GPU Programming and Architecture: Course Overview

Transcription

1 Lectures GPU Programming and Architecture: Course Overview Patrick Cozzi University of Pennsylvania CIS Spring 2012 Monday and Wednesday 9-10:30am Moore 212 Lectures will be recorded Image from Instructor Patrick Cozzi: pjcozzi@siggraph.org Instructor Include [CIS565] in subject line Office Hours SIG Lab Monday and Wednesday, 10:30-11:00am Just see me after class If you are curious, see 1

2 Teaching Assistant CIS 565 Hall of Fame Varun Sampath: Office Hours SIG Lab Tuesday, 5-6pm Thursday, 3-4pm Jon McCaffrey Krishnan Ramachandran Varun Sampath Starting at NVIDIA this summer Are you next? If you are curious, see Course Website Google Group Schedule, reading, slides, audio, homework, etc. Signup: Be active; let s build a course community 2

3 GitHub Used for course materials, homeworks, and the final project Create an account: Join our GitHub organization: Prerequisites CIS 460/560 CIS 371 or CIS 501 Strong C or C++ Who is new to source control? Books Programming Massively Parallel Processors 2010, David Kirk and Wen-mei Hwu Old draft: GPU Graphics Processing Unit Is it still just for graphics? OpenGL Insights 2012, Patrick Cozzi and Christophe Riccio, Editors Selected readings handed out in class Images from and 3

4 New: Start with GPU architecture programming model for GPU Compute GPU Compute example: conjunction analysis Parallel algorithms that form building blocks 4

5 example: Scan Given: Historical and modern graphics pipeline Compute: Graphics Pipeline In parallel! New: WebGL WebGL Demos OpenGL / WebGL Graphics Pipeline WebGL Skin WebGL Water 5

6 Real-Time Rendering Real-Time Rendering Real-Time Rendering OpenGL / WebGL Graphics Pipeline GPU Compute + Real-Time Rendering New: Mobile Mobile Real-Time Rendering OpenGL / WebGL Graphics Pipeline 6

7 Performance! Student Presentations. Examples: To scale! Mobile Real-Time Rendering OpenGL / WebGL Graphics Pipeline Computer Vision Fluid Simulation Financial Analysis Volume Rendering Order-Independent Translucency Architecture, Compute, Rendering, etc. Topics are up to you Grading Homeworks (5) 40% Student Presentation 10% Final Project 40% Final 10% Homework Submission Push your submission to GitHub by midnight on the due date Bonus Days: Five per person Homework only; not for presentation or project 7

8 Homework Submission Homework Submission Late Policy: One second to one week late: 50% deduction More than one week late: no credit Effort Effort Student Due date Time Pro boxer Fight night Time Academic Integrity GPU Requirements Homework and the project require an NVIDIA GeForce 8 series or higher Update your drivers: What GPU do I have? What OpenGL/OpenCL/ version: 8

9 GPU Requirements Lab Resources Moore 100b - NVIDIA GeForce 9800s SIG Lab - Most machines have at least NVIDIA GeForce 8800s. Two machines have a GeForce 480, and one machine has a Fermi Tesla card Contact Varun CPU and GPU Trends FLOPS FLoating-point OPerations per Second GFLOPS - One billion (10 9 ) FLOPS TFLOPS 1,000 GFLOPS CPU and GPU Trends CPU and GPU Trends Compute Intel Core i7 4 cores 100 GFLOP NVIDIA GTX cores 1 TFLOP Memory Bandwidth System Memory 60 GB/s NVIDIA GT GB/s Install Base Over 200 million NVIDIA G80s shipped Chart from: 9

10 Class Exercise Parallel sorting Reminders Include [CIS565] in subject line. Signup for our google group: Join our GitHub organization: Signup: Organization: Spring-2012 No class or office hours Monday, 01/16. 10