Introduce the OpenGL pipeline

More information

CENG 477 Introduction to Computer Graphics. Graphics Hardware and OpenGL

CENG 477 Introduction to Computer Graphics. Graphics Hardware and OpenGL CENG 477 Introduction to Computer Graphics Graphics Hardware and OpenGL Introduction Until now, we focused on graphic algorithms rather than hardware and implementation details But graphics, without using

More information

Survey in Computer Graphics Computer Graphics and Visualization

Survey in Computer Graphics Computer Graphics and Visualization Example of a Marble Ball Where did this image come from? Fall 2010 What hardware/software/algorithms did we need to produce it? 2 A Basic Graphics System History of Computer Graphics 1200-2008 Input devices

More information

Fast Interactive Sand Simulation for Gesture Tracking systems Shrenik Lad

Fast Interactive Sand Simulation for Gesture Tracking systems Shrenik Lad Fast Interactive Sand Simulation for Gesture Tracking systems Shrenik Lad Project Guide : Vivek Mehta, Anup Tapadia TouchMagix media labs TouchMagix www.touchmagix.com Interactive display solutions Interactive

More information

Blink: 3D Display Multiplexing for Virtualized Applications

Blink: 3D Display Multiplexing for Virtualized Applications : 3D Display Multiplexing for Virtualized Applications January 20, 2006 : 3D Display Multiplexing for Virtualized Applications Motivation Sprites and Tiles Lessons Learned GL in, GL out Communication Protocol

More information

Programming shaders & GPUs Christian Miller CS Fall 2011

Programming shaders & GPUs Christian Miller CS Fall 2011 Programming shaders & GPUs Christian Miller CS 354 - Fall 2011 Fixed-function vs. programmable Up until 2001, graphics cards implemented the whole pipeline for you Fixed functionality but configurable

More information

Accessing the GPU & the GPUImage Library

Accessing the GPU & the GPUImage Library Accessing the GPU & the GPUImage Library Instructor - Simon Lucey 16-623 - Advanced Computer Vision Apps Today Motivation GPU OpenGL GPUImage Library Algorithm Software Architecture SOC Hardware Correlation

More information

3-D Accelerator on Chip

3-D Accelerator on Chip 3-D Accelerator on Chip Third Prize 3-D Accelerator on Chip Institution: Participants: Instructor: Donga & Pusan University Young-Hee Won, Jin-Sung Park, Woo-Sung Moon Sam-Hak Jin Design Introduction Recently,

More information

2.11 Particle Systems

2.11 Particle Systems 2.11 Particle Systems 320491: Advanced Graphics - Chapter 2 152 Particle Systems Lagrangian method not mesh-based set of particles to model time-dependent phenomena such as snow fire smoke 320491: Advanced

More information

The Graphics Pipeline and OpenGL I: Transformations!

The Graphics Pipeline and OpenGL I: Transformations! ! The Graphics Pipeline and OpenGL I: Transformations! Gordon Wetzstein! Stanford University! EE 267 Virtual Reality! Lecture 2! stanford.edu/class/ee267/!! Albrecht Dürer, Underweysung der Messung mit

More information

CSE 167: Introduction to Computer Graphics Lecture #5: Rasterization. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2015

CSE 167: Introduction to Computer Graphics Lecture #5: Rasterization. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2015 CSE 167: Introduction to Computer Graphics Lecture #5: Rasterization Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2015 Announcements Project 2 due tomorrow at 2pm Grading window

More information

Today. Rendering algorithms. Rendering algorithms. Images. Images. Rendering Algorithms. Course overview Organization Introduction to ray tracing

Today. Rendering algorithms. Rendering algorithms. Images. Images. Rendering Algorithms. Course overview Organization Introduction to ray tracing Today Rendering Algorithms Course overview Organization Introduction to ray tracing Spring 2009 Matthias Zwicker Universität Bern Rendering algorithms Problem statement Given computer representation of

More information

EE , GPU Programming

EE , GPU Programming EE 4702-1, GPU Programming When / Where Here (1218 Patrick F. Taylor Hall), MWF 11:30-12:20 Fall 2017 http://www.ece.lsu.edu/koppel/gpup/ Offered By David M. Koppelman Room 3316R Patrick F. Taylor Hall

More information

Graphics and Imaging Architectures

Graphics and Imaging Architectures Graphics and Imaging Architectures Kayvon Fatahalian http://www.cs.cmu.edu/afs/cs/academic/class/15869-f11/www/ About Kayvon New faculty, just arrived from Stanford Dissertation: Evolving real-time graphics

More information

Evolution of CPUs & Memory in Video Game Consoles. Curtis Geiger & Matthew Meehan

Evolution of CPUs & Memory in Video Game Consoles. Curtis Geiger & Matthew Meehan Evolution of CPUs & Memory in Video Game Consoles Curtis Geiger & Matthew Meehan 1 ST GENERATION Magnavox Odyssey first console, released 1972 No CPU or Memory entirely made up of transistors, resistors,

More information

Real-Time Buffer Compression. Michael Doggett Department of Computer Science Lund university

Real-Time Buffer Compression. Michael Doggett Department of Computer Science Lund university Real-Time Buffer Compression Michael Doggett Department of Computer Science Lund university Project 3D graphics project Demo, Game Implement 3D graphics algorithm(s) C++/OpenGL(Lab2)/iOS/android/3D engine

More information

Shaders. Slide credit to Prof. Zwicker

Shaders. Slide credit to Prof. Zwicker Shaders Slide credit to Prof. Zwicker 2 Today Shader programming 3 Complete model Blinn model with several light sources i diffuse specular ambient How is this implemented on the graphics processor (GPU)?

More information

CS427 Multicore Architecture and Parallel Computing

CS427 Multicore Architecture and Parallel Computing CS427 Multicore Architecture and Parallel Computing Lecture 6 GPU Architecture Li Jiang 2014/10/9 1 GPU Scaling A quiet revolution and potential build-up Calculation: 936 GFLOPS vs. 102 GFLOPS Memory Bandwidth:

More information

Grafica Computazionale: Lezione 30. Grafica Computazionale. Hiding complexity... ;) Introduction to OpenGL. lezione30 Introduction to OpenGL

Grafica Computazionale: Lezione 30. Grafica Computazionale. Hiding complexity... ;) Introduction to OpenGL. lezione30 Introduction to OpenGL Grafica Computazionale: Lezione 30 Grafica Computazionale lezione30 Introduction to OpenGL Informatica e Automazione, "Roma Tre" May 20, 2010 OpenGL Shading Language Introduction to OpenGL OpenGL (Open

More information

Fast Hardware For AI

Fast Hardware For AI Fast Hardware For AI Karl Freund karl@moorinsightsstrategy.com Sr. Analyst, AI and HPC Moor Insights & Strategy Follow my blogs covering Machine Learning Hardware on Forbes: http://www.forbes.com/sites/moorinsights

More information

GPU Architecture. Alan Gray EPCC The University of Edinburgh

GPU Architecture. Alan Gray EPCC The University of Edinburgh GPU Architecture Alan Gray EPCC The University of Edinburgh Outline Why do we want/need accelerators such as GPUs? Architectural reasons for accelerator performance advantages Latest GPU Products From

More information

Rendering Algorithms: Real-time indirect illumination. Spring 2010 Matthias Zwicker

Rendering Algorithms: Real-time indirect illumination. Spring 2010 Matthias Zwicker Rendering Algorithms: Real-time indirect illumination Spring 2010 Matthias Zwicker Today Real-time indirect illumination Ray tracing vs. Rasterization Screen space techniques Visibility & shadows Instant

More information

Applications and Implementations

Applications and Implementations Copyright Khronos Group, 2010 - Page 1 Applications and Implementations Hwanyong LEE CTO and Technical Marketing Director HUONE OpenVG Royalty-free open standard API Low-level 2D vector graphics rendering

More information

GPU Computing and Its Applications

GPU Computing and Its Applications GPU Computing and Its Applications Bhavana Samel 1, Shubhrata Mahajan 2, Prof.A.M.Ingole 3 1 Student, Dept. of Computer Engineering, BVCOEL Pune, Maharashtra, India 2Student, Dept. of Computer Engineering,

More information

Whiz-Bang Graphics and Media Performance for Java Platform, Micro Edition (JavaME)

Whiz-Bang Graphics and Media Performance for Java Platform, Micro Edition (JavaME) Whiz-Bang Graphics and Media Performance for Java Platform, Micro Edition (JavaME) Pavel Petroshenko, Sun Microsystems, Inc. Ashmi Bhanushali, NVIDIA Corporation Jerry Evans, Sun Microsystems, Inc. Nandini

More information

CS8803SC Software and Hardware Cooperative Computing GPGPU. Prof. Hyesoon Kim School of Computer Science Georgia Institute of Technology

CS8803SC Software and Hardware Cooperative Computing GPGPU. Prof. Hyesoon Kim School of Computer Science Georgia Institute of Technology CS8803SC Software and Hardware Cooperative Computing GPGPU Prof. Hyesoon Kim School of Computer Science Georgia Institute of Technology Why GPU? A quiet revolution and potential build-up Calculation: 367

More information

Parallel Computing: Parallel Architectures Jin, Hai

Parallel Computing: Parallel Architectures Jin, Hai Parallel Computing: Parallel Architectures Jin, Hai School of Computer Science and Technology Huazhong University of Science and Technology Peripherals Computer Central Processing Unit Main Memory Computer

More information

Accelerator cards are typically PCIx cards that supplement a host processor, which they require to operate Today, the most common accelerators include

Accelerator cards are typically PCIx cards that supplement a host processor, which they require to operate Today, the most common accelerators include 3.1 Overview Accelerator cards are typically PCIx cards that supplement a host processor, which they require to operate Today, the most common accelerators include GPUs (Graphics Processing Units) AMD/ATI

More information

Advanced Computer Graphics (CS & SE ) Lecture 7

Advanced Computer Graphics (CS & SE ) Lecture 7 Advanced Computer Graphics (CS & SE 233.420) Lecture 7 CREDITS Bill Mark, NVIDIA Programmable Graphics Technology, SIGGRAPH 2002 Course. David Kirk, GPUs and CPUs:The Uneasy Alliance, Panel Presentation,

More information

NVLink on NVIDIA GeForce RTX 2080 & 2080 Ti in Windows 10

NVLink on NVIDIA GeForce RTX 2080 & 2080 Ti in Windows 10 https://www.pugetsystems.com Home / View All Articles / NVLink on NVIDIA GeForce RTX 2080 & 2080 Ti in Windows 10 Read this article at https://www.pugetsystems.com/guides/1253 NVLink on NVIDIA GeForce

More information

Threading Hardware in G80

Threading Hardware in G80 ing Hardware in G80 1 Sources Slides by ECE 498 AL : Programming Massively Parallel Processors : Wen-Mei Hwu John Nickolls, NVIDIA 2 3D 3D API: API: OpenGL OpenGL or or Direct3D Direct3D GPU Command &

More information

CS 316: Multicore/GPUs

CS 316: Multicore/GPUs CS 316: Multicore/GPUs Kavita Bala Fall 2007 Computer Science Cornell University Announcements Core Wars will be out in the next couple of days Aim at having fun! Number of points allocated to it is small

More information

Bifurcation Between CPU and GPU CPUs General purpose, serial GPUs Special purpose, parallel CPUs are becoming more parallel Dual and quad cores, roadm

Bifurcation Between CPU and GPU CPUs General purpose, serial GPUs Special purpose, parallel CPUs are becoming more parallel Dual and quad cores, roadm XMT-GPU A PRAM Architecture for Graphics Computation Tom DuBois, Bryant Lee, Yi Wang, Marc Olano and Uzi Vishkin Bifurcation Between CPU and GPU CPUs General purpose, serial GPUs Special purpose, parallel

More information

Bifrost - The GPU architecture for next five billion

Bifrost - The GPU architecture for next five billion Bifrost - The GPU architecture for next five billion Hessed Choi Senior FAE / ARM ARM Tech Forum June 28 th, 2016 Vulkan 2 ARM 2016 What is Vulkan? A 3D graphics API for the next twenty years Logical successor

More information

Deep Learning Accelerators

Deep Learning Accelerators Deep Learning Accelerators Abhishek Srivastava (as29) Samarth Kulshreshtha (samarth5) University of Illinois, Urbana-Champaign Submitted as a requirement for CS 433 graduate student project Outline Introduction

More information

1. Introduction 2. Methods for I/O Operations 3. Buses 4. Liquid Crystal Displays 5. Other Types of Displays 6. Graphics Adapters 7.

1. Introduction 2. Methods for I/O Operations 3. Buses 4. Liquid Crystal Displays 5. Other Types of Displays 6. Graphics Adapters 7. 1. Introduction 2. Methods for I/O Operations 3. Buses 4. Liquid Crystal Displays 5. Other Types of Displays 6. Graphics Adapters 7. Optical Discs 1 Structure of a Graphics Adapter Video Memory Graphics

More information

Using Graphics Chips for General Purpose Computation

Using Graphics Chips for General Purpose Computation White Paper Using Graphics Chips for General Purpose Computation Document Version 0.1 May 12, 2010 442 Northlake Blvd. Altamonte Springs, FL 32701 (407) 262-7100 TABLE OF CONTENTS 1. INTRODUCTION....1

More information

! Readings! ! Room-level, on-chip! vs.!

! Readings! ! Room-level, on-chip! vs.! 1! 2! Suggested Readings!! Readings!! H&P: Chapter 7 especially 7.1-7.8!! (Over next 2 weeks)!! Introduction to Parallel Computing!! https://computing.llnl.gov/tutorials/parallel_comp/!! POSIX Threads

More information

GPGPU Applications. for Hydrological and Atmospheric Simulations. and Visualizations on the Web. Ibrahim Demir

GPGPU Applications. for Hydrological and Atmospheric Simulations. and Visualizations on the Web. Ibrahim Demir GPGPU Applications for Hydrological and Atmospheric Simulations and Visualizations on the Web Ibrahim Demir Big Data We are collecting and generating data on a petabyte scale (1Pb = 1,000 Tb = 1M Gb) Data

More information

Applications and Implementations

Applications and Implementations Copyright Khronos Group, 2010 - Page 1 Applications and Implementations Hwanyong LEE CTO and Technical Marketing Director HUONE System Integration Application Acceleration Authoring and accessibility Khronos

More information

Generations of Consumer Computer Graphics as Seen in Demos. Markku Reunanen, Aalto University

Generations of Consumer Computer Graphics as Seen in Demos. Markku Reunanen, Aalto University Generations of Consumer Computer Graphics as Seen in Demos Markku Reunanen, Aalto University Outline Consumer computer graphics Different generations with examples Conclusion Further reading The microcomputer

More information

Case 1:17-cv SLR Document 1-3 Filed 01/23/17 Page 1 of 33 PageID #: 60 EXHIBIT C

Case 1:17-cv SLR Document 1-3 Filed 01/23/17 Page 1 of 33 PageID #: 60 EXHIBIT C Case 1:17-cv-00064-SLR Document 1-3 Filed 01/23/17 Page 1 of 33 PageID #: 60 EXHIBIT C Case 1:17-cv-00064-SLR Document 1-3 Filed 01/23/17 Page 2 of 33 PageID #: 61 U.S. Patent No. 7,633,506 VIZIO / Sigma

More information

Programming Graphics Hardware

Programming Graphics Hardware Tutorial 5 Programming Graphics Hardware Randy Fernando, Mark Harris, Matthias Wloka, Cyril Zeller Overview of the Tutorial: Morning 8:30 9:30 10:15 10:45 Introduction to the Hardware Graphics Pipeline

More information

Today. Rendering algorithms. Rendering algorithms. Images. Images. Rendering Algorithms. Course overview Organization Introduction to ray tracing

Today. Rendering algorithms. Rendering algorithms. Images. Images. Rendering Algorithms. Course overview Organization Introduction to ray tracing Today Rendering Algorithms Course overview Organization Introduction to ray tracing Spring 2010 Matthias Zwicker Universität Bern Rendering algorithms Problem statement Given computer representation of

More information

A Low Cost Tile-based 3D Graphics Full Pipeline with Real-time Performance Monitoring Support for OpenGL ES in Consumer Electronics

A Low Cost Tile-based 3D Graphics Full Pipeline with Real-time Performance Monitoring Support for OpenGL ES in Consumer Electronics A Low Cost Tile-based 3 Graphics Full Pipeline with Real-time Performance Monitoring Support for OpenGL ES in Consumer Electronics Ruei-Ting Gu, Tse-Chen Yeh, Wei-Sheng Hunag, Ting-Yun Huang, Chung-Hua

More information